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Data Analytics to Drive Business Value

Did you know that data can open up countless opportunities for your business to thrive?

In today’s fast-paced digital landscape, data analytics is not just a buzzword, it’s a crucial tool for driving business value.

But what is the role of data analytics?

It’s more than just having access to data. It’s about empowering your business and ensure sustainability with the right information, tools, and resources to analyze data and extract meaningful insights.

According to recent reports, 73.5% of respondents in data-leading companies across the globe reported that their decision-making processes were always data-driven.

This statistic underscores the importance of embracing data analytics as a driving force behind a business’s success.

So, are you ready to unlock the full potential of your data? Read on!

How can data analytics contribute to business value?

Let’s break down 8 practical ways data analytics can add value to your business:

  • Business Goal Alignment
  • Productivity Enhancement
  • Problem-Solving
  • Better Data Management
  • Faster Communication
  • Growth Opportunities
  • Data Monetization
  • Personalization

Dive into the advantages and learn strategies to attain them:

  1. Setting Clear Goals: Measuring Success with KPIs

Data analytics has revolutionized every facet of business and key performance indicators (KPIs) are no exception. In the past, KPIs mainly focused on sales and revenue metrics, but now they encompass a wider range of factors in your business, like clicks, customer visits, average user session duration, lead conversion rates, and more.

The emergence of Artificial Intelligence (AI) models has introduced new KPIs tailored to measure the performance of these models specifically. These analytical measurements align with your business objectives rather than relying on standard metrics to achieve desired outcomes. Some data analytics business growth examples are shared for your reference.

For instance, Amazon utilizes metrics like Weighted Absolute Percentage Error (WAPE) to gauge the accuracy of forecasts compared to the actual outcomes for a given sample. This use of data analytics ensures that KPIs are finely tuned to reflect the real-world impact and effectiveness of business strategies and AI technologies.

  1. Enhance Productivity

Data analytics is your strategy for making smarter decisions. By diving into the data, leaders can craft strategies backed by solid evidence, really understand their customers to fine-tune marketing efforts, and, ultimately, boost productivity.

Analyzing big data analytics market can help you spot trends and patterns. With that knowledge in hand, you can tailor your products or services to meet exactly what your customers are looking for. And the more you know about your customers, the better you can build loyalty andramp up sales.

So, data analytics isn’t just about numbers; it’s about knowing your customers inside and out and using that knowledge to fuel your business growth.

  1. Reduce Problems

Data analytics can assist in minimizing business challenges. With analytics, you understand exactly who your customers are and what they want, making your marketing efforts effective.

It helps in customer segmentationby sorting your customers into groups based on who they are and what they like. In revenue forecasting, analytics can help you mitigate problems, giving you a clearer view of where your business is headed financially.

Analytics can pinpoint where you’re overspending or where there’s room for efficiency improvements, helping you save those precious dollars.

Data analytics helps streamline your processes and activities for maximum efficiency and quality. We all face uncertainties, but with analytics, you can identify and tackle potential threats head-on, keeping your business safe and sound.

For example, the American Express Data Analytics, Risk, and Technology (DART) Laboratory helps to tackle risks that come from how people behave and the decisions they make. The main aim of the lab is to deliver tech solutions that help us manage business risks better and help in crisis management.

  1. Reduction of Duplicate Data

Data duplication is a big hurdle when you’re trying to analyze data accurately and efficiently. Data analytics and AI can help sniff out and eliminate duplicate data in those massive datasets you’re dealing with. Not only does this save you storage space, but it also turbocharges your data processing speed.

An example of data analytics to drive business value is Natural Language Processing or NLP. It helps you analyze unstructured data like text to spot possible duplicates based on context and meaning.

Take Microsoft, for example. They’re using NLP for all sentiment analysis, figuring out topics, detecting languages, pulling out key phrases, and sorting documents into categories.

  1. Streamline Processes by Identifying Experts

Did you know that advanced analytics can help us find the ideal person to solve a specific question or issue?

Let me give you an example. CData Software, a platform for assessing data, uses advanced analytics to pinpoint the experts in their support team. They track how many tickets each support representative handles using Atlassian Jira. They also organize the tickets by the products or services customers are asking about.

Then, their sales team takes this data for business analytics and puts it into reports and dashboards. This helps them figure out which support representative is good to contact when a potential customer has a technical question about a certain product, feature, or function.

This system has made teamwork within the company better and has left customers happier with the support they receive.

  1. Unlock New Opportunities

With advanced data analytics, businesses can easily predict what customers want before they even know it themselves. By digging deep into data, businesses can spot hidden patterns, see trends before they happen, and even forecast future outcomes with impressive accuracy.

For example, Avionos is an expert in digital consultancy and uses advanced analytics to help its clients uncover exciting new opportunities. By diving into customer behavior, global data analytics market size, trends, and more, they can pinpoint what resonates with customers.

  1. Data Monetization

A lot of companies out there have valuable information they can use to make money through advanced analysis. Uses of data analytics make them find hidden treasures in your data that others would pay for. Some data analytics business growth examples are discussed in the underlying sections.

For example, Katalys has rolled out a new solution called Katalys Automated Monetization (K.A.M). It’s designed to help publishers boost revenue and allow brandsto expand their customer base.

The key is to find a platform that allows you to share data easily and supports advanced analytics. This way, you can maximize the value of your data by pinpointing changes that can lead to better outcomes.

  1. Personalizing Experiences

Advanced analytics is important to personalize customer experience. It helps to enhance customer satisfaction and engagement. For example, Sports Buff teamed up with Ensono, a tech partner, to make watching sports even better. During FIFA World Cup Qatar 2022, they added cool graphics to the broadcast, giving fans extra information and ways to get involved.

They collected data from different places about what fans like and don’t like, then used that information to make sure everyone gets a personalized experience.

In today’s business landscape, many companies have huge sets of data, yet only a handful know how to truly tap into its potential. This advantage doesn’t just mean better investment outcomes; it can mean surpassing expectations altogether.

Let’s take a look at how data analytics influences the investment journey!
python language

What is the Impact of Data Analytics on the Investment Lifecycle?

Data analytics plays a pivotal role in every stage of the investment process, aiding companies in achieving Return on Investment (ROI) and optimizing returns. It helps in the following:

  • Pre-Acquisition Analysis: Before acquiring a company, investors rely on data analytics to forecast post-acquisition revenue potential. Visibility into existing revenue and pipeline data helps estimate the revenue runway after acquisition.
  • Examining Cost Structures: Besides revenue analysis, evaluating the cost structure is equally vital in pre-acquisition analytics. Transitioning into the entry period requires a deeper level of data analysis for both revenue and costs.

Data analytics industry trends are here to drive future sustainability. Limited pre-acquisition data emphasizes the significance of data analysis during the investment and growth phases. Compiling portfolio data offers a comprehensive view, unveiling opportunities for maximizing ROI.

For example, analyzing a portfolio company’s data assets can reveal valuable insights. These are:

  1. Understanding Your Business: It will take a closer look at what’s happening with your top-selling products or services. If sales are lower than expected, you might need to adjust your marketing strategies to give them a boost.
  2. Identifying Your Ideal Customers: The analysis can pinpoint common characteristics among your most valuable customers. This helps create customer segments and ideal customer profiles (ICPs), so you can tailor your efforts to attract more of these high-value customers.
  3. Streamlining Your Operations: It digs into your data to find out if certain products are costing you more to produce or manage. Understanding the relationship between costs and revenue for these products can identify areas where you can cut waste and optimize efficiency.

According to recent insights, using AI can help you strategize financial policies. It means you gather insights from data to formulate investment strategies and create personalized products that fit your needs.

In summary, data analytics serves as a cornerstone in investment decision-making, offering actionable insights across various stages of the investment lifecycle.

Now read about data analytics industry overview in the following sections.

Role of Data Analytics to Drive Value and Maximize ROI

Data Analytics Industry Growth

When you’re steering your company culture towards making decisions backed by data, it’s smart to start by understanding how data can boost value and investments. Businesses need to pinpoint which data points are the most valuable.

Both Private Equity (PE) firms and the leaders of the companies need to have ongoing access to the following regularly updated information:

  1. Clear Product and Service Index: You need a straightforward list of everything your company offers. Each item should have its own code or description so you can easily tell them apart. This helps in understanding their prices and value better. If things are grouped together, it’s hard to see what each one brings to the table individually.
  2. Central Customer Database: It’s crucial to have one big list of all your customers. And if you have their info in different places, it’s essential to use the same codes or descriptions for them everywhere. This also goes for how you name businesses across different systems. Using different names for the same thing can mess up your data and make analysis harder.
  3. Additional Lists as Needed: Depending on how your business works, you might need other lists too. These could include things like lists of buildings, employees, different cost areas, or how your departments are set up.
  4. Company-wide Sales Tracking: You should always have access to updated lists showing all your sales. It’s helpful to break these down by things like region or product type. This makes it easier to see how different parts of your business are doing.
  5. Understanding All Business Costs: It’s not just about how much money you make from selling something. You also need to know how much it costs to make or deliver it. Sometimes, regular accounting systems don’t give the full picture of how much you’re really earning from something. So, it’s important to track all the costs involved.

When it comes to tracking and understanding your data, there are a bunch of tools out there to help you visualize, analyze, and stay organized. But, with so many options, it can be tough to figure out which one fits your needs best.

Let’s dive in and find some of the best tools!

4 Best AI Data Analysis Tools in 2024 and 2025

Some data analytics industry trends and tools for you to explore are discussed in the underlying section.

  1. Microsoft Power BI

Microsoft Power BI is a popular tool for business individuals. It helps them properly make sense of their data. You can bring in data from all sorts of places and then create reports and dashboards to visualize it, which can give you some really neat insights.

Additionally, you can also use it to build machine learning models and tap into some other smart features to help you analyze your data even more.

Power BI comes well with other integrations like Excel. It isresponsive and easy to use. However, it can be pricey compared to some other options out there.

Curious about mastering data visualization for the industry? Keep reading!

  1. Microsoft Excel

Microsoft Excel has been a top-notch tool for data analysis since it first came out, and it’s still holding its own today.

With Excel’s Data Analysis Toolpak, you can dive into your data and make different charts and graphs to understand it better. It filters data quickly using search boxes and pivot tables.

Additionally, you can get into making machine learning models without writting a single line of code, using formulas to analyze data in different ways, and even building complex neural networks.

However, Excel does have its limits. It’s built around the idea of spreadsheets, which can take a bit of time to get the hang of all its features, especially if you’re not into coding.

  1. Akkio

Akkio is a good tool for business individuals who want to do dataanalysis and data forecasting. With Akkio, you don’t need to do coding to dive into your data. It is lead scoring, which helps you figure out which leads are worth chasing after.

Akkio helps you predict future trends based on your data. Plus, it’s easy to use and connects seamlessly with other tools you might already be using. So, you can import and export data easily.

For further insight into Akkio, learn more!

  1. Qlik

QlikView is a data visualization and business intelligence tool. Itallows AI technology to help you analyze your data.

One of the things individuals like about QlikView is its user-friendly setup. It’s a good tool for teamwork. You can collaborate with your team seamlessly thanks to features like drag-and-drop editing and easy workflows.

While QlikView is a platform with good functionality, it’s important to consider a couple of things. Firstly, it does come with a higher price tag compared to some alternatives. Secondly, its AI features might not be as extensive as some other options out there.


How do you make your organizations foster engagement and embrace a data-driven culture? This blog offers 8 essential strategies to leverage data analytics and elevate your business’s value.

By prioritizing data in your decision-making processes, your organization can uncover numerous opportunities to create value for everyone involved. Here, we have discussed the pivotal role of data analytics across the investment lifecycle and its profound impact on maximizing Return On Investment (ROI).

With a dedicated emphasis on data in decision-making processes, businesses unlock opportunities to generate value for all involved parties. Here, we have discussed the role of data analytics in the investment lifecycle and in maximizing ROI.

Furthermore, we provide a comprehensive overview of popular data analytics tools, like Microsoft Excel, Microsoft Power BI, Qlik, and Akkio, to empower your data-driven initiatives.

Grab the data-driven strategies and explore the best programming tools for 2025 to unlock the full potential of your organization!


  1. Belghith, M., Ben Ammar, H., Masmoudi, F. and Elloumi, A., 2021, December. Data Visualization for Industry 4.0: Developing Dashboards with Power BI–A Case Study in a Pharmaceutical Company. In International Conference Design and Modeling of Mechanical Systems(pp. 402-408). Cham: Springer International Publishing.


  1. Dong, J.Q. and Yang, C.H., 2020. Business value of big data analytics: A systems-theoretic approach and empirical test. Information & Management.


  1. Bordeleau, F.E., Mosconi, E. and de Santa-Eulalia, L.A., 2020. Business intelligence and analytics value creation in Industry 4.0: a multiple case study in manufacturing medium enterprises.


  1. Ciampi, F., Demi, S., Magrini, A., Marzi, G. and Papa, A., 2021. Exploring the impact of big data analytics capabilities on business model innovation: The mediating role of entrepreneurial orientation.


  1. Hallikainen, H., Savimäki, E. and Laukkanen, T., 2020. Fostering B2B sales with customer big data analytics.


What Are The Most Popular Programming Languages 2024?

Do you want to learn a new skill that can boost your career prospects and solve real-world problems?

If yes, then you might want to consider learning a programming language. Programming languages are the tools that allow us to communicate with computers for developing software applications. They can be used for various purposes, such as web development, data analysis, artificial intelligence, gaming, and more.

But with so many programming languages out there, how do you choose which one to learn? Which programming language is best for getting jobs this 2024? Which programming language is going to remain popular in the future?

In this article, we aim to answer all these questions and more. Stick around.

What Is ‘Programming Language’ In Simple Words?

A programming language is a set of rules and symbols that tells a computer what to do. It allows us to write instructions for the computer in a way that is easier for us to understand and modify. Thus it defines how the computer should execute those instructions and handle errors.

For example, if we want to make a calculator app, we can use a programming language to tell the computer how to perform calculations, display the results, and handle invalid inputs.

Now let’s learn about the varied types of programming languages and what they offer.

Types of Programming Languages

Based on various criteria, such as syntax, features, paradigms, or applications, programming languages fall under various categories and classifications. However, there is no definitive or universal classification, and some languages may belong to more than one type.

Here are some common types of computer languages with examples.

  1. Procedural languages: These languages follow a step-by-step approach to solve a problem, using variables, functions, loops, and conditional statements. They are easy to learn and implement, but they can become complex and hard to maintain for large programs.
    Some examples of procedural languages are C and Pascal.
  1. Object-oriented languages: These languages use objects as the main building blocks of a program, where each object has its own data and behavior. Here objects interact with each other through messages, and inherit properties from other objects. This makes the code more modular, reusable, and extensible.
    For example: Java, Python, C++, and Ruby.
  1. Functional languages: These languages focus on the output of functions rather than the state of variables. Functions are taken as first-class values. This means that they can be stored in data structures, considered arguments and returned as results. Functional languages avoid side effects and mutable data, which make them more expressive, concise, and reliable.
    Some examples of functional languages are Haskell, Scala, Erlang, and F#.
  1. Scripting languages: These languages are designed to automate tasks, manipulate data, or enhance the functionality of other applications. They are usually interpreted rather than compiled, which makes them more flexible and portable, but also slower and less efficient.
    For example: JavaScript, PHP, Perl, and Python.
  1. Markup languages: These languages are used to define the structure, presentation, or content of documents, such as web pages, e-books, or data formats. They use tags or symbols to annotate the text, which can then be processed by browsers, parsers, or other applications.
    Some examples are HTML, XML, CSS, and TeX.
  1. Query languages: These languages are used to retrieve, manipulate, or analyze data from databases, data warehouses, or other sources. They use commands, expressions, or clauses to specify the criteria, conditions, or operations on the data.
    Some common query languages are SQL, SPARQL, XQuery, and Datalog.
  1. Domain-specific languages: These languages are tailored for a specific domain, problem, or application, such as Mathematics, Statistics, Engineering, gaming, or music. They have a limited scope and vocabulary, but they are more expressive, concise, and efficient for their intended purpose.
    For example: Matlab, R, Logo, and Swift.
  1. Multi-paradigm languages: These languages support more than one programming paradigm, such as imperative, declarative, functional, or object-oriented. They offer more flexibility and choice for the programmers, but they also require more skill and discipline to use them effectively.
    Some examples of multi-paradigm languages are Python, Scala, and Kotlin.

Now as we step into 2024, the demand for specific programming languages continues to shift. You certainly have experience on programming, but are you ready for the future? Let’s explain.

Top 10 Programming Languages That The Industry Wants In 2024

python language
In this ever-evolving landscape of data science and technology, staying agile and ahead on the latest programming languages is crucial for any aspiring or seasoned developer.

Here let’s explore the top 10 programming languages to learn this year, each playing a unique role in shaping the digital world.

  1. Python

Renowned for its simplicity and versatility, Python maintains its top spot. Widely used in web development, Artificial Intelligence (AI), data science, and automation, Python’s readability and extensive libraries make it a go-to language for both beginners and seasoned developers.

  1. JavaScript

Being the backbone of web development, JavaScript is indispensable. With it one holds the ability to develop dynamic web pages that are interactive too. This is what makes JavaScript a must-learn programming language. With frameworks like React and Vue.js dominating the scene, mastering JavaScript opens doors to powerful front-end development.

  1. Java

Java has stood the test of time and continues to be a force to reckon with. It powers Android app development and is a key player in enterprise-level applications. Learning Java provides a solid foundation for building robust, scalable, and cross-platform applications.

Apart from these top 3 types of programming languages, consider the underlying options to bolster your career for the future.

  1. C and C++

These stalwarts remain fundamental, especially in system programming and game development. C and C++ form the backbone of many high-performance applications, making them essential languages for those delving into low-level programming.

  1. Swift

For iOS app development, Swift is the language of choice. Its concise syntax and emphasis on safety make it one of the favorites among developers creating applications for Apple’s ecosystem. As the demand for iOS apps continues to rise, Swift maintains its relevance.

  1. Kotlin

Kotlin offers modern features and seamless inter-operability with Java and is an officially supported language for Android development. Developers looking to create Android apps efficiently are increasingly turning to Kotlin for its conciseness and expressiveness.

  1. PHP

Despite being around for decades, PHP remains vital for server-side web development. Powering popular content management systems like WordPress, PHP is a valuable addition for those focusing on web backend development.

  1. Matlab

Matlab is an essential language in scientific computing, engineering, and data analysis. Widely used in academia and industry, mastering Matlab is advantageous for professionals working in research and development.

  1. SQL

Structured Query Language (SQL) is indispensable for managing and manipulating databases. As data continues to be a driving force in technology, understanding SQL is crucial for anyone working with databases and data-driven applications.

  1. HTML

Is HTML a programming language? While not a programming language per se, HTML is the backbone of web development. Understanding HTML is a fundamental skill for anyone venturing into web design and development, as it forms the basis for creating web pages.

Staying relevant in the ever-changing tech landscape requires a strategic approach to learning programming languages. Whether you are a beginner or a seasoned developer, mastering these top 10 languages in 2024 will undoubtedly position you for success in the dynamic world of programming.

How Is Programming Shaping The Industry?

In the rapidly advancing landscape of technology, programming languages play a pivotal role in shaping various industry and job domains. As we look forward to 2024, understanding the synergy between programming skills and specific occupational sectors becomes imperative.

Let’s explore how proficiency in programming languages can significantly impact and elevate the following domains.

Navigating the Tech-Driven Professions

  1. Web Development

Languages such as Python, JavaScript, and HTML are indispensable in the realm of web development. As businesses aim to sustain, compete and enhance their online presence, web developers proficient in these languages are in high demand. Frameworks like Django (Python) and React (JavaScript) further amplify the significance of programming skills in this domain.

  1. Data Science

Python, with its robust libraries like Pandas and NumPy, is a powerhouse in the field of data science. As organizations leverage data to make informed decisions, professionals proficient in programming languages for data manipulation and analysis find themselves at the forefront of this burgeoning industry.

  1. Artificial Intelligence and Machine Learning

Python’s dominance extends to Artificial Intelligence (AI) and Machine Learning (ML) applications. TensorFlow and PyTorch, both Python-based, are widely employed in building and training sophisticated AI models. Mastery of programming languages in this domain opens doors to creating innovative solutions and contributing to the AI revolution.

  1. Mobile App Development

Swift and Kotlin emerge as key players in mobile app development, particularly for iOS and Android platforms, respectively. With the demand of mobile applications continually surging, programmers skilled in these languages are well-positioned to thrive in the dynamic and competitive app development industry.

  1. Cybersecurity

Programming languages like Python and Java are instrumental in cybersecurity efforts. Writing secure code, developing robust applications, and implementing effective security measures all rely on a solid understanding of programming. Professionals well-versed in these languages contribute to safeguarding digital assets and mitigating cyber threats.

  1. Cloud Computing

Languages like Java, Python, and JavaScript are integral in the field of cloud computing. Whether it’s building scalable applications or managing cloud resources, programming skills are a prerequisite for cloud engineers and architects. Proficiency in these languages is vital for optimizing cloud infrastructure and services.

  1. DevOps

In the world of DevOps, scripting languages such as Python and Shell are essential for automation and continuous integration/continuous deployment (CI/CD) processes. Professionals in DevOps roles leverage programming skills to streamline workflows, enhance efficiency, and achieve seamless collaboration between development and operations teams.

  1. Blockchain Development

Languages like Solidity (for Ethereum) and C++ find applications in blockchain development. As blockchain technology gains traction across various industries, programmers proficient in these languages are instrumental in designing and implementing decentralized solutions and smart contracts.

Now that programming languages are influencing a range of job domains, they’re forging a symbiotic relationship between technology and your chosen profession. Whether you’re aiming to be a web developer, data scientist, AI engineer, or exploring emerging fields like blockchain, mastering relevant programming languages is your pathway to success in the tech-driven workforce of 2024.

Which Programming Language Is Best For Your Career This 2024?

programmer writing a code
Programming languages are the tools that enable developers to create software, applications, websites, and more. However, not all programming languages are equally popular or in-demand in the job market. Some languages have more opportunities, higher salaries, and better prospects than others.

Therefore, it is important for aspiring programmers to choose the right language to learn and master.

5 Best Programming Languages – Get Yourself Job-Ready!

The following are some of the best programming language examples to keep an eye on and learn this 2024 for acquiring that competitive edge.

  1. Python

Python stands out as a versatile, easily graspable, and extensively applied language, well-suited for diverse domains including web development, data science, machine learning, artificial intelligence, and beyond. With a sizable and dynamic community, Python boasts an extensive collection of libraries and frameworks, contributing to its heightened demand across industries. In the United States, Python developers can anticipate an average salary reaching $115,000.

  1. JavaScript

As discussed in the earlier sections, JavaScript remains as one of the most popular computer languages for web development. This is because it enables dynamic and interactive features on web pages. JavaScript is also used for backend development, mobile development, desktop development, and more, thanks to its powerful frameworks and libraries such as React, Angular, Node.js, and Electron. In the United States, the average salary for JavaScript developers is around $110,000.

  1. Java

This stands out as a mature, reliable, and high-performance programming language extensively employed in diverse fields such as enterprise applications, web development, and mobile development. Recognized for its portability, scalability, security, and concurrency features, Java boasts a substantial and committed community, an extensive array of tools and frameworks, and significant industry demand. In the United States, Java developers can anticipate an average salary reaching $105,000.

  1. Go

Crafted by Google, Go emerges as a contemporary language tailored to tackle the complexities of modern software development. Characterized by speed, simplicity, and concurrency, Go is well-suited for constructing scalable and dependable systems, particularly in the realms of cloud computing, micro-services, and distributed systems. Bolstered by an expanding and passionate community, Go features a minimalist and expressive syntax, contributing to its heightened demand within the industry.

  1. TypeScript

TypeScript, an extension of JavaScript, introduces static typing and additional features to elevate the dependability, readability, and maintainability of JavaScript code. Compatible with JavaScript, TypeScript seamlessly integrates with any JavaScript framework or library. Its rising popularity among web developers is attributed to its ability to identify errors during compile time, enhance code quality, and provide robust support for large-scale projects. In the United States, TypeScript developers can anticipate an average salary of $120,000.

These are some of the best programming languages to learn in 2024 for getting jobs, based on their popularity, demand, salary, and future prospects. However, there are many other languages that are also worth learning, such as Kotlin, Swift, Rust, C#, and R.

Ultimately, the programming language that you wish to learn depends on your personal goals, interests, and preferences. The most important thing is to keep learning and improving your skills, as programming languages are constantly evolving and changing.

Other Career Options to Consider

Starting your coding journey requires you to put thoughtful consideration on whether your career goals remain aligned with some of the best programming languages in the world. Your choice should reflect your career interests and the specific realm of software development you aspire to enter.

As you venture into coding, consider the following programming languages tailored to various career paths.

Let’s distill the aforementioned options into a concise overview:

  • Front-end Web Development

Explore JavaScript and TypeScript for creating dynamic and interactive user interfaces.

  • Back-end Web Development

Delve into the versatility of JavaScript, TypeScript, Python, Go, Elixir, and C# to master server-side development.

  • Mobile App Development

Choose Swift for iOS, Java for Android, or C# for cross-platform app development to craft innovative mobile applications.

  • Game Development

Focus on C# to enter the realm of game development, leveraging its capabilities for creating engaging and immersive experiences.

  • Desktop Applications

Master Java, Python, JavaScript, or TypeScript based on your preferences, as each excels in developing desktop applications for diverse purposes.

  • Systems Programming

Explore the intricacies of C, Rust, and Go to delve into low-level programming, shaping the core functionality of various systems.

Ultimately, the best programming language for you is the one that aligns with your career aspirations and the type of software development that ignites your passion. Choose wisely and embark on a journey of skill acquisition that resonates with your professional goals.

What Are The Future Programming Languages For 2025?

As we approach 2025, the ever-evolving landscape of technology hints at the emergence of new programming languages poised to shape the future of software development.

Let’s delve into the potential programming languages that are anticipated to gain prominence in 2025:

Exploring the Next Wave of Innovation

  1. Rust

The language is gaining fast popularity nowadays for its uptight focus on performance, memory safety, and zero-cost abstractions. Rust is thereby positioned to become a key player in systems programming. With its emphasis on preventing common programming errors, Rust is expected to attract developers seeking both efficiency and robust security features.

  1. Julia

Julia has gained recognition for its prowess in scientific computing and data analysis. With high-performance computing being in demand in the industry, Julia’s speed and ease of use make it a strong contender for applications in fields such as finance, engineering, and research.

  1. TypeScript

Building on the foundation of JavaScript, TypeScript introduces static typing to enhance code quality and developer productivity. Its growing adoption in web development, particularly with popular frameworks like Angular, positions TypeScript as a language to watch in the evolving ecosystem of front-end development.

  1. Haskell

Haskell, a functional programming language, is gaining traction for its strong type system and concise syntax. With an emphasis on mathematical reasoning and purity in functions, Haskell is anticipated to attract developers looking to build robust and maintainable codebases.

  1. Elm

This functional programming language is specifically designed for front-end web development. Focused on simplicity and reliability, Elm is gaining attention as a language that enables developers to build scalable and maintainable user interfaces, addressing challenges commonly faced in large-scale web applications.

  1. Kotlin

While Kotlin is already established, its versatility and interoperability with Java make it a language with a promising future. With continued support from major frameworks and its adoption for Android app development, Kotlin is likely to maintain and expand its influence in the software development landscape.

  1. Crystal

Crystal combines the elegance of Ruby with the performance of languages like C. Its focus on developer-friendly syntax and high-performance execution makes it an intriguing option, particularly for building fast and reliable applications.

  1. Elixir

Elixir, built on the Erlang virtual machine, is gaining popularity for its scalability and fault-tolerance. As the demand for concurrent and distributed systems rises, Elixir’s unique features position it as a language to watch in the development of robust and resilient applications.

  1. Dart

Dart, backed by Google, is the programming language powering Flutter, a framework for building cross-platform mobile applications. As Flutter gains momentum, it is expected that Dart will play a significant role in the mobile app development landscape.

  1. Racket

Racket, a descendant of Scheme and Lisp, is gaining attention for its extensibility and focus on language-oriented programming. With its unique approach to language design, Racket is anticipated to attract developers exploring unconventional and expressive programming paradigms.

The future of programming languages for 2025 promises a diverse and dynamic landscape. Developers looking to stay at the forefront of innovation should keep an eye on these languages, each offering unique strengths and capabilities to address the evolving needs of the software development industry.


How do you choose the best programming language to learn in 2024? This blog helps you answer this question by introducing the concept of programming languages, explaining their different types and giving some examples of each.

Here we have also enlisted some of the most popular programming languages to learn in 2024, such as JavaScript, HTML/CSS, Python, C, C++, and Swift, and described their features and advantages. Finally this article aims to help you pick the right programming language for your goals and interests.

Get encouraged and learn new programming skills this 2024 to boost your career prospects and solve some real-world problems!


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  2. Wassberg, J., 2020. Computer Programming for Absolute Beginners: Learn essential computer science concepts and coding techniques to kick-start your programming career. Packt Publishing Ltd.
  3. Srinath, K.R., 2017. Python–the fastest growing programming language. International Research Journal of Engineering and Technology4(12), pp.354-357.
  4. Wexelblat, R.L. ed., 2014. History of programming languages. Academic Press.
  5. Sebesta, R.W., 2012. Concepts of programming languages. Pearson Education, Inc.

Technology Innovation for the Bottom of the Pyramid

Perhaps Mr. Franklin D. Roosevelt, the U.S President himself, would not have imagined while coining the term “Bottom of the pyramid”, that the poorest yet largest socio-economic segment would be one of the most lucrative segment for entrepreneurial innovation. The modern strategic mastermind, Dr. C.K Prahalad, however, in his book titled “The Fortune at the Bottom of the Pyramid” foresaw this driver of change and growth.

It has been 84 years now since the term first came into being, and as technology rapidly earned its place as the 4th factor of production by modern definition of economics, technopreneurs are creating massive value catering to the “Bottom of the pyramid”. By serving the underserved, they are the real winds of change.

Today, approximately, there are a whopping 3 billion people living on less than $2.5 a day globally. As a major pie from this statistic, India, being an agriculture driven economy, constitutes about 70% of the population living by such a metric. Thus, even though such a segment would largely depict a fairly low purchasing power & limited intellectual capital, they would, infact, also represent the largest demographic market segment by per capita income.

But why should an entrepreneur target the bottom of the pyramid? What are the underlying opportunities?

Digital innovation is transforming lives by impacting and enabling human functions, and human emotions. While most of the urban agglomerations are ideal to market testing, the semi-rural and rural markets are not invested upon, hence not impacted enough. There is substantial need and evidently more buyers than sellers, only if the right tools reach the right hands. Out of a billion mobile phone users, only 250 million are smartphone users. Out of which again, only a mere 30% have access to 3G networks, the rest, 2G.

Though counterintuitive, low purchasing power means high business opportunity. The  massive chunk of human capital in our target segment can be engaged in semi-skilled opportunities, which in turn can provide traction in areas of logistics and outsourcing for high growth and well funded startups.

Venture capitalists are investing heavily in technology startups while large corporations are launching startup accelerators in emerging economies. The objective? Reach & Market expansion. And when the thought leaders foresee holistic growth, bottom of the pyramid provides a bouquet of opportunities in terms of scale.

With opportunities galore, let’s think about some of the key growth drivers in today’s world of rapid disruption in this segment:

  • With growing secondary & tertiary occupations in semi-rural & rural areas, the dependence on farming is witnessing a decline, thus ensuring steady income which bears a positive effect on disposable income.
  • Better infrastructure, increased investment, good monsoons, farm-loan waivers and improved income levels are increasing spending propensity.
  • Government initiatives like PMRDF, PMKVY, Jandhan Scheme, transactions using UIDAI & Swachh Bharat campaigns are drivers to economic upliftment in areas which need the most.
  • There has never been a greater impetus from NGOs, CSR programs of large corporations & self-help groups which are working towards alleviating deep-rooted socio-economic issues in this segment.
  • Public infrastructure projects like enhanced road connectivity is improving employment quotient due to improved commutation.
  • Technology adoption intermediaries are the agents of change who serve as a bridge between the bigger picture and implementation at the grassroots.
  • The Digital India program initiative by the Government of India which is striving to making every citizen have access to information at their fingertips.

Are there role models from the large firms who follow a rather traditional innovation approach? Precisely, yes, and very effective:

Organization Segment Innovation Why innovative?
Godrej & Boyce  Consumer durables  ChotuKool refrigerator  Battery powered, does not require regular electricity supply
 Vortex  Banking  Low cost ATM  Very less power consumption, reliable cash dispense module
 TATA Chemicals  Consumer goods  Water purifier  No running water or electricity, low cost of access Rs. 899
 HUL  FMCG  Khushiyon ki Doli  Affordable multi-brand home care & hygiene products
 Nokia  Software  Nokia Life Tools  Windows OS non-smartphone utility suite
 ITC  Agriculture  Choupal  Empowers farmers with up-to-date agricultural and marketing information through access to internet and computers.
 GlaxoSmithkline  FMCG  Asha (milk food drink)  40% cheaper than the regular variant of Horlicks, affordable health drink
 IFFCOTOKIO  Financial Services  Microcredit  Loans to individuals and SME proprietors without CIBIL
 Uber  On demand cabs  Self-employment  On-demand cab service to urban customers, semi-skilled rural workers migrating to cities, better livelihood
Big basket, Swiggy Hyperlocal delivery Logistics On-demand home grocery semi-skilled rural workers migrating to cities, better livelihood
Facebook, Ola Digital 2G services Enabling customers to book cab services using 2G networks, Facebook Lite version for 2G networks


While large corporations are setting new standards to innovation by constantly striving to maximize reach, several new kid-on-the-blocks (read startups) are also embracing innovation in their own capacities, thus, setting examples for others to follow and create social value, beyond mere business figures. Some of the notable ones deserve a mention below:

  • Selco solar – Provide sustainable energy solutions
  • Nanopix – Have developed proprietary lot sorting algorithms for farm produce
  • iKure Techsoft – Enable selling accredited medicines, tracking doctors, attendance, prescriptions
  • Ampere – Provide affordable electric vehicles, e.g, scooters, cycles, trolleys
  • Boond – Aid in alleviating social issues
  • Paani –Enable mobile commerce even for non-smartphone users through mobile-based loyalty programs for underserved communities
  • Bempu – Infant warming solutions using a wristband
  • Samasource – Creates employment by outsourcing (BPO/KPO), customer support skills that can be easily trained and delivered.
  • Digital Empowerment Foundation – Provides rural areas with digital literacy, access to digital tools and information-rich knowledge.


Now, how well does Zivanta Analytics fit into the social innovation bandwagon? Are we doing our bit as a corporate citizen? In the last couple of years of our existence, we have catered to several niche social sectors as consultative partners of large corporations and NGOs alike, empowering them with cutting edge technology services & analytics. With the help of our social consulting verticals that we work in, our clients are able to make sense of large unstructured data sets, unregulated information systems, unevaluated social program investments emanating from the bottom of the pyramid.

Some of our major clients are ACC-Holcim, Save the Children, Voltas, Ernst & Young, Ministry of Small & Medium Enterprises, Govt. of India. Projects delivered range from reporting, surveys, fieldwork, MIS, dashboards, web development, implementation interventions, content & documentation, metrics measurement, bid & procurement management, etc.

Riding the wave of social change using technology and digital innovation, Zivanta Analytics, with its yearn and drive to create an impact through value at the bottom of the pyramid, believes the day is not far where empowerment will weigh heavier on the scale against disparity & lack of exposure. That is the day when communities will unite, for the greater good, irrespective of the pyramid.


My Internship Experience with Zivanta Analytics

One balmy morning, I stood in front of the Zivanta Analytics office. With one year of the MBA course behind me, I was at Zivanta Analytics for my internship interview.  Professors had cautioned that this was the real thing, much removed from the presentations at the business school in familiar surroundings.  I was forewarned that at the internship interview I was to be quizzed by battle-hardened professionals who over the years have honed their skills on separating the wheat from the chaff.  In business school professors help you to add value to yourself, but as an intern I was to position myself on how I was to add value to the company and in the bargain learn something in the real world situation.

For comfort I had this brilliant piece of advice which does rounds at my business school during the internship and placement seasons “do not feel bad when interviewer rejects u, people usually reject expensive things because they cannot afford them”. With these lines in my head,  written by one of the greatest (albeit anonymous) philosopher of all times, it gave me  a momentary sense of false confidence, As I entered the Zivanta Analytics office,  I felt like David, out to slay the Goliath.

At the interview table I was certainly the David, but where were the Goliaths. The two-member team who interviewed me did not appear at all intimidating. They asked the usual questions- about academics, my future plans and about me as a person. What impressed me was that the interviewers at Zivanta Analytics went at length to explain the pick of projects which I could choose from if I were to be selected, and how such experience will help in my career in the long run. The entire process was interviewee centric and was about my benefits and gains.

The mail next day followed with a telephone call informed me of my selection. It felt good to have cracked the interview. I looked forward to attending office; the interviewers had certainly left a very positive impression on my mind.

First day I was introduced to my mentor for the internship period at Zivanta Analytics.  My mentor,  who has a string of impressive degrees including those from abroad and a formidable work experience, spoke to me as a colleague and not as a supervisor of a boot camp.  My colleagues in the business analytics team at Zivanta Analytics were a cheerful lot, always helpful and very humane.

The sense of humour even during the toughest of delivery schedule was impressive. When tight deadline would come up, the refrain from the supervisor would be “guys let’s get into the pressure cooker and blow the client up”.

My first assignment was to assist the team lead in one of the projects which involved developing an algorithm to rank credit cards. That was my first hands-on experience in data analytics, which I could never have learned from only studying books. I eventually got involved in many subsequent projects for Zivanta Analytics. Even though I was an intern, my opinions and suggestions were always taken. I was always included in crucial business meetings and my supervisors encouraged me to come up with new ideas.

The responsibility and flexibility during my internship days in Zivanta Analytics helped me find my bearings and helped transition from business school to work life seamlessly.

In a nutshell, I was the David who never had to slay a Goliath, for there are no Goliaths at Zivanta Analytics.

Today I work as a full-time staff at Zivanta Analytics and the learning curve for me remains steep as ever.

How Data Digitization Can Help Real Estate Hedge Fund Managers

Since its invention back in the 1990s, digitization has diffused its way into every conceivable sector of commerce; specially the service industry. In financial services the rise of digital technologies has dramatically changed the manner in which institutions deliver information to their clients. Zivanta Analytics has helped in data digitization of a leading real estate hedge fund company which has brought more efficiency in their work there by shortening the TAT for their bidding for each deal.

The company’s primary objective is to deploy capital for pools of real estate assets that contain a title, document or compliance issue which impacts the marketability of that asset to the current owner. It utilized an asset based due diligence review which encompassed the legal curative strategy, property value and cash flow analysis data points needed to secure the assets with an appropriate equity position to protect a potential investment risk.

The objective of the company is to acquire real estate pool which came with thousands of scanned collateral documents which told the story about the constituent properties, its lien and title status, default details, assignments and other key variables which determine the risk profile of the property. For taking a price position for bidding for a Deal, the risk profile needs to be determined.

To create the risk profile of these properties, the relevant data had to be culled out from the collateral documents for each property. Zivanta Analytics had been retained by the Hedge fund company to sift through thousands of collateral documents and the key indicators. Zivanta Analytics has also built an analytics engine which uses the key data to build the risk contours of each individual property in a deal.

The company selected a specific deal and had transferred the entire collateral set to Zivanta Analytics in pdf format. Analysts at Zivanta analytics who are trained to look into the real estate collaterals, sorted the documents and looked at the completeness for building the collateral datasets. Accordingly the digitization strategy for a given deal was decided.  The collaterals which could be machine read were sent to the technical data scraping team who wrote codes to digitise. The remaining collaterals which were not machine readable were sent to the data associates who keyed in the data for each property from each collateral using either voice or key board based data entry method. As the data were entered, the data quality team concurrently checked the  data for quality using proprietary checking  tools and analytics.

The cleansed data was then processed by the Zivanta proprietary analytics engine to create a risk profile for each property.  The data could be queried by the hedge fund company experts through a custom interface developed by Zivanta Analytics. A dashboard to help analyze the risk profile was also developed.

With the help of this newly developed process the hedge fund company got quality data on tight deadlines at very economic costs. The risk profile created using the data from the collateral documents helped make an informed decision regarding the bid price for acquiring a deal. Once a Deal is acquired, the  experts  at the company are now using the data set to identify and mitigate the risk associated with each individual property  thereby making the property marketable at prevailing  market rates.

How Big Data Is Helping The Banking Industry

The 80s and the 90s made a revolution in the banking industry when IT systems virtually revamped the whole banking process. The use of the internet  made it a lot easier to assess and evaluate the progress of a bank beforehand. It even had enhanced the service provided by the banks.

Banks always have a lot of information regarding their clients. With this information they can learn newer ways to provide better services. With the insights they have, they can make sure their customers are always provided with resources that are beneficial and not available elsewhere. The use of Big data has now opened up a new way for banks to be more profitable. The very use of Big data is enabling the banking sector answer a simple question in seconds which is not possible without harnessing the power of Big Data.

Big Data is an extensive system that can help banking industries simplify their system and work better. It helps them in developing a sincere clientele. Following is a list of ways in which the banking industry is affected by the use of Big Data:

Customer Segregation:

When a bank is provided with the insight to track and trace the habits of their clients of where and how they spend their money, it becomes easier for them to understand the clients’ needs. Once the results are analysed, clients can be categorized into different segments. This will suggest their banking needs and the marketing campaigns can be drawn up accordingly. This will also promote a healthier customer relationship.

Cross Sell Opportunity Enhancement:

With the use of Big Data, the banking industry can improve their relationships with their clients and understand them better. Big Data provides a more personal assistance and helps banks with detailed information on their clients. This information helps banks come up with schemes that are direct and personalized. These schemes gain maximum attention and are able to make sure they can come up with similar plans for the future. As their ability to analyze and assess the situation increases, their ability to deliver according to the expectations of their clients increases as well.

Efficiency Improvement:

Big Data helps banks avoid all situations that can be embarrassing for them. When a client asks a question that can only be answered by assessing the database, Big Data comes handy. The clients no longer have to wait to be answered because of a system failure. Their queries are solved immediately. By entering the name of the customer, banks are provided with all his important details. This also increases the level of satisfaction received from the customers. It also develops a sincere number of clients that learn to rely on their banks more.

 Fraud Detection:

Internet no doubt has made life simpler; however, it has also made fraud easy. When banks come up with newer ways to stop fraud, people come up with newer ways to commit it. This makes it impossible for banks to be able to trace the fraudulent convicts. The use of Big Data rids them of this problem. It makes it easy for banks to immediately be able to trace a fraud and put an end to it. The installation and use of this system makes it easy for banks to identify where the fraud is being committed. They can stop it immediately without delaying or experiencing a loss.

Risk Management:

With help of Big Data information is easily located on a single large scale platform and it becomes easier to reduce the number of risks. Everything that is needed by the banks becomes available at a central platform. This reduces the chances of them losing any information. It also helps them avoid being ignorant towards a fraud. They can easily detect them and in turn reduce all kinds of risks.

So in a nut shell Big Data is very beneficial. If it is taken up by industries it can be utilized with the right kind of knowledge. It assists the banks in taking steps and coming up with initiatives that provide guaranteed benefit. Big Data not only helps banks attract a larger client base but also helps them markedly reduce all frauds and secure their system.

Digital Marketing as a tool for Brand Building

A brand is all about what people say about you when you are not in the room. The million dollar question here is “Can we in any way influence and shape the conversation that takes place in our absence?”

Michael William Krzyzewski is an American basketball player and coach at Duke University. He is regarded as America’s most successful basketball coach of all times. He interestingly was able to link his stakeholders comprising of recruiters, players, and fans to the brand promise. Michael William was able to deliver on his promise of a path to a career in basketball and even winning championships with the help of his website and adhering to techniques of digital marketing.

In today’s technology driven era, digital channels provide a positive environment to building a brand. One of the very basic activity associated with digital marketing is helping to ‘bring a brand to life’. As dependency on technology is increasing globally, digital marketing tools are gaining immense popularity as a fantastic tool for brand building. A basketball, baseball or rugby coach in order to have a solid brand has to first focus on enhancing customer experience through the help of digital marketing.

The advantages of utilizing digital marketing as a tool for brand building are:

  • Get targeted results:
    Online marketing can help in focusing on the important issues like zeroing on the right market and right consumer. A dedicated approach aimed at the targeted consumer can help make things easy. A regular update on social media, web content, SEO can be profitably used to reach out to specific demographics and particular geographic regions.
  • Increase of digital footprint:
    The use of technology has greatly increased over the past few decades. People are accessing more content digitally using their laptops, mobile phones, tablets etc. A brand can be easily brought to live by using the proper content, user experience and engaging with the audience through social media to name a few.
  • Delivering on promise and purpose:
    For a coach, the target audience should feel connected to the common dream of winning championships, a path to an NBA career and riches to name a few. They should be able to relate that a brand connection is the doorway to their individual’s goals of landing with top colleges, top recruiters, or becoming a great player. Proper digital branding can create an environment that will help bridge the gap.
  • Enhancing Brand Loyalty:
    Digital marketing helps in building brand loyalty. It makes stakeholders aware of the reason behind accepting and sticking to the brand. In order to build brand loyalty reaching out to the hearts, minds and lives of the stakeholders is necessary. Creating more exciting ways to engage with target audience should be a priority.

Digital brand building is a tool that helps garner faith right from the first visit to the website, to email newsletter to the Facebook or LinkedIn page. A brand is far more important than just a logo or an image. It is something which creates an imprint in the mind of customers.

How Digital Marketing can help your business grow

Digital marketing has become an essential part in today’s world. With both competitors and potential customers constantly online, digital marketing is the only way to proceed ahead. When you’re a small business owner the online world can seem intimidating. Here is a list of five simple digital marketing strategies that any business owner can implement to help their business grow.

1.Setting a Goal:You’re looking for ways to help your small business grow. You might want more customers, more recognition or maybe you’re looking to get ahead of the competition. Whatever the case may be, starting with a solid goal in mind greatly increases your chances of success. Digital marketing is a great way for small businesses to prosper, but going into the process blindly can leave you with a jumbled mess. A lot of strategy and precision goes into digital marketing and having a goal helps you know what to focus on.

2.Creating a Marketing Funnel:The most successful businesses have an effective marketing funnel in place. A marketing funnel is when you map out a customer’s journey from when a customer is a complete stranger to when they become a lead, and then put certain strategies in place that will encourage them to move through this funnel. Things like lead magnets, calls to action, opt-ins and offers are all effective pieces of a funnel.

Having an effective marketing funnel won’t just get you more leads, it can also help you turn leads into repeat buyers. If the customer has a good experience they might return to purchase from you again or even tell others they know about your business. The elements of a marketing funnel can seem like a lot to put together, but they’re simple concepts when broken down. You’ll see that numbers 3,4 and 5 help to break down and explain the different aspects of having a marketing funnel in place on your site and how to put together some of the most important pieces of it.

3.Developing a call-to-action:We talked about using a call-to-action in the second step as a part of your marketing funnel, but what is a call-to-action exactly? A call-to-action (CTA) is an image or text that prompts visitors to take action, such as subscribe to a newsletter, view a webinar or request a product demo. CTAs should direct people to landing pages, where you can collect visitors’ contact information in exchange for a valuable marketing offer. In that sense, an effective CTA results in more leads and conversions for your website. This path, from a click on a CTA to a landing page, illustrates the much desired process of lead generation. In order to increase visitor-to-lead conversion opportunities, you need to create a lot of calls-to-action, distribute them across your web presence and optimize them. A good CTA should be attention grabbing and help lead a potential customer further into your marketing funnel.

4.Creating an Effective Lead Magnet:A lead magnet can be used alone or along with a CTA. This will also be used either within your marketing funnel or as a way to drive potential customers into your funnel. Supply them with something relevant to your product or service that they want. Use your offers as a way to gather more information about a potential buyer while driving them further into your funnel at the same time. This brings them closer to becoming an actual quality lead who will spend money on your product or service. The idea behind a lead magnet is to trade information. You supply something like a free download of a white paper, but in order to complete the download the individual has to fill out a form that will provide you with more information about them. You’ll use the information you gather to interact with them more as they progress through your funnel.

5.Driving Traffic:In order for there to be people to drive into your marketing funnel, there first has to be traffic on your website. There a variety of ways you can drive traffic to your website. Here are a few of the recommendations:

  • Quality Content: Use content such as blog posts, press releases and articles on authority websites. Insert links to various places on your website within this content to build your brand name through exposure and drive traffic to your website.
  • Keyword Strategy: Inserting related keywords into content will help your content and website show up in more search results, this leads to higher volumes of web traffic.
  • Website Optimization: Ensuring that your website is optimized and functioning at it’s best is essential. People don’t want to visit a website that doesn’t work properly.
  • Social Media: Use engaging social media posts to attract more traffic to your site. Using pictures, video, and other relevant media will help your posts get more engagement.

How Credit Card Can Help When You Are Jobless

A new study from the National Bureau of Economic Research have  examined how credit access affects the way Americans look for new jobs. It turns out that credit can often help job seekers in a marked way especially those with lower income and fewer savings.

The study found that when workers lose their jobs, a higher limit on their existing card allows them to take longer to find a new one. The study linked up an employment database with millions of Trans Union credit reports from 2001 to 2008. It showed that a credit limit increase equal to 10 percent of a person’s prior annual salary can translate into their spending as many as three weeks more looking for a job.This situation is ideal for people who do not have any debt burden on their shoulder. Moreover you have to use your credit card sensibly in such situations.

Longer unemployment might sound like a serious situation as people are anxious about their finances and future. But it’s also a mistake to jump at the first job opportunity that comes your way because you’re desperate for money. It is observed that when unemployed people have access to more credit they become choosier regarding jobs. Most often they end up with better jobs a year later, both higher-paying and at larger, more productive companies.

The study found that it’s not really credit-card spending that makes people to be pickier. It’s the fact that they knew that cash was available if they needed it, which gives them confidence to hold out longer for better opportunities.

For the unemployed a credit card with a generous limit can work much as unemployment insurance or emergency savings. These extra resources give them the ability to apply for jobs, network, get retrained, or even move to cities with more promising job markets.

The problem, however, with relying on credit-card debt after a job loss is that banks are notorious for cutting off credit just when customers need it most. In 2009, the average credit-card limit dipped about 40 percent. So when lots of people lose their jobs, that credit-card cushion can vanish.

In other words, job seekers and government policymakers have similar, difficult choices to make during a recovery: If people rush out to find any old job as quickly as possible, they can hurt their finances and productivity in the long run. But if they have the opportunity to wait for the right job to come along their way it can surely help them avail the right job at the right time.

Sports Coaching – in the Digital Era

Change is the law of life. The rapid rise in digital advancement and communication platforms along with the increase in human interactions has changed the face of sports coaching.New coaching needs are coming up as the requirements of the athletes are changing. Today the role of a coach is many and varied. It encompasses the job of an instructor, assessor, facilitator, advisor, supporter, organizer, motivator, and counselor all rolled into one. Coaching today is all about improving the overall experience and to connect digitally with the stakeholders.

The big question is how a website can help increase the digital visibility of a sports coach. Digital marketing helps promote a website and makes it visible during online searches. Digital Marketing comprises of techniques like blogging, social media promotion, search engine optimization, content marketing, and video marketing. Being seeing online is now an important aspect for engaging with supporters and customers irrespective of the sports a person is pursuing. With the advent of new technologies, it has become tough to advertise without an effective online presence.

The importance of a Website to build Brand Image:

  • A coach can customize his website according to his needs in order to promote the services provided by him online. It is also convenient to add a photo, a photo gallery – an assortment of photographs, testimonials from customers and even a YouTube video.
  • A website will help in getting online bookings as timings of sessions and other itineraries can be easily published online.
  • A website provides a single platform to communicate, manage and store information about client’s database.
  • A calendar marked with all the session details and schedules can be made available easily. There is also an option of sending notifications and timely reminders to clients.
  • A website also allows easy tracking of players, their attendance, payment status, coaching hour completed via a simple dashboard.
  • Real-time chats with clients and assistance can be made available to players, guardians all stakeholders.

Technology plays an important role in helping people to stay connected and communicate easily. It is now essential for coaches to stay connected and engage with clients using digital tools. Digital Marketing is all set to change the sporting world.

Important Digital Marketing tools are:

Social Media – Social media platforms such as Twitter, LinkedIn and Facebook can be utilized to promote exclusive content and reach out to all stakeholders. Be it live coverage during a particular sporting event, experts commenting on Twitter- user engagement is the key focus.

Blogging – Blogging by coaches can be used to motivate players and even counsel them. This is a great medium to highlight the trials and tribulations of a sportsman and bring to the forefront a more human aspect of the sport.

Brand Management using search engines – An important tool to promote is by using SEO for brand management. This is a technique where only positive listings appear in internet searches. This means that when a particular name is being searched, the first few pages will only showcase the positive or quality on brand links. The negative listings will be pushed down the result pages. This helps in creating and building the goodwill of a brand image. A sports coach can use this effectively to his benefit.

Sports Coaching is all about people, passion, and progress. A proper balance in communicating with the people with passion for the sport will bring about progress and hence build a great brand image