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Data Analytics and Predictive Modeling

AI-Driven Data Analytics and Predictive Modeling

Are you an engineer or an experienced technology professional looking to pursue a career in AI-driven analytics and predictive modeling? While driving transformations, these are breakthrough technologies that would generate millions of new jobs. So, let’s explore them and a few other aspects of them.

AI’s Growth – Energy Consumption – Relation with AI-Driven Data Analytics and Predictive Modeling

AI’s exponential growth excites us all. However, while appreciating that, we often tend to ignore the other side – AI’s energy consumption! Now, why talk about AI’s energy use when the topic is AI-driven data analytics and predictive modeling? There’s a relationship between both and we will come to it soon.

So, AI data is stored on massive server farms that consume unimaginable energy. Let’s consider the simple example of ChatGPT. When you enter a prompt in it, the chatbot processes it using its servers hosted in data centers. These centers use up to 1.5 percent of the entire global electricity!

Isn’t that surprising? Of course, as users of AI, we would never think about it. Thus, AI’s value in the future will be determined not by money or the jobs it will replace but by the energy it will consume. However, how do you derive such conclusions? It is through AI-driven data analytics and predictive modeling.

AI-driven data analytics and predictive modeling are at a very high level of competition in the market. It might surprise you but these domains don’t yet exist in India as no player has invested in building servers and data computational farms AI requires. OpenAI works on Microsoft servers, which aren’t present in India now. However, it will as efforts are underway to bring it into the country. A Bangalore startup has invested a significant amount in this direction.

So, although AI-driven analytics and predictive modeling haven’t taken off in India yet, they will do so in the near future and create a demand for professionals well-versed in it. That’s how learning them steps in and is important. Let’s begin with what AI-driven data analytics and predictive modeling are.

About AI-Driven Data Analytics and Predictive Modeling

AI Data Analytics

AI data analytics uses AI to analyze large data sets, simplify trends and provide data analysts with vital insights. It helps support, automate, and simplify every stage of the journey of data analytics. AI tools can help collect data and prepare it for analysis. Further, you can train ML models and apply them to the prepared data to uncover patterns and insights. Eventually, AI enables analysts to comprehend and interpret trends and insights to drive better and more informed decision-making.

AI-driven data analytics can be used anywhere. For example, analysts can use it in the retail space, while dealing with massive data sets, comprising structured and unstructured customer data. It can help large retail players analyze data concerning various areas, including sales, loyalty program sign ups, average customer spending, highest-selling products, etc. These insights can steer informed decisions about inventory, marketing tactics, and more.

Read Full Blog – Phases of Data Analytics Lifecycle

Predictive Modeling

Now, what is predictive modeling? OK. So, the need for predictive modeling stems from the curiosity of knowing what will happen in the future or projecting the outcome of a particular event. So, predictive modeling is a statistical technique that helps analysts predict the results of future events based on historical data. It involves creating a mathematical model that collects relevant input variables and produces a predicted output variable.

Let’s look at an example of a predictive modeling application to understand it better. Risk is an integral part of the BFSI sector. A financial institution wouldn’t be able to compute the amount of risk involved in onboarding a particular customer only by looking at them or their photo IDs, etc. 

This is where AI plays a role as it helps build predictive models to help institutions determine the risk involved in customers and transactions. While providing loans, banks use credit scoring models to assess a client’s repayment ability. 

Similarly, they can use a statistical model to predict if a customer is likely to miss an EMI in the next two to three months or so! Additionally, predictive modeling helps assess people without a credit history.

AI Analytics and Predictive Modeling Career Opportunities

AI data analysts blend conventional data analysis skills and AI-ML expertise. Their skills aren’t confined to interpreting historical data but making crucial projections, and accelerating and enhancing decision-making across various departments. Hence, their crucial role in a company makes them in-demand professionals. 

Some roles include AI Data Analyst, Data Scientist, Financial Data Analyst, Risk Analyst, Healthcare Data Analyst, and Retail Analytics Specialist. AI data analysts have a place in every company that uses AI to analyze data, draw inferences, and make informed decisions.

On the other hand, predictive modeling is an area of expertise used across various job positions and realms. For example, a bank data scientist can use predictive modeling to project outcomes and help the organization make educated decisions about customer onboarding, risks, etc. 

Thus, predictive modeling can come in as an upgrade for such a person as it will help them enhance their skills and deliver more value to the company. Similarly, some other positions or professionals who must learn predictive modeling include AI programmers, financial data analysts, product data scientists, etc.

Final Words

AI data analytics and predictive modeling help you analyze quicker, and better and make informed predictions by leveraging AI’s predictive capabilities. They are emerging as technologies and also as encouraging career options, particularly given AI’s increasing dependence across the business world.

However, these are specialized areas requiring you to pursue formal education under expert trainers and through a competent course curriculum. Data science and data analytics courses in Pune prove crucial in this regard. Experienced and credible institutes like Ethan’s continuously update and upgrade them as per industry needs, ensuring competent education. Additionally, the abundant practical exposure you receive during the course prepares you better for the challenges as well as opportunities in the industry. Call us at +91 95133 92223 to  connect with our experts and explore more about our courses.

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