Words reading "Artificial intelligence AI", miniature of robot and toy hand are pictured in this illustration
Reuters
Numbers, numbers everywhere! But not many to make sense of these numbers! Imagine the huge amount of data generated every minute in the current world. When the teacher is late to class, what do you do? Most students open their phones to browse the internet and check online deals. Imagine you are checking for a deal on shirts. Suddenly, you realise mom’s birthday is coming up, and you move on to a page showing, say, ladies’ shirts. A bot pops up saying that there is a huge discount on perfumes.
So, you have browsed through many varied pages in a few minutes. Now, the e-commerce website is confused. Are you a genuine buyer? Or are you there just passing your time? Also, which page should it show you the next time you log in? These are a few instances where data leads you to insights.
But how do we get a grasp on these big chunks of data? The true power lies in converting raw numbers into meaningful insights that drive decision-making and strategy. This transformation process, often called data analytics, involves several stages, each crucial for turning data into actionable knowledge.
This is where data analytics comes into play, transforming raw data into meaningful insights that can drive informed decisions. In today’s digital world, where data is generated at an unprecedented rate, analysing and making sense of this data is crucial. Whether it is an e-commerce platform trying to predict your next purchase, a streaming service recommending a movie, or an educational institution analysing student feedback, data analytics helps turn the chaos of data into actionable strategies.
Every click you make, every page you visit and every product you check on the e-commerce website you browse is tracked and recorded. This data is fed into complex algorithms designed to identify patterns and predict behaviour. If you lingered on the perfume page but didn’t make a purchase, the algorithm might conclude that you are interested in perfumes but need a little more incentive to buy. The next time you log in, you might see a special discount or a reminder about the product. This is a direct result of data analytics in action.
Predicting future
Data analytics isn’t just about understanding past events but also about predicting the future. Predictive analytics uses historical data to forecast future outcomes. For instance, OTT platforms analyse your viewing history, the time you spend watching certain genres, the ratings you give, and even the time of day you usually watch. By doing so, they can predict with a high degree of accuracy which shows or movies you might enjoy next. This personalised recommendation system is powered by predictive models that continually learn and adapt to your preferences.
However, the power of data analytics extends far beyond e-commerce and entertainment. For example, in education, institutes can analyse student performance data to identify patterns indicating intervention needs. If a student’s grades are declining, data analytics can help identify the areas where they are struggling, allowing educators to provide targeted support. Similarly, universities and colleges can analyse reviews and feedback to improve their services, tailor their courses, and enhance student experience.
In the corporate world, data analytics is a vital tool for decision-making. Companies use data to analyse market trends, customer behaviour, and operational efficiency. For example, a retailer might use data analytics to determine which products are selling well and which are not. By analysing this data, they can make informed decisions about inventory management, marketing strategies, and pricing. This helps businesses stay competitive and responsive to changing market conditions.
Thus, data analytics is a powerful tool that helps make sense of the vast amounts of data generated daily. Courses in data analytics empower one to get into the world of making sense of how we live and work.