Data Analytics is the way that we look at data all around us. From the color of the birds in the sky to random numbers on our computer, the possibilities of data are endless. But what is Data Analytics and how is it useful for us? In simple terms, data analytics is nothing more than understanding the data collected and identifying the ways this data can predict future outcomes.
Take an example of a person buying a car. When buying a car, one looks at the price, its features, its color, and how well it can manage in the conditions that it is subjected to. Data Analytics is exactly like that. After understanding and analyzing the different types of data available and collected by us on a topic, we see how this data can help us identify the general effect of this product/company going forward in the future, and what we can change to make it better.
Applications in Real Life
In this article, however, we will not be looking at Data Analytics as a whole, but only focusing on the real-life applications of Data Analytics, that is, how can Data Analytics help us in our everyday problems. Let us look at some sectors where Data Analytics can help us solve real-life problems:
· Healthcare: The industry that has been impacted most by data analytics and data science is the healthcare industry. With the introduction of big data, we can analyze patient data such as records and present symptoms to identify the best possible treatment for him/her as well as identify any future side effects that may occur.
· Retail: Ever since the introduction of e-commerce, the retail industry has been severely impacted by Data Analytics. Analyzing data such as customer data, their preferences, product data, location data, etc. we can identify the needs of each customer and which product suits them. We can also look at how we can serve them better in the future.
· Entertainment: As the number of digital gadgets increases in the everyday life, the need for data analytics in the entertainment industry has also increased significantly. With the introduction of many streaming giants such as Netflix, Amazon Prime, Hotstar, Disney +, etc., customer data such as details, movie preferences, as well as data on the movies or TV shows streamed such as the number of users streaming, watch time and rating help us identify which genre is favored by the users and which does not perform as well.
To summarize, with the advancement of technology and the introduction of various types of technology in several sectors, the need for Data Analytics and analysis of data collected by various sectors has increased as well. With new technologies being discovered each day in this field, it is difficult to keep track of the ways Data Analytics can help each industry and the people around us. Nevertheless, we conclude that Data Analytics has helped in improving the quality of life of all people and has impacted the way the world functions.