Big Data Analytics
Big data analytics is a term that describes the process of using data to discover trends, patterns, and other correlations, as well as using them to make data-driven decisions.
Nowadays, a growing number of companies, including Netflix, Hulu, Amazon and Spotify, use big data analytics to uncover useful insights for their business.
Types of Big Data Analytics
There are four types of big data analytics :
Diagnostic analytics is one of the more advanced types of big data analytics that you can use to investigate data and content. Through this type of analytics, you use the insight gained to answer the question, “Why did it happen?”
Let’s say there has been a drastic change in a product’s sale even though you have not made any marketing changes to it. You would use diagnostic analytics to identify this anomaly and find the causal relationship for such a change. This type of analytics enables businesses to understand their customers by using tools for searching, filtering, and comparing the data produced by individuals.
Descriptive Analytics is the examination of data or content, usually manually performed, to answer the question “What happened?” (or What is happening?), characterized by traditional business intelligence (BI) and visualizations such as pie charts, bar charts, line graphs, tables, or generated narratives.
Some tasks that require this type of analytics include the production of financial reports and metrics, surveys, social media initiatives. Most commonly reported financial metrics are a product of descriptive analytics, such as year-over-year (YOY) pricing changes, month-over-month sales growth, the number of users, or the total revenue per subscriber. These measures all describe what has occurred in a business during a set period.
Prescriptive analytics takes the results from descriptive and predictive analysis and finds solutions for optimizing business practices through various simulations and techniques. It uses the insight from data to suggest what the best step forward would be for the company.
Prescriptive analytics can help a business understand what their customers want to buy and why. These outcomes can be arrived at with detailed and timely information on customers and their purchasing journeys. This will help managers accelerate their sales cycles and be able to find and open up new avenues for cross and up-selling.
Predictive analytics is all about making predictions about future outcomes based on insight from data. In order to get the best results, it uses many sophisticated predictive tools and models such as machine learning and statistical modeling.
Predictive analytics is one of the most widely used types of analytics today. Through the predictions made with this type of analytics, companies can find ways to save and earn money, manage shipping schedules, and stay on top of inventory requirements.
Hope you enjoyed knowing about the different types of analytics ! Happy reading.