Data Analytics – Which type suits your business best?
Data analytics cannot be considered as a one-size-fits-all blanket strategy. Data Analytics is used for different purposes depending on the organizational structure and its goals. There are three major types of analytics used in corporates
- Descriptive Analytics
- Predictive Analytics
- Prescriptive Analytics
Let’s know a brief about them:
Descriptive analysis answers the question “What has happened?”. Descriptive analytics involves techniques that analyze the data coming in real-time and historical data.
The main objective of descriptive analytics is to find out the reasons behind precious success or failure in the past.
Small and big businesses can use descriptive analytics to understand the overall performance of the company at an aggregate level and describe the various aspects which you can use to identify the gaps.
Example 1: Google Analytics is an example of descriptive analytics. The tool mines user data and present in a way that is useful to the end user.
Example 2: Cohots is another form of descriptive analytics where you learn the behavior of your users over a given period of time.
Predictive analytics answers the question “What would happen in future if <” condition”>?”. Analysing past data patterns and trends can accurately inform a business about what could happen in the future. This helps in setting realistic goals for the business, effective planning and restraining expectations. Predictive analytics predicts the likelihood of a future outcome by using various statistical and machine learning algorithms
Predictive analytics can be further categorized as –
- Predictive Modelling –What will happen next, if?
- Root Cause Analysis-Why this actually happened?
- Data Mining– Identifying correlated data
- Forecasting– What if the existing trends continue?
- Monte-Carlo Simulation – What could happen?
- Pattern Identification and Alerts –When should an action be invoked to correct a process
Example 1: Man has discovered various interstellar objects and patterns using predictive analytics.
Example2: Companies like Walmart, Amazon use it to predict customer behavior which results in exemplary sales.
They identify trends in sales based on purchase patterns of customers, forecasting customer behavior, forecasting inventory levels, predicting what products customers are likely to purchase together so that they can offer personalized recommendations, predicting the number of sales at the end of the quarter or year.
Prescriptive Analysis answers the question “What to do. ”Big data might not be a reliable crystal ball for predicting the exact winning lottery numbers, but it definitely can highlight the problems and help a business understand why those problems occurred. Businesses can use the data-backed and data-found factors to create prescriptions for the business problems, that lead to realizations and observations.
Simulating the future, under the various set of assumptions, allows scenario analysis – which when combined with different optimization techniques, allows prescriptive analysis to be performed.
Business rules are preferences, best practices, boundaries and other constraints. Mathematical models include natural language processing, machine learning, statistics, operations research, etc.
Example 1: Aurora Health Care system (Wisconson, USA) saved $6 million annually by using prescriptive analytics to reduce re-admission rates by 10%. Prescriptive analytics can be used in healthcare to enhance drug development, finding the right patients for clinical trials, etc.
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