BA is comprised of three categories of analytics. Write a summary for each category and include at least two techniques for each of the three categories of analytics.
BA is comprised of three categories of analytics.
Write a summary for each category and include at least two techniques for each of the three categories of analytics.
Businesses use analytics to explore and examine their data and then transform their findings into insights that ultimately help executives, managers and operational employees make better, more informed business decisions. there are three types of analytics businesses use are descriptive analytics, what has happened in a business; predictive analytics, what could happen; and prescriptive analytics, what should happen. While each of these methodologies offers its own unique insights, advantages and disadvantages in their application, used in combination these analytics tools can be an especially powerful asset to a business.
- descriptive analytics:-
Descriptive analysis or statistics does exactly what the name implies: they “describe”, or summarize, raw data and make it something that is interpretable by humans. They are analytics that describe the past. The past refers to any point of time that an event has occurred, whether it is one minute ago, or one year ago. Descriptive analytics are useful because they allow us to learn from past behaviors, and understand how they might influence future outcomes.
The vast majority of the statistics we use fall into this category. (Think basic arithmetic like sums, averages, percent changes.) Usually, the underlying data is a count, or aggregate of a filtered column of data to which basic math is applied. For all practical purposes, there are an infinite number of these statistics. Descriptive statistics are useful to show things like total stock in inventory, average dollars spent per customer and year-over-year change in sales. Common examples of descriptive analytics are reports that provide historical insights regarding the company’s production, financials, operations, sales, finance, inventory and customers.
Use Descriptive Analytics when you need to understand at an aggregate level what is going on in your company, and when you want to summarize and describe different aspects of your business.
Predictive Analytics: Understanding the future
Predictive analytics has its roots in the ability to “predict” what might happen. These analytics are about understanding the future. Predictive analytics provides companies with actionable insights based on data. Predictive analytics provides estimates about the likelihood of a future outcome. It is important to remember that no statistical algorithm can “predict” the future with 100% certainty. Companies use these statistics to forecast what might happen in the future. This is because the foundation of predictive analytics is based on probabilities.
These statistics try to take the data that you have, and fill in the missing data with best guesses. They combine historical data found in ERP, CRM, HR and POS systems to identify patterns in the data and apply statistical models and algorithms to capture relationships between various data sets. Companies use predictive statistics and analytics any time they want to look into the future. Predictive analytics can be used throughout the organization, from forecasting customer behavior and purchasing patterns to identifying trends in sales activities. They also help forecast demand for inputs from the supply chain, operations and inventory.
One common application most people are familiar with is the use of predictive analytics to produce a credit score. These scores are used by financial services to determine the probability of customers making future credit payments on time. Typical business uses include understanding how sales might close at the end of the year, predicting what items customers will purchase together, or forecasting inventory levels based upon a myriad of variables.
Use Predictive Analytics any time you need to know something about the future, or fill in the information that you do not have.
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