Top 4 Business Analytics Techniques By Vuelitics
Posted By velan | 18 January, 2021

18 January: Top 4 Business Analytics Techniques

Business Analytics is
● analyzing and transforming data into useful information by the use of math and statistics;
● discover and predict the trends and results, and
● fundamentally, make smarter, data-driven business decisions.

It uses predictive analysis, data mining, and statistical analysis to extract valuable insights from the data.
Business Analytics Techniques
Business analytics techniques provide solutions to everything a company needs to make informed decisions – from what is happening in the company to what panacea to apply for optimizing the business functions and how to positively impact the business goals.
1. Descriptive Analytics
The primary, yet the simplest technique entails decoding the data into understandable information. Its purpose is to outline the discoveries and help one understand what is happening in the business. Businesses use descriptive statistics on the existing data to discover the strengths and weaknesses to plan and strategize.

The two main approaches are data aggregation and data mining. Companies mine historical data to study consumer behaviors and engagements with their businesses for service improvement, targeted marketing, upselling, etc.
2. Diagnostic Analytics
It helps to diagnose why something happened in the past through data examination, data discovery, data mining, and correlations. It digs to the roots of the data to understand why the events occurred and ascertain the factors contributing to the outcome. Probability, feasibility, and outcome distribution are used for the analysis.

For example, diagnostic business data analytics will help with reasons for increase or decrease in sales in that year, however with limited actionable insights. It will help you understand the connection and sequence.
3. Predictive Analytics
Predictive analytics collects information and uses it to predict future outcomes. It predicts the probability of an event to occur in the future. It builds on the preceding descriptive analytics phase to extract the likelihood of the outcomes.

The specialty of predictive analytics is to create models to foretell future data. It is characterized by machine learning algorithms for analyzing and testing data.

For example, predictive analytics is used to determine the opinions posted on social media by common people and deduce their sentiment.
4. Prescriptive Analytics
Prescriptive analytics along with testing and a few other techniques are used to decide which outcome will produce the best results in a series of situations. It optimizes functions to produce the desired outcome while ensuring key performance metrics are used in the process.

For example, while booking a cab online the application uses GPS to locate the closest driver to your location.

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