Types of Data Analytics

We know that businesses use many kinds of analytics to take decisions. The main thing for an analyst or data scientist is to find the right analytics for business problems and their usage at right time in companies so that they can maximize the profits. There are different types of analytics as they all will provide insights from the data- they are

• Descriptive Analytics
• Predictive Analytics
• Prescriptive Analytics
• Diagnostic analytics
• Cognitive analytics.

Descriptive analytics is one of the most commonly used analytical techniques as it provides insights into where a company needs to improve by using its past and current data. Does it give answers to

• What happened?
• How much loss to the company?
• Where did it happen?

Nowadays, companies use many descriptive analytics software programs. Some of the popular tools are SPSS, MATLAB, Microsoft Excel, and data mining tools.

Diagnostic Analytics is another type of analytics as it will give the root cause of a problem that a business is facing and helps in solving critical situations. Most of the techniques that companies use to conduct analytics are the drill-down approach, data discovery tools, and correlation and data mining methods.

Predictive analytics is a type of analytics that predicts what will happen in the future by using past and present data. This is so popular that most businesses use this analytics to predict in various business fields. Some of the tools that companies use to conduct these analytics are Rapid Miner, R, Python, SAP, SAS, Microsoft Azure studio etc.

Prescriptive analytics is one of the advanced analytics as it analyzes the result of particular action or decision taken by the companies. To conduct this analysis, companies use past data, feed data and big data. Machine learning techniques and their models are mostly used to conduct this analysis.

Cognitive analytics is the most advanced analytics that companies have started using nowadays as it uses artificial intelligence, machine learning, and deep learning techniques to analyze the data. The information from this analysis is useful for future references.

Data analytics helps companies to solve many critical situations even if it is in a bad state. Companies are still able to come back and strengthen their position in the market. The only thing that needs to be done is to select the right analytics method for the situation and apply it at the right time so that companies are able to get good results from it.