There are majorly three types of data analytics. They are:

• Descriptive Analytics: Descriptive analytics  uses historic data to provide insight on “What happened in the past”.  Data analyst works based on the historic data to deploy analytic techniques and deduce inference based on the data.  This process entails procedures such as data acquisition, data processing, data analysis, and data visualization. 
• Predictive Analytics: Predictive analytics uses data, statistical model & machine learning algorithm to forecast future outcomes.  This analytic offers answers to questions about what the future holds. Predictive techniques use historical data to recognize patterns, determine if they are likely to happen again, or build a predictive model from such data. Predictive analytics tools provide a way to peek into what may likely occur in the future, given a dataset of what has happened in the past. Predictive analytics techniques include a range of statistical and machine learning algorithms, which include: artificial neural networks, decision trees, and regression.
• Prescriptive Analytics: Prescriptive analytics are techniques put in place to ensure excellent practices are maintained, or woeful results are mitigated following results from descriptive and predictive analytics. This analytical technique assists in answering questions on what should be done and how to do it. By using metrics and insights from descriptive and predictive analytics, respectively, organizations can make reliable data-driven decisions when they face uncertainties. Advanced artificial intelligence techniques can automate prescriptive analytics by taking the outputs from predictive models and making decisions based on expert systems. Generally, this type of analytics illustrates an analysis based on set rules and recommendations to recommend a specific logical path for the organization.

Benefits of Leveraging Data analytics

The benefits of data analytics include, but are not limited to:

• Better decision making: Data analytics provides managers with the ability to make faster and more informed business decisions that are backed up by facts. Results from descriptive analytics can also guide marketers to target marketing campaigns accurately. 
• Improved Performance: Optimal performance is a factor of a deeper understanding of customer requirements, which, in turn, builds better business relationships. Data analytics also affords analysts and managers a way out for improved flexibility and an excellent ability to respond to change within the business and the market in general. Data analytics has been proven to reduce costs, hence, increasing profit.
• Increased awareness of risk, enabling the implementation of preventative measures: Predictive analytics provides options for optimum risk awareness as it offers a path to peek into possible future occurrences.

Applications of Data Analytics

Applications of data analytics include:

• Fraud Detection: Carefully analyzing customer spending trends can give away unusual patterns in their spending habits. This anomaly can be a sign of fraudulent activity on the account. Financial institutions and web commerce sites use this descriptive-analytical approach with prescriptive techniques to identify and stop fraudulent spending and web shopping.
• Energy Management: Power distributing companies can use data analytics to predict the amount of energy to be consumed around a specific time of the day. This gives the opportunity to accurately set prices for peak and off-peak periods. Energy consumers can also use descriptive data analytics to monitor how they use power and what they use it on. The results from this can allow them to better monitor energy use.
• Digital Advertisement: Targeted advertisement is a vital part of digital marketing. Accurately targeted adverts help organizations have a higher advert conversion rate. This reduces the amount spent on adverts and increases revenue.

Conclusion

As the amount of data generated daily rises to 2.5 quintillion bytes, there is a need to put it to good use. Data analytics offers a pathway for this development. There has been remarkable progress in data analytics, as shown in this article, and the only limitation might be your imagination!  

Lee, inventor of the World Wide Web. “Without big data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway.” – Geoffrey Moore, author and consultant.