Data Analytics – A trending and popular career field for the future



ExcelR Solutions. Data analytics is a science field to analyze raw data to conclude the information. Most of the techniques and data analytics processes have been automated into algorithms and mechanical processes which work on raw data for human use. Data analytics methods can disclose metrics and trends which would contrarily be lost along with large information. Then, this information can be used to optimize the processes to boost the total business or system efficiency.

Why is there a need to understand data analytics?

Data analytics is an open term that includes various types of data analysis. Any kind of information is subjected to data analytics methods to receive awareness to improve things. For instance, a manufacturing company regularly records the downtime, work queue and operation time for different machines and the data is then analyzed to plan out the number of workloads for the machines so that the machines can operate to their maximum capacity. Data analytics can perform much more than identifying bottlenecks in the production process. Also, gaming companies use data analytics techniques to set schedules for receiving rewards for players which keeps the majority of players engaged in the game. Likewise, content-driven companies use a lot of data analytics tools for customers that keep them hooked onto the content through clicking, watching and restructuring content to receive another click or view from customers.

Significance of data analytics

ExcelR Data Analytics Courses In Pune. Data analytics is integral as it helps businesses to enhance their performances by embedding it to the business model. The companies will be able to reduce costs by finding the most efficient manner in doing business and by allowing companies to store a vast amount of data. Also, a company can use data analytics to make decisions that are better for business and help in evaluating customer trends and satisfaction that can result in the production of new and well-equipped products and services.

Types of data analytics

Data analytics is branched into four primary types of analytics.

1.        Descriptive analytics
   This type of analytics depicts the events that have happened over a specified period, for example, have the number of views increased and have the sales increased compared to the previous month?
2.      Diagnostic analytics
   This type of analytics has emphasis on the reason for something to happen. This includes many different data inputs and a small part of hypothesizing. For instance, a question on whether the weather affected the sales of beer or did the new marketing campaign have an impact on sales.
3.       Predictive analysis
   This type of analytics analyzes the likelihood of events happening in the future. For example, the impact of sales due to the hot summer in the previous month or the various types of weather models used to predict the hot summer in the present year.
4.       Prescriptive analytics
   ExcelR Solutions. This type of analytics mentions a suitable course of action for predicting events to happen in the future. For instance, if the possibility of a hot summer occurring is measured based on the model showing 58% above the average of different types of weather, then a suitable course of action would be to include an evening timing to the brewery and rent a supplementary tank to improve output.


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