4 Stages of Data Analytics

Stats on the amount of data being used throughout the world are mind-boggling. A report from Forbes suggests that Google conducts more than 3.5 billion searches every day. This boom in data has provided enterprises with enormous opportunities to derive insights that can help them achieve their business goals. The need for data analytics has become so crucial, that in the next five years there will be at least 40 percent more jobs for data scientists and analysts.

Hence, there is no denial of the fact that a job as a data analyst is the new big thing in the market. It is one of the highest paying jobs for freshers in the industry according to research. To become a data analyst, one needs to have in-depth knowledge of python programming and an ability to interpret data for getting insights on business opportunities. If you wish to get a job as a data analyst, this is the perfect time to do so. You can join classes for python training in Gurgaon or Delhi to get a grasp on the fundamentals of python and its usage in the industry.

Four Stages of Data Analytics

Before entering the world of data analytics, you need to know what is the most basic skill that an analyst must have? The most common answer you will get is that you require the ability to translate or interpret data to derive insights and solutions to help an enterprise in achieving its business objectives. In this article, we provide you with information on how you can analyze data through the four basic stages of data analysis which are listed below:

• Descriptive Analysis (For Insights on what is happening?)

Descriptive analysis provides a complete view of the key measures and metrics that are used within the company. It is the most common analysis done by a data analyst. An example of descriptive analysis can be the monthly profit and loss statement. The analyst can even have data on a huge population of customers. Using the data of customers and understanding their demographic information is categorized as descriptive analysis. Using good visualization tools can enhance the message of this type of analysis.

• Diagnostic Analysis (For Insights on why it is happening?)

The second step in solving the complexities of data is diagnostic analysis. After assessing the descriptive analysis of data, diagnostic analysis tools help the analyst in finding the root cause of the problem that the enterprise is facing. Well-designed business information dashboards that are incorporated with featuring filters and real-time reading of data at multiple successive points help analysts in drilling down the problems and isolating them.

• Predictive Analysis (For Insights on what will likely happen?)

Predictive analysis helps the data analysts in forecasting the problems that an enterprise is likely to face. It can be the likelihood of an event happening in future or estimating the point of time when the event might occur. In the predictive analysis, a variety of variable data is used to make predictions with the help of predictive models. The variability of the component data is important for good predictions, taking all components and compiling them together helps in better predictions. The market is filled with uncertainties and being able to make predictions can help enterprises in better growth.

• Prescriptive Analysis (For Insights on what can be done?)

In a prescriptive analysis, the data analyst utilizes the complete stages – beginning from what has happened, why it has happened and what will happen – to determine the best course of action to take for an enterprise. The prescriptive analysis is not just to find the best course of action but also to eradicate the complexities of the future; thus, helping the organizations in achieving their business objectives.

The importance of data analysis in the achieving the business objectives is growing day by day. With the increase in the amount of data usage, the jobs for data analysts and scientists will rise even higher. So if you are looking for a good career choice, the data analyst can be an important one. To learn how to become a good data analyst, you can opt for python training in Gurgaon or Noida according to your preference and take the first step towards your career.