How to move from Descriptive Analysis to Predictive Analysis

According to the industry, expert analytics are a very important aspect of the growth of the organization. Today the important attributes of analytics have been growing rapidly, and companies are moving for towards making them an essential part of their system. Analytics are data-driven methods that help the organization in management and decision-making. Suppose you execute the analytics in a proper and well-mannered. In that case, it can become your companion to make decisions in the business organization’s growth while considering the present and past data. Currently, many people are switching from descriptive analysis to predictive analysis. There are a lot of reasons for their decision. Today we are here to explore the various reasons why people are moving from descriptive analysis to predictive analytics.

Why move from descriptive analytics to prospective analytics?

It is very important to know why people want to move from descriptive analytics to predictive analytics. With a lot of research, we came to some conclusions which we want to discuss with you. Firstly predictive analytics are centralized around the present data to predict future situations. It helps to organize data and put all the data at one place for easy access. Predictive analytics improve business decision-making power because the decisions are dependent upon the data that is available in the present and also known to the decision-makers. Also, predictive analysis focuses on the real-time views of the data that help the business organization to know the various issues that will occur in the future and they can also take specific actions to solve those issues in advance. All the organizations are willing to know what will happen in the future except what has happened in the past. This is the major reason why they want to adopt predictive analysis as compared to descriptive analytics.

Also Read: Data Warehousing – Traditional vs Cloud!

Identify the mattresses you want to influence for your data
It is very important to know what the basic needs of the business are and what type of matrices. It needs, for example, if you want to grow your business in the future and you are not concerned with the past, then it is wise to move from descriptive analytics to productive analytic tools. It will help you to make decisions about whether you need to move or not.

Determine the various attributes

Before a customer takes your services that represent the experience of the user, you need to answer some questions. Is this because of an account balance change? Could it be a comment on social media? Could it be several calls to the call center? Etc. When you need all the answers, then you have to consider what are the potential data sources that can help you to talk to doing silly mistakes in the future. And you can only do this with the help of predictive analysis

Integrated data sources

Now you need to integrate various Tata sources that show the entire customer experience with your organization to build an effective and reliable predictive model. Various sources may include financial systems, ticketing systems, ERP, CMS, transactional systems, and social media sites. This may also involve various technologies like data warehouse solutions, cloud sources, on-premise databases, and even spreadsheets. This step is very important because without processing the various sources, you cannot be able to move from one analytics to another analytics tool.

Valuable Read: How Alpha helps in Data Integration and Data Analytics

Add the logic to the data model

After getting all the sources of data fully integrated into the analytics model, you need to add different predictive algorithms to the system to get the important predictive analytical reports. There are so many open-source technologies like R and Python, which can be used to develop a predictive algorithm. These algorithms will help you to get the analytics report, which is made with the combination of present data and future predictions. The reports are also capable of providing the operationalized data to the financial services organizations.

Create reports and dashboards to visualize the predictions

While moving from one analytics to another analytics, you need to set up a system that can help you visualize all the insights and reports. You must create a report and dashboards which are necessary to visualize past and future performance of the business organizations. Creating reports for call centers and other organizations is easily highlighted with the help of visual interfaces. Providing these proactive features to the users will help you to reduce the risk and also save your time in the field of decision-making.

Automatic data processing

Automatic data processing sequence means the connectivity of data integration and predictive algorithms. The organizations need to schedule the entire process to keep updated daily. They must have recent data from all the sources to ensure the predictive models are working accurately.

Enable the user with access to the predictive

Today providing access to few analytics to the end user is very important. Many companies, by doing the same thing, are growing very frequently. This is very important for the employees and end users must know what is happening with their data and what will happen with their data in the future. Various service agents and sales representatives in the organization must know what is going on at a higher level with the data of the public. This is the way by which you can enhance or increase the various sources to collect data and also take the help of your employees and end users to make your services better.

Conclusion

Moving from one analytics to another is not hard, but you need to be ready to handle the new analytics tools and services to make your source’s services better. While moving from descriptive analytics to predictive analytics, you may consider all the above-stated steps. If you feel that we missed something, and then please share it with us in the comment section