With the revolution in other sectors, Big data and business intelligence has been also revolutionized. We have now so many tools and technologies available in the market that helps to make work done in less time and with fewer efforts.

These days’ are now equipped with the advanced big data analytics services and it become an essential and fundamental part of the business organizations. So many companies are looking for the digital transformation of the organization to be part of the digital race of the business organizations. You can see analytics as an experience with which you can improve your digital implementations. This never-ending stream for a business organization is information and that is very much valuable for them as well. The question we have here is “What is the future of business with analytics?” To answer this I stated below some necessary things which may help you to clear the picture in your mind about the future of analytics.

1 Data Quality Management (DQM)

In the few past years, the analytics trends in terms of Data quality grew very fast. The importance of Big Data services is realized with the help of Business intelligence to analyze and grab values from a huge number. Data collection process these days reached a very high scale. But when we made reports from these huge databases then the results are much prone to errors.  It is believed that in future Data Quality management will become an important activity.

DQM is an analytical process to check the quality of data storage methods. There are so many important aspects of for which DQM is responsible like data storage patterns, data classification, manage data inputs, etc.

2 Data Discovery

Don’t mix Data Discovery with Data mining, both are different concepts. According to experts data discovery is one of the top 5 future trends. It is basically a process for collecting data from different types of databases and silos and combines it into a single source for easy and instant evaluation. This is a kind of big data analytics which can help you to make data easy to use, agile, flexible, reduces insight time, and also allow the organizations easy handling of a variety of data. You can perform this action with the help of data discovery and data visualization tools.

One of the most efficient methods of data discovery is using web scraping. With this method you can extract relevant data directly from websites, social media and blogs to gain insight into consumer behavior and other market trends. A web scraping proxy solution which can handle large amounts of data from these sources can go long ways in taking your business analytics to the next level.

3 Predictive analytics

Predictive analysis is a process of extracting information from available data in order to presume the future possibilities. It can be considered an updated version of data mining that refers only to the data forecasting. It helps to figure out what might happen in the future with all kinds of possibilities. The analytics presume the possibilities of future data that is why there are also the possibilities of errors. So with the help of analytics, you can try to avoid these errors. These days airlines are using this to determine how many tickets to sell at different prices.

4 Prescriptive analytics

It helps you to go a step forward in the future. It is helpful to figure out what decisions should be taken place in different situations and which steps to take in order to achieve the goal. The perspective analysis makes it possible with the help of various techniques like graphs, simulation, neural networks, event processing, recommendation engines, machine learning, and heuristics. The analytics helps you to see what will be the future effects of future decisions on various aspects?

Perspective analytics allows you to optimize scheduling, inventory, production and supply chain designs to provide customers what they want.

5 Digital Ethics and privacy

In order to maintain security Digital Ethics and privacy plays an important role.  Data loss is something which can ruin the organization. Data security issues are very common in these days. But in future to maintain the security you have to be alert all the time. So many companies like MySpace, Compass Bank, NHS, LinkedIn, Apple, etc are pushing themselves very much in the field of security. Now the digitalization of data increases the risk of data breach and losses. So, there are so many tools by which you can see the possibilities of data loss and you may be able to close the loopholes in advance.

6 Embedded analytics

Embedded analytics helps business process applications to integrate analytical content. It provides related information and analytical tools for the various tasks so that the user can behave smartly. Various organizations started to take advantage of the embedded analytics on a wider scale. The analytics are helpful in both internal and external operations to provide meaningful interactions to the customers, suppliers, and partners. In addition, these analytics help you to align the overall convergence of technologies.

7 Proactive data analysis

The organization is very sensitive in the use of the data, AI and machine learning concepts. The reason behind this is the way of misleading optimization of data. In this analytics, we assume that the analytics is the part of optimization. In other words, we can say that this is the scientific way of converting data into insights to make it more sensible and usable. These insights are very helpful to predict what is coming in the future and you will get a chance to make the right decision at the right time.


The future of analytics is very bright in the world of business organizations. With some enhancements, we can integrate data today and we may make the processes much better with the future predictions. There are so many moving pieces when we see the future of data analytics. But with the right implementation and projection, you can make these things better for all.