For the longest time possible, statisticians and data scientists have been relying on predictive analytics to help them in making daily business decisions. However, this entire situation is about to be changed by Big Data.

More and more data continues to stream online, and it gets integrated into existing Business Intelligence (BI), CRM, ERP and other important business systems. This brings the single view of the customer into focus. Even though the impact has not been felt by most customer service and field sales representatives, some companies are striving to see how that can come to play soon.

Big data has made a tool which mostly used for cohort and regression analysis available to line-level managers. This has helped the managers to use non-transactional data to make strategic and long-term business decisions.

However, big data is not about to overshadow traditional BI tools. Actually, big data will make BI a more valuable and useful tool for many businesses. You will always be required to look into the past to be able to predict the future, but with big data, you will be needed to do more than that. So, business intelligence will never go away, but big data will enhance it.

How can you know if the results you are getting in the initial stages of discovery will indeed bear out in the future? For example, many ladies love high-heel shoes than the standard heel shoes. So, preliminary analysis of the data may suggest that more high-heel shoes sell better than standard heel shoes, and this means high-heel shoes sell better.

Therefore, this is a correlation, not a cause. If you carefully study historical transaction data gathered from your business intelligence tools, you may realize that, for instance, your latest marketing campaigns are paying off because the retailers are putting high-heel shoes at eye level.

Social media will always have its value. It helps retailers know how the customers react to particular products and which stores sell these products most. Through this, the retailers can stock the stores according to the client’s response. BI and big data helps you look into these patterns and correlate your brand with geographic location and customer responses. Without this, you can miss out a small window of opportunity to sell your products.

Previously, many decisions were based on historical data, and by the time that happened, the trend may have already passed. But big data analytics helps that happen with a lightning speed.
This is accomplished through the integration of open source technologies, that is, the sources of big data platforms. Today, the cloud can easily capture and store large volumes of non-transactional data which was once not valued, or people had no idea of how to handle it.

Unstructured data is often viewed as the driving force behind big data. However, it barely plays a part in this. This information is usually correlated with geographical data, integrated with flat files of the existing structured customer data and adding streams from new sources. This helps you to understand how the users of a certain social media platform react towards your product. As a result, a new and very powerful tool is created.

There are two things which have happened to big data. It assists to bring in more variety of data from different sources, and this data can be micro-optimized. For instance, you can easily change behavior using tools like smartphones at the point where this tactical business decision has to be made.

Shortening time to answer key to big data analytics

The greatest advantage of this type of analytics is reducing the time to answer. Data scientists now require the shortest time possible to answer queries and models which took them months to build to answer.

Big data and business intelligence technologies have made this possible as they allow information to be worked with before it is optimized, rationalized or re-rationalized.

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