Modern needs of Big data consumption require data integration before data actually hit the business intelligence tools. This includes leveraging complex and unstructured data and enables raw data to flow securely through business. Today, even the smallest companies produce huge amount of data across systems which need to communicate with each other and therefore requires a platform to pipe all these data sources into Data Lakes.

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Most of companies are facing problem with big data. The top 5 Big Data problems are: - To get correct insights from the data, Data silos make it time consuming to draw conclusions from it, Unreliable data, Speedy technology, and Lack of skilled personnel. Thus, if decisions are not taken at a high pace it can affect the outcome as Big Data is fast data. The solution to the above problem is Data Integration. This allows to get deeper insight from Big Data. This will also increase the trustworthiness of the data. Now to integrate data it is of utmost importance to use clean data. This can be done by removing duplicates, verifying and updating data on a timely basis and implementing consistent data entry.

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As soon as Big Data started transpiring into the future, it is believed that it would transform the way companies sell, market, communicate, educate etc. There has been an enormous progress of Big Data which helps in data integration and analytics. Nowadays much of the work is concerned on future and therefore it focuses on identifying the consequences of it. The prospect of Big Data has enlarged in recent days and there are key "first-order", second and third order, sample "second-order", sample "third-order implications of Big Data. With the conversion of Big Data into Implications Wheel, it furnishes everyone with new perception and control.

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