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Why Big Data Big Analytics

The importance of big data in the current technological environment is paramount. Industries are trying to identify the customer behavior and purchase trends to promote its product.  Industries like healthcare, Financial Firm, Government data, Retailer and Telecom data is increasing day by day. The opportunities and uses of Big Data in the coming years for retail, pharmaceutical, financial services industries are huge. The recent study conducted by the Premium Business School with IBM about the big data activities in the today’s organization clearly reflects that. The result reveals about the stages of the big data adoption followed by top 5 Big Data Use cases identified by IBM. This shows that software giant IBM is started focusing on Big Data and developed a product Info Sphere. It tells the importance of Big Data and other tools used in the different Use Cases.

 

Recent study conducted by premier business school along with IBM discussed about the stages to start Big Data in the organization. It says 6 percent of the organization already executing big data initiatives but there is no evidence mentioned about analytics benefits for every dollar spent. It also says 47 percent developing a strategy based on the business needs. However, author Michael Minelli, Michele Chambers and Ambiga Dhiraj discussed in the Big Data Big Analytics book quoted major Big Data Exploration is based on the three V’s – Volume, Velocity and Variety are sync with the ‘Big Data Big Analytics’. Data Volume, Data Variety and Data Velocity are varies from industry to industry. Data Variety can be i.e. structured, unstructured, semi-structured.

 

The usage of unstructured data is relatively text heavy and it should be used in a different context. Velocity of the data boat also is not same for all industries. For e.g. banking transaction volumes are larger than the Pharmaceutical Industry transaction volumes. Banking transactions are more structured and velocity of the transaction is quite faster than other industry. Hence, point of developing a strategy is purely based on the business needs is completely sync with the ‘Big Data Big Analytics’ author. This point is very well adjudged by the product of IBM Info Sphere. It has the data Explorer and the capability to retrieve 3 V’s even in the semi-structured data for the organization. It also tells importance of the unstructured data and ways to collaborate the unstructured data. It implies Big Data Big Analytics, concentrates not only about the structured & semi structured but also the unstructured data which significantly contributes to the business decisions.

 

In this present global scenario, understanding customer buying behavior using Big Data Big Analytics tools is possible. IBM Info Sphere has the capability to derive the customer behavior without logging into multiple applications. IBM Info Sphere data explorer works with combination of Master Data Management to combine information in context from different application and repositories in (CRM, ECM, Supply chain, order tracking database and email etc.,) without logging into multiple systems. Usage of different kinds of tools to bring multiple types of data together and make decision is inevitable.  Usage of Multiple application to retrieve unstructured and semi structured data together helps to arrive better decision about the customer.

 

Security is foremost important in the financial transactions. Percolator query can handle both structured and unstructured data. IBM Info Sphere streams and Hadoop analytics enhance security and intelligence analysis by accessing even unstructured data from smart devices and social network, e-mail, POS and other data’s. The best approach to solve fraud with big data in social network analysis is possible using IBM Info Sphere tools. The state of the big data technology and tools used for the integration is increasing in many large organizations. Ventanna Research Report reveals that 76 percent use RDBMS and 61 percent use text files for integration. In addition to that more than 55 percent use their own existing data technology for big data integration. The cost involved in using these tools and only large organizations are comfortable to use or adapt their own existing infrastructure and use RDBMS from Oracle for integration. With these advance tools organization able to meet their business needs

 

We believe technology advances over time, size of datasets that qualify as big data will also increase. Hence, planning for the big data integration is inevitable but with respect to industry and business demand. Also, research report from Ventana supported data integration is inevitable in the coming days for large organization. Customer behavior can be extracted using Unstructured, Structured or Semi-structured data with multiple tools. 55 percent of the organization, inclined to select big data integration in the next 12 to 18 months. Out of this 55 percent, 25 percent inclined to use Hadoop as a big data integration technology. The In-memory database, NoSQL tools, specialized database are minority tools and 93 percent of the organizations are satisfied with it without adapting high end Hadoop technology. It implies organizations are comfortable in using minority tools compare to Hadoop technology for big data integration. As per the Ventana research report, 56 percent said integration of big data technology improved business activities and processes and 93 percent use dedicated data integration product to improve business activities and process.

 

This clearly says organization showed interest for big data integration however these data arrived only from selective participant with restricted to limited demographic areas. Finally, I conclude that volumes of data have been quadrupled. Most big firms identified the big data trend and ready to accept more Volume, Velocity and Variety in unprecedented ways. This perfect storm of the three V’s makes it extremely difficult and cumbersome with the current data management and analytics technology and practices.

 

 

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