big data analytics

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Big data analytics applies to data sets whose size is beyond the ability of commonly used software tools to capture, manage, and process data in a timely fashion.

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Big Data Analytics:

Big Data Analytics ParStream

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A process of examining large amounts of data, A variety of types to uncover hidden patterns, unknown correlations and other useful information. That information can provide: Advantages over rival organizations B usiness benefits E ffective marketing and increased revenue Let Us Understand Big Data Analytics

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Primary goal of big data analytics is : To help companies make better business decisions: By enabling data scientists & other users to analyze huge volumes of transaction data. That may be left untapped by conventional business intelligence programs. Used as part of advanced analytics disciplines such as predictive analytics and data mining. Processing of large data sets across clustered systems. Why Big Data Analytics?

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Detect, prevent and remediate financial fraud. Calculate risk on large portfolios. Execute high-value marketing campaigns. Improve delinquent collections. big data can benefit your business

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BI (business intelligence) solutions New visual resources New data sources Cloud solutions Latest trends Social intelligence Mailing intelligence Big data analysis techniques can be

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IT is under pressure to tap into growing quantities of data to help the business make better, informed decisions by combining new sources of big data with existing enterprise dark data. How will you uncover more customer and business insight and more data value? Predictive Analytics Behavioral Analytics Data Interpretation Key Challenges in Big Data

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Big data analytics applies to data sets whose size is beyond the ability of commonly used software tools to capture, manage, and process data in a timely fashion. “The amount of data in our world has been exploding, and analyzing large data sets, so called big data will become a key basis of competition, underpinning new waves of productivity growth, innovation, and consumer surplus” CONCLUSION

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