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.

1. Big Data Analytics
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2.  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
• Business benefits
• Effective marketing and increased revenue

3.  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.

4.  Detect, prevent and remediate financial fraud.
 Calculate risk on large portfolios.
 Execute high-value marketing campaigns.
 Improve delinquent collections.

5.  BI (business intelligence) solutions
 New visual resources
 New data sources
 Cloud solutions
 Latest trends
• Social intelligence
• Mailing intelligence

6.  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

7. 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”

8. To know more visit: https://www.parstream.com