Read more at http://blog.promptcloud.com/2014/07/a-guide-to-evaluate-your-big-data-needs.html

2. EVALUATING
YOUR
BIG DATA NEEDS
Dazed by the volume of your big data?
Facing a data deluge?
Don’t worry, big data isn’t all that difficult to use.
Simply go through this guide and see how you can cash in on big data!
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3. I
BE DISCREET
Data is the means, not the end. Iden fy your needs, know your
problem, and use your own judgment to take the decisions based on
analysis results.
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4. II
KNOW WHAT YOU WANT
Know your big data needs. Analyze the viability, gauge its u lity in
addressing your problem. Don't end up inves ng- and was ng-
resources in 'be er' technology.
www.promptcloud.com

5. III
CHOOSE DATA
To begin using data analy cs start by priori zing: filter the noise; find
data sets that help resolve immediate problems. Learn to iden fy
pools with large number of fish, don’t run a er Moby Dick!
www.promptcloud.com

6. To begin using data analy cs start by priori zing: filter the noise; find
data sets that help resolve immediate problems. Learn to iden fy
pools with large number of fish, don’t run a er Moby Dick!
IV
MATCH DATA
Big Data is redundant if not matched properly to your needs.
Incorporate it into your business needs. Use it to gather insights,
derive a strategy from it. Align data to business needs, not vice versa.
www.promptcloud.com

7. To begin using data analy cs start by priori zing: filter the noise; find
data sets that help resolve immediate problems. Learn to iden fy
pools with large number of fish, don’t run a er Moby Dick!
V
TRIAL & ERROR
Churn data in different ways to gather new perspec ves. Start from
scratch and reinvent the process. Sharpen your analy cs tools;
crystallize data.
Save me and resources as new data sets you con nue innova ng
and through newer data sets!
www.promptcloud.com

8. To begin using data analy cs start by priori zing: filter the noise; find
data sets that help resolve immediate problems. Learn to iden fy
pools with large number of fish, don’t run a er Moby Dick!
VI
CURATE DATA
Quality data ma ers. Don’t sit on irrelevant data: it’ll only compound
your problems! Offload what you don't need. Or best, start off with
relevant data.Reduce the noise and to sing the tune be er.
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9. THANK YOU
Visit blog.promptcloud.com for more
interes ng reads on Big Data and Analy cs.
www.promptcloud.com