There are 6 important areas of risk in every project related to Big Data and analytics: business objectives, business case, skills and acumen,not any type of IT project, new stakeholders in a non-stop evolution environment.

1. © Pragsis Bidoop 2015. Big Data & Analytic experts
6 Areas of RISK in a BIG DATA project

2. © Pragsis Bidoop 2015. Big Data & Analytic experts
Top Risks:
BUSINESS
OBJECTIVES
Decide what you want to
get with big data and
explore initiatives
BUSINESS
CASE
Big Data projects cannot
be subject to traditional
requirements
SKILLS AND
ACUMEN
Have the right analytic
and IT skills in your
company

3. © Pragsis Bidoop 2015. Big Data & Analytic experts
Top Risks:
NOT AN IT
PROJECT
Do not make your Big
Data project just an IT
project
NEW
STAKEHOLDERS
New risks and needs
added to those traditional
of business-IT alignment
Keep learning and
improving
NON-STOP
EVOLUTION

4. © Pragsis Bidoop 2015. Big Data & Analytic experts
Why you should have them in mind:
 Big Data is not for everyone
 Have clear technical/business requisites
 Be ready to answer extra data-questions
 Big Data projects should have innovation
and exploratory purposes
 Unless you have a solid big data path,
big-data projects should be lean
 Big Data requires new skills
 Maybe you have the expertise in
analytics, but lack the expertise in new
ways of dealing with (new) data

5. © Pragsis Bidoop 2015. Big Data & Analytic experts
Why you should have them in mind:
 Big Data implies new types of
stakeholders added to those of IT and
BI projects
 Big Data projects are not common
practice in most companies
 Analytics and business expertise are
actually more important
 Technology does not stop: there are
new ecosystems and new elements
every other day
 With Big Data technologies, come new
needs: governance and lineage

6. © Pragsis Bidoop 2015. Big Data & Analytic experts
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