6 areas of risk in a Big Data project

Regarding Big Data projects there are some common risks related to 6 areas that every company should have in mind.

Business objectives

You should decide what you want to get with big data initiatives and have it clear:

  • Big Data is not for everyone, being in a traditional data-warehouse and BI environments should be advantageous
  • Have clear technical/business requisites and adapt your KPIs
  • Be ready to answer extra data-questions: sources, consumption, analysis type, hardware…

Business case

Big Data projects cannot be subject to traditional requirements:

  • Big Data projects should have innovation and exploratory purposes
  • Unless you have a solid big data path, big data exploration should be lean; you should fail cheap and begin with a pilot

Skills and acumen

Your company should have the right analytic and IT skills:

  • Is your business already getting any profit from data analysis?
  • Maybe you have the expertise in analytics consuming, but lack the expertise in new ways of doing it

Not an IT project

Do not make your Big Data project, just an IT project:

  • Big Data projects are not common-practice in most companies
  • Analytics and business expertise are actually more important

New stakeholders risks

Added to traditional risk of business-IT alignment, there are new risks:

  • Risks related to management and (new) vendors
  • There are new types of stakeholders added to those of IT and BI projects

Non-stop evolution

Big Data is not a goal, it’s a path, so keep learning and improving:

  • Technology does not stop: there are new ecosystems and new elements every other day
  • With Big Data technologies, come new needs: governance and lineage 

Anyway, when talking about Big Data the bigger risk is not moving on.