5. Big data projects are complex with numerous
moving parts that impact whether a big data
project is successful or not. If your big data
project currently isn’t up to par, consider
these 5 factors.
6. Transferring data to a new database, new cloud
platform, or new subscription within the cloud creates
an extra step in an already complex process.
1
STOP MOVING YOUR DATA
7. MOVING DATA IN THE MIDDLE
OF A PROJECT INTERRUPTS THE
ANALYTICS PROCESS.
10. PLAN AHEAD TO ENSURE NETWORKS
CAN ACCOMMODATE NEW AND RAPIDLY
GROWING WORKLOADS.
11. Data sets grow quickly and unexpectedly, and the
infrastructure behind it needs to be able to grow
with it.
3
SCALABILITY (OR LACK OF IT)
12. A SCALABLE STORAGE SYSTEM WILL
PREVENT BOTTLENECKS AND LEAD TO
FASTER AND EASIER DATA ACCESS.
13. Even with every other factor fully optimized,
focusing on the wrong data leads to dead ends and
a team that is swamped with irrelevant information.
4
WRONG DATA FOCUS
14. IDENTIFY WHAT DATA MATTERS MOST
AND WHAT DATA IS RELEVANT TO WHICH
TEAMS. THEN, MAKE SURE THE DATA IS
ACCESSIBLE TO THOSE TEAMS.
15. Big data insights need to be acted upon quickly.
5
SLUGGISH DATA CULTURE
16. CREATING A DATA-DRIVEN CULTURE IS
JUST AS IMPORTANT AS HAVING THE
RIGHT INFRASTRUCTURE IN PLACE.
17. Are you looking to leverage the power of big
data? Should you buy and build or rent and pay
as you grow? Click the button to see a complete
big data vendor comparison.
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