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5 FACTORS IMPACTING YOUR BIG DATA PROJECT’S PERFORMANCE
BIG DATA HAS HUGE POTENTIAL.
! BUT IT COMES WITH ACCOMPANYING RISK
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.
1 STOP MOVING YOUR DATA Transferring data to a new database, new cloud platform, or new subscription within the cloud creates an extra step in an already complex process.
MOVING DATA IN THE MIDDLE OF A PROJECT INTERRUPTS THE ANALYTICS PROCESS.
End Result = Bottlenecks
2 OVERLOADED NETWORKS Poorly constructed internal networks are quickly overwhelmed by rapid data growth.
PLAN AHEAD TO ENSURE NETWORKS CAN ACCOMMODATE NEW AND RAPIDLY GROWING WORKLOADS.
3 SCALABILITY (OR LACK OF IT) Data sets grow quickly and unexpectedly, and the infrastructure behind it needs to be able to grow with it.
A SCALABLE STORAGE SYSTEM WILL PREVENT BOTTLENECKS AND LEAD TO FASTER AND EASIER DATA ACCESS.
4 WRONG DATA FOCUS 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.
IDENTIFY WHAT DATA MATTERS MOST AND WHAT DATA IS RELEVANT TO WHICH TEAMS. THEN, MAKE SURE THE DATA IS ACCESSIBLE TO THOSE TEAMS.
5 SLUGGISH DATA CULTURE Big data insights need to be acted upon quickly.
CREATING A DATA-DRIVEN CULTURE IS JUST AS IMPORTANT AS HAVING THE RIGHT INFRASTRUCTURE IN PLACE.
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