5 Factors Impacting Your Big Data Project's Performance

FACTORS IMPACTINGYOUR BIG DATA PROJECT’S

PERFORMANCE

5

PRESENTED BY:

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.

Transferring data to a new database, new cloud platform, or new subscription within the cloud creates an extra step in an already complex process.

1STOP MOVING YOUR DATA

MOVING DATA IN THE MIDDLE OF A PROJECT INTERRUPTS THE ANALYTICS PROCESS.

End Result = Bottlenecks

Poorly constructed internal networks are quickly overwhelmed by rapid data growth.

2OVERLOADED NETWORKS

PLAN AHEAD TO ENSURE NETWORKS CAN ACCOMMODATE NEW AND RAPIDLY GROWING WORKLOADS.

Data sets grow quickly and unexpectedly, and the infrastructure behind it needs to be able to grow with it.

3SCALABILITY (OR LACK OF IT)

A SCALABLE STORAGE SYSTEM WILL PREVENT BOTTLENECKS AND LEAD TO FASTER AND EASIER DATA ACCESS.

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.

4WRONG DATA FOCUS

IDENTIFY WHAT DATA MATTERS MOST AND WHAT DATA IS RELEVANT TO WHICH TEAMS. THEN, MAKE SURE THE DATA IS ACCESSIBLE TO THOSE TEAMS.

Big data insights need to be acted upon quickly.

5SLUGGISH DATA CULTURE

CREATING A DATA-DRIVEN CULTURE IS JUST AS IMPORTANT AS HAVING THE RIGHT INFRASTRUCTURE IN PLACE.

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