5 Factors Impacting Your Big Data Project’s Performance
Big data analytics projects frequently fail to return ROI due to these five factors. Learn how to make your big data cloud project succeed.
@Ronald_vanLoon: 5 Factors Impacting Your Big Data Project’s Performance | #BigData #ROI #rvl
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. 1 STOP MOVING YOUR DATA
Poorly constructed internal networks are quickly overwhelmed by rapid data growth. 2 OVERLOADED NETWORKS
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)
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
Big data insights need to be acted upon quickly. 5 SLUGGISH DATA CULTURE