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5 Factors Impacting Your Big Data Project's Performance

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5 FACTORS IMPACTING YOUR BIG DATA PROJECT’S PERFORMANCE


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PRESENTED BY:


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BIG DATA HAS HUGE POTENTIAL.


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! BUT IT COMES WITH ACCOMPANYING RISK


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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.


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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.


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


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End Result = Bottlenecks


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


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


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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.


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


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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.


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


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5 SLUGGISH DATA CULTURE Big data insights need to be acted upon quickly.


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


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