Eight Classic Big Data Mistakes
Focusing on Technologies Instead of Business
CIOs and IT leaders too often lose sight of business requirements because they get caught up in the big data infrastructure planning. Work with business closely to ensure tech aligns with needed outcomes.
Not Knowing What You’re Looking For
Always precisely determine what you seek at all stages. Otherwise, your analytics team will get lost amidst the big data.
Disregarding Context
All data should be assessed for context and relevancy or it will never translate to usable business value.
Dismissing Bias
Preconceptions help guide teams toward effective analytics. But they can also skew conclusions.
Shortchanging Data Quality
Deploy tools such as language correction libraries to process unstructured data in order to ensure its integrity.
Not Securing Data Sponsorship
To avoid pushback somewhere high along the leadership chain, you need an executive influencer to serve as an advocate for the data.
Not Executing a Cost-Benefit Analysis
Every project needs its own assessment. If you simply apply an initial use case model to all of those projects which follow, the cost analysis may veer off target.
Dwelling on What Already Happened
While you need to understand why a customer behavior ortrend resulted in a certain metric, the point of analytics is translating that into what’s going to happen next.
