Table 1: Common mistakes for analytics projects.
Failing to build the need for big data within the organization
Islands of analytics with “Excel culture”
Data quality and reliability related issues
Not enough investigation on vendor products and rather than blindly taking the path of least
resistance
Departmental thinking rather than looking at the big picture
Considering this as a one-time implementation rather than a living eco-system
Developing silo dashboards to answer a few questions rather than strategic, tactical and operational dashboards
Not establishing company ontology and definitions for “single version of truth” culture
Lack of vision and not having a strategy; not having a clear organizational communications plan
Lack of upfront planning; overlooking the development of governance and program oversight
Failure to re-organize for big data
Not establishing a formal training program
Ignoring the need to sell success and market the big data program
Not having the adequate architecture for data integration
Forgetting rapidly increasing complexities with …volume, velocity, variety, veracity, and many more
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