Define and articulate Big Data Solution requirements, scoping and planning
Create a conceptual high-level view of the solutions by defining the components of the solutions and the scope
Top-level logical design for the big data solution including the data integration system, data repositories, the analytics system and the access system.
Deliver the final, detailed set of blue prints for the building the big data solution
Construct the big data solution/environments including the data integration system, the data repositories, the analytics system and the access system
Implement the big data solutions in the productions environment and deliver to the user community. Training and knowledge tranfer
Proof of Concept Options
Configuration
On premise enterprise, cloud computing environment
System requirements
5 server minimum, 16 GB, 2 TB of storage OR Cloud computing – additional cost for cloud service
What does POC consist of?
Access requirement
Read only access to customer target data
User permission
Provide access to the servers
Resource requirement
DataReady resources
One DataReady Architect, one Big Data Subject Matter Expert
Time line- 160 hours
Successful Pilot/POC criterion – example
Success criterion based on visualization of the following KPIs
1. Operational device / machine log
2. Business Application Logs
3. External Feeds
4. Corporate feeds / Rich Site Summary (RSS)
5. Internet of Things (IoT)
6. Acceptance for roll to production