Proof of Concept & Discovery Phase for Data Analytics Platform

July 6, 2017 at 12:13 pm Leave a comment

The client is a large, healthcare-­‐focused strategic media planning and buying group of several agencies. The group offers media planning for different channels by analyzing existing data available within each agency. They wanted to develop an analytics platform to improve executive decision-­‐making across the agency.

To help our client be strategic about creating such a platform, we engaged in a Proof of Concept (POC) and Discovery Phase to do the following: (1) identify how feasible it would be to use existing agency data to effectively analyze and measure performance and trends, and (2) understand and document the business and technical requirements for developing an analytics platform.

Business Benefits:

  • We recommended a big data-­‐based solution with a clear path for execution. This approach will help our client do the following:
  • Attain business vision of scalability, maintainability and sustenance
  • Manage data traits like volume, variety and historical data persistence
  • Accommodate the future vision of predictive modeling, taking into account the growth of data volume

Engagement Deliverables


Key Highlights:

Proof of Concept (2 months with 2 resources)

During this phase, we performed following activities:

  • Defined success criteria for POC
  • Extracted data from multiple data sources
  • Cleaned up data and ingested it into the data warehouse
  • Classified data as qualitative and quantitative
  • Validated data integration business rules to secure and isolate data access
  • Performed data analysis across agencies (brands) and created custom reports

Discovery Phase (6 weeks with 1 onsite and 2 offshore resources)

  • Gathered and documented key business and technical requirements
  • Understood different stakeholders’ visions and business goals
  • Identified data sources for the analytics platform’s data warehouse
  • Examined and determined expected data volumes and the type of data to be analyzed
  • Defined a recommended solution based on the aforementioned activities
  • Defined the recommended technology stack

Proposed Technologies

  • Kafka Connect, Kafka (with Zookeeper), Cassandra, Spark (with Mesos), Ubuntu, Tableau, Scala, Python, Java

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