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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
o Kafka	
  Connect,	
  Kafka	
  (with	
  Zookeeper),	
  Cassandra,	
  Spark	
  
(with	
  Mesos),	
  Ubuntu,	
  Tableau,	
  Scala,	
  Python,	
  Java
Proof of Concept & Discovery Phase for Data Analytics Platform

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Proof of Concept & Discovery Phase for Data Analytics Platform

  • 1. 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 o Kafka  Connect,  Kafka  (with  Zookeeper),  Cassandra,  Spark   (with  Mesos),  Ubuntu,  Tableau,  Scala,  Python,  Java Proof of Concept & Discovery Phase for Data Analytics Platform