Successful Analytics Practice

How do you start and grow a successful analytics practice? In my experience it is best to start with a three (or multiples) member team and then grow it based on the push and pull of project pipeline. The role of the three (described below) differ but come together for a successful implementation.

1. Data Management Specialist 
• Should possess good data management skills and excellent SQL skills
• Should have worked in a data warehouse project 
• Should have worked with major database vendor products and should be exposed to Hadoop, MapReduce, HBase and Cassandra
• Responsible for creation of the data foundation layer 
2. Data Modeler
• Should have a statistical background and a flair for number crunching
• Should be able to create algorithms and data mining models.
• Responsible for exploitation of the data foundation layer
3. Business Analyst 
1. Should be able to interpret model output with business scenario and come up with actionable insight 
2. Should be able to work with Analytical COTS products and have basic SQL knowledge
3. Responsible for insight delivery from the exploitation layer

The three roles will come together for a successful data analytics project. The tool set choice will further determine the team composition but in essence the structure should be spun around the three core role.

Cost conscious companies unable or sometimes unwilling to build a team would argue and scout for the often difficult to find one resource who can do all three things - But to me that is not the right way to lay the foundation for growth in an emerging service area.