1. Infastructure
1.1. Infrastructure as service
1.1.1. Inside Infosys data storage and computing power
1.1.1.1. IIP
1.1.2. 3rd parties data storage and computing power
1.1.2.1. Amazon Web Solution
1.1.2.2. Google cloud computing
1.1.2.3. Microsoft Azure
1.2. Infrastructure of client
1.2.1. In-house storage and computing power
1.2.2. 3rd parties data storage and computing power
1.3. Inside team Infrastructure
1.3.1. personal laptops
1.3.2. SQL server for internal use (150GB)
1.3.3. Teleconference / Brain Storm / Meeting room
2. Roles to cover
2.1. Database Manager/Developer / Data Cowboy
2.2. Data Scientist / Advanced analyst
2.3. Visualizer / Data Artist
2.4. SAP Data Warehouse Expert / Domain Experts
2.5. Project coordinator / Scrum Master
3. Technology / Software
3.1. Data Service
3.1.1. MSSQL Server 2016
3.1.2. AWS Redshift Account
3.1.3. Microsoft Azure Account
3.1.4. Hadoop Environment
3.1.5. TERADATA Environment
3.1.6. MSSQL
3.2. Analytical Capabilities
3.2.1. Close to data (server solutions)
3.2.1.1. R Server close to data (Revolution R)
3.2.1.1.1. sdfsds
3.2.1.2. H2O
3.2.1.3. Python
3.2.1.4. Spark / Scala / MapReduce
3.2.2. On laptops
3.2.2.1. Office
3.2.2.2. Rstudio + R
3.2.2.3. Visual Studio
3.2.2.4. MSSQL Management Studio
3.3. Vizualisations
3.3.1. Tableau Server + Tableau Development
3.3.2. Spotfire
3.3.3. Microsoft Power BI
3.3.4. SAP Lumira
3.3.5. R Shiny Server
3.4. Process Flows and presentations
3.4.1. JIRO
3.4.2. Prezi
3.4.3. PPT
3.4.4. Visio
3.4.5. Mindmeister