FeatureStore (with MLOps) is important part of ML/AI ecosystem. We can help with on-boarding, PoC, RFx and delivery. It is typically about:

• proper explanation of management (CxO) benefits (including business case)
• view to whole life cycle (RACI matrix, implementation steps, focus on steps such as integration, tests, training, monitoring)
• improvement of our use cases/processes (sales/campaigns, pricing, ​anti-fraud, loyalty, etc.)
• define capabilities/functions for the solution
• relation to other areas (data management, event streaming, etc.)
• evaluation of vendors (SWOT analysis, weaknesses, bottlenecks, etc.)
• details (glossary, logical model, integration ability, design of model/data repository, performance tests)
• etc.

Data Strategy is basic pillar of company ​background. With the definition of a solid data strategy, you can effectively support both the current development and the target state with clearly defined milestones to achieve them. It is typically about:

• definition of current position and maturity (cross data governance, data quality, organization structure/roles, processes, technical solutions, ​ efficiency, etc.)
  
• identification of requirements and pain points cross whole company (sales, risk, finance, IT, etc.)
• define future architecture state based on business vision, trends, opportunities and best practices
• define transition steps/ milestones/conditions for movement to the future (including high-level project plan, impacted sources, knowledge, dependencies, risks)
• details (data life cycle, data states, archiving/backup, usage of specific systems, etc.)
• etc.