AUTHORITY - Baseball Infographic

Head of Product, Major Healthcare Analytics Organization

Your Challenges

Many enterprises look at modern data-driven companies like Amazon or Google and see their own future. Companies have undertaken a long-running effort to consolidate data stores, implement automated data analytics solutions to successfully update processes (aka pipelines) and now have rationalized data warehouses, lakes, lakehouses, etc. While this represents real progress, it is only a start on the path to becoming a data analytics driven organization.

Implementing a comprehensive data analysis effort against rationalized data is where the real payoff occurs. This analysis is performed with varying levels of effort and sophistication. Enterprises are analyzing their data using approaches such as:

  • Implementing data visualization capabilities (Quicksight, Tableau, etc.) 
  • Using business intelligence platforms (PowerBI, Oracle Analytics Cloud, etc.) 
  • Applying AI and machine learning to data analysis (Databricks, etc.) 


Our Solutions

Infinitive has vast experience helping companies implement data analytics solutions to enable them to analyze their data more effectively. We have performed projects where we collaborate with organizations to choose and implement data visualization tools, configure business intelligence platforms, and implement AI-based solutions to clients’ data analysis needs.

How We’ve Done it

Infinitive understands that becoming a data-centric enterprise is a process. We help our clients organize their data so that it can be analyzed, visualize their data by creating platforms which allow “citizen data scientists” to perform data analytics, and implement sophisticated AI-based analytics. It all starts with our data transformation methodology.

At the highest level of the data transformation methodology, Infinitive structures the effort into four main phases:

  1. Strategy – review current state, establish a roadmap, and prioritize deployment.
  2. Foundation – establish governance / technology frameworks, launch Proofs of Concept 
  3. Operation – build out the infrastructure for modern data management at scale.
  4. Transformation – implement the data analytics, AI and ML that drive business benefit. 


Each of these major phases is decomposed into a lower-level set of actions. Each of the lower-level actions is decomposed again into atomic tasks along with clear deliverables to be produced. The result is a playbook that can be followed allowing for:

  1. Faster project start-up, easier staffing, and assignment of tasks. 
  2. Less rework from missed tasks and misunderstood dependencies. 
  3. Improved cohesion from one task to the next. 
  4. Accurate and early assessment of costs and benefits. 
  5. Quicker time to value. 

Why Work With Infinitive

Infinitive’s data analytics solutions experts are dedicated to improving your organization’s collection, movement, storage, use and analysis of data. As an AWS Advanced Consulting Partner, Snowflake Partner, and Databricks Partner we help companies develop a strategy for becoming a data driven enterprise. We also help with the implementation of that data-centric strategy.