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:
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.
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:
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: