Your company realizes that analytics is a competitive differentiator, and business users have managed to operationalize analytics within the organization. Finding new sources of data (even outside the established company ones) and new tools to further automate the time-to-analysis, is actively encouraged and supported within the organization (thinking outside the box). Analytics culture is growing and becomes part of the company’s DNA. Your organization has most likely established mature data and analytics teams (data engineers, data scientists, MLOps) and there is a Chief Data Officer or Chief Analytics Officer on the company board.
Data integration supports modern tooling and there is a coherent architecture which your company is able to easily scale. Employees can easily access data assets company wide, being provided with data catalogues (what data is available where, what are the definitions, data metadata) and are able to trace the Data Lineage (where does the data come from). At this stage organizations are starting to invest more heavily into developing new ML/AI capabilities, and understand the data/analytics life-cycle which requires continuous investment.