In order to have data on the processes we’re trying to improve, we need somewhere to store that data.
Paper documents (time-clock punch cards, warehouse manifests and fulfillment docs, and manual ledgers) and spreadsheets have historically been used for the storing, organizing, analyzing, and reporting steps, and many organizations still depend on these basic tools for data sources for BI.
But many of these manual storage methods have been replaced by automated systems that store their data in digital format such as flat files or relational databases, such as Microsoft SQL Server, IBM DB2, Oracle Database, Amazon RDS, and Google’s Cloud SQL.
This means that modern BI tools, which either have native integrations to these data stores (in the case of relational databases such as Oracle or Microsoft SQL server) or have application programming interfaces (APIs) that support communication with databases, production machinery and devices, and any other automated system that produces data and also has an API, can be configured to pull the data needed to produce your BI.
And as Cloud-enabled databases and Cloud Computing platforms have become more available, data can be pulled from multiple Cloud-connected solutions and Internet-of-Things-enabled systems to enable more informed business decision-making. (Eric Knorr, Editor-in-Chief at InfoWorld, has written a solid piece on “What is Cloud Computing”, describing the major pieces and the major players.)