Purpose
This chapter defines the Agency’s enterprise-wide initiative to provide a consolidated, secure gateway to the wealth of CMS data where users can leverage business intelligence (BI) software tools to access, manipulate, analyze, and share integrated data and then create information they need to ask business questions and derive accurate, clear answers. This chapter articulates the BI guidance and standards that should be used by CMS and CMS Contractor partners for all CMS Processing Environments.
While CMS supports all of these tools, CMS prefers that project teams consider these factors:
- Use case
- Cost at scale
- Ability to reuse developed capabilities for the given data source(s)
Scope
The concepts, strategies, and guidelines discussed in this chapter align with the CMS Business Intelligence Strategy, Version 1.5, December 9, 2008 that prescribes the BI tools and processes forming the conceptual framework of the BI environment. This chapter inherits the strategies, guidelines, and capabilities from the CMS Business Intelligence Strategy, Version 1.5, December 9, 2008; CMS Cognos ReportNet Guidelines, March 3, 2006; and CMS MicroStrategy 8 Guidelines, March 16, 2006.
This chapter is also updated with content from the Technical Review Board (TRB) Research Spotlight Data Analytics & Business Intelligence (BI) Tools, May 12, 2023.
This chapter provides architecture guidance, incorporates best practices, and defines the infrastructure of the BI Environment using components compatible with the CMS TRA. It includes the BI Reference Architecture and services that form a blueprint for helping CMS build BI solutions. This document represents the CMS Business Intelligence Reference Architecture in two virtual views—the “Business View” and the “Technical View.”
Why Data Analytics & BI is Important
Data is an asset, and Analytics/BI extracts value from it. Both data analytics and BI are used interchangeably, with BI being the generalized term encompassing analytics, but there are some distinctions. Data analytics is the process of primarily collecting, inspecting, cleansing, transforming, storing, modeling, and querying data. Its goal is to produce insights that inform decision-making. There are 4 main types of data analysis:
- Descriptive: Informs that an event “A” occurred
- Diagnostic: “A” occurred because of an event “B”
- Predictive: What could be the future of “A” if “B” continues
- Prescriptive: What is the best course of action?
While BI provides Descriptive and Diagnostic and can be Predictive based on history only, it doesn't take future trends into consideration. Thus, BI provides a progress report, while data analytics also provides data-driven insights into what are the prescriptive changes to progress.
CMS applications collect and store vast amounts of data. When this data is presented visually in a graphical form, it is easier to interpret, understand, and quickly observe data patterns than to query the data and parse the results. This is the power of data visualization and the primary reason for teams to use it. Data visualization is an integral part of BI, and it helps teams to visualize their data and interact with them. This makes it easier for business users to spot patterns and trends in a much better way. Here are some of the reasons why Analytics and BI are crucial for any application.
- Ability to gain customer insights
- Greater visibility on business operations
- Get actionable insights
- Improved efficiency across the division / group / center
- Real-time data availability
- Better marketing efforts
- Gives the business a competitive advantage
Hence, it is beneficial for CMS Systems and Business Owners to analyze the need for data analytics and BI and to look closely at the various tools used at CMS.