Analytics Platform Training Series
Initial basic analytics platform training is included with any Health Catalyst Analytics Platform installation. Depending on organizational needs, however, more extensive or customized training may be desired. The analytics platform training series teaches data architects and business intelligence (BI) developers how to use Health Catalyst’s tools and processes, so they can customize and maintain their own analytics applications. Participants will learn about basic use cases for each of the platform’s tools; they’ll leave knowing how to interact with their data warehouse to drive outcomes improvement.
What topics are covered?
Sample topics include
- Source Mart Designer (SMD)
- EDW Console
- Subject Area Mart Designer (SAMD)
- Instant Data Entry Application (IDEA)
Who should attend?
Data architects, data engineers, data analysts, and other individuals who will be using Health Catalyst platform tools to interact with their enterprise data warehouse (EDW) are encouraged to attend. It’s important that all participants are familiar with SQL and data warehousing concepts.
Preview Some of the Lessons and Principles
Do you want a better idea of what we’ll cover?
Below we’ve included a sample of articles to give you a better idea of what we’ll teach and what you’ll learn. Feel free to review and share with others.
When creating a healthcare data warehouse, typically time-to-value will take one to two years. But using our data warehouse tools, we’ve reduced that time to months. Usually a lot of manual labor goes into extracting data from EHRs or other sources systems. Metadata mapping helps by indicated where data is located in each system. However, that mapping process is also typically time-consuming and onerous. Using Health Catalyst’s Source Mart Designer, the mapping is automated and ETL scripts become a cinch. Then we use our Atlas tool to make search for specific data easier and more intuitive.
A key feature of effective analytics infrastructure in healthcare is a metadata-driven architecture. In this article, three best practice scenarios are discussed:
- Automating ETL processes so data analysts have more time to listen and help end users
- Using a metadata repository to enhance data literacy among users and improve trust in data, thus enabling data governance policies
- Improving turnaround time for data analysts who support frontline staff who, in turn, monitor interventions based on evidence-based medicine that is constantly changing
The article unravels the components of the metadata-driven architecture as part of an overall analytics platform. Learn the methodology for creating faster data results, generating speed to value, and realizing systemwide analytics adoption.
The Changing Role of Healthcare Data Analysts—How Our Most Successful Clients Are Embracing Healthcare Transformation (Executive Report)
The healthcare industry is undergoing a sea change, and healthcare data analysts will play a central role in this transformation. This report explores how the evolution to value-based care is changing the role of healthcare data analysts, how data analysts’ skills can best be applied to achieve value-based objectives and, finally, how Health Catalyst’s most successful health system clients are making this cultural transformation happen in the real world.