Power BI's 3-tier reuse strategy can help extract valuable insights from an organization's data & reduce dependence on expensive data warehouse resources.
As healthcare leaders, you want to extract as much value as possible from your organization's data to gain insights that improve care. However, managing the rising volumes of healthcare data to achieve this is increasingly challenging. Power BI offers a pragmatic three-tier reuse strategy that can help overcome these hurdles. The reuse methodology mirrors the familiar “bronze, silver, gold” structure used in data lakehouses. Raw incoming data is stored in the bronze tier, processed into analysis-ready formats in the silver tier, and made available for analytics and AI in the gold tier. Power BI applies similar staging of data refinement from raw inputs through to impactful insights.
This blog explains the key components of this methodology to help you choose the right approach for your data needs.
Some may wonder why Power BI opts to use dataflows rather than SQL for its self-service reporting datasets. By handling data manipulation inside dataflows, overburdening source systems are avoided and access needs are reduced. Consider it creating versatile intermediate refined datasets, each serving distinct purposes. It strengthens data pipelines and decreases dependence on expensive data warehouse resources.
This reuse strategy offers some key advantages such as simplified architectures, flexible data refinement, and cost savings, allowing healthcare leaders to focus on vital insights rather than data infrastructure.
Reusable datasets serve as the core of a resilient data reuse strategy, effortlessly integrating with emerging Datamarts, and providing a robust infrastructure for efficient navigation through the intricacies of dataset preparation, Direct Query, aggregations, imports, data flows, and Datamarts. Picture them as core components in Power BI’s three-tiered strategy, ensuring a smooth and adaptable journey through the diverse scenarios presented in our decision-making toolkit.
When considering the appropriate approach, you can look at it from a different perspective:
Are you preparing data for visualization or self-service use?
Are you dealing with "big data" or needing real-time refreshes without delays?
Can you tolerate refresh delays for aggregated values?
If none of the above apply; it covers all other scenarios.
Are you performing ETL work reusable across multiple datasets?
Are you engaging in self-service data preparation to build a data product?
By enhancing analytical capabilities during digital transformations, Power BI allows for more efficient reuse of data, streamlined processes, and patient-centered insights. Taking purposeful steps to comprehend and utilize Power BI’s functions leads to improved decision-making capabilities and superior patient care. Healthcare leaders who strategically implement these tools across evolving organizational needs pave the way toward fluency in data analytics.
Explore our FREE eBook series on data reusability.
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