What KPIs should you use to measure the success of your data warehouse?

1 Data Warehouse Performance

Monitoring the performance of your data warehouse is essential to ensure it can handle the volume and variety of data you need to store and process. You can use KPIs such as load time, query time, availability, and utilization to measure its speed, efficiency, and reliability. Load time measures how long it takes to load data from the source systems into the data warehouse. Query time measures how long it takes to execute queries and retrieve data from the data warehouse. Availability evaluates how often the data warehouse is up and running without any failures or downtime. Utilization assesses how much of the data warehouse resources (such as storage, memory, CPU, etc.) are being used and how efficiently.

2 Data Warehouse Quality

When assessing your data warehouse, it is important to ensure that it contains accurate, consistent, complete, and relevant data that meets the expectations and requirements of your users and stakeholders. To measure the quality of your data warehouse, you can use metrics such as accuracy (how well does the data match the source systems and real-world events?), consistency (does the data conform to established standards and definitions?), completeness (how much of the data needed to support analysis and reporting is available?), and relevance (does the data align with current and future business needs?).

3 Data Warehouse Usability

Measuring the usability of your data warehouse for your users and stakeholders is an important KPI. To ensure that your data warehouse is easy to access, understand, and use for its intended purposes and audiences, you should track metrics such as accessibility, understandability, usefulness, and satisfaction. Accessibility refers to how easy it is for users and stakeholders to connect to and access the data warehouse from their preferred tools and platforms. Understandability measures how easily users and stakeholders can comprehend the structure, content, and meaning of the data warehouse. Usefulness looks at how well the data warehouse supports analytical and reporting needs. Finally, satisfaction evaluates how pleased users and stakeholders are with the functionality, performance, quality, and value of the data warehouse.

4 Data Warehouse Business Impact

A fourth KPI for your data warehouse is the business impact it has on your organization. You want to make sure that the investment and effort you have put into it is worth it and yields tangible and intangible benefits. To evaluate your data warehouse, you can look at metrics such as ROI, alignment, innovation, and competitive advantage. For example, how much return on investment have you gained from your data warehouse in terms of increased revenue, reduced costs, improved efficiency, or enhanced customer satisfaction? Additionally, how well does your data warehouse support the strategic objectives and priorities of your organization? Moreover, how much has your data warehouse enabled or facilitated new insights, opportunities, or solutions for your organization? Lastly, how much has your data warehouse given you an edge over competitors in terms of market share, customer loyalty, or brand reputation?

5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?