Enterprises from every industry and scale are working to leverage data to achieve their strategic objectives—whether they are to be more profitable, effective, risk tolerant, prepared, sustainable, and/or adaptable in an ever-changing world. An enterprise’s data maturity must grow at pace with the business and its needs to achieve agility and resilience today—otherwise it will be hamstrung, or even worse tripped up, by limited capabilities. A mature data warehouse is the strongest component of data maturity.

To be able to leverage a data warehouse, it must be efficiently accessed, integrated, governed and effectively managed. As consultants and analysts, we encounter organizations all the time who struggle with their data warehouse.

The technical debt that has accumulated from years of workarounds and gap-fixing existing warehouses may seem too “expensive” to rip and replace with a more capable modern data warehouse. Plus, there are other enterprise priorities, for better or worse. However, the demand for a mature, modern data warehouse is too strong to ignore regardless of what current state is or what enterprise priorities du jour are.

At the least, you should understand where you may have some gaps from expectations and modernity in your data warehouse, which can help you budget and scope your project better.

These days many believe the best vessel to be a data lake/cloud storage (not necessarily in data page/relational-like format). And many are finding ways to join the relational database with the lake as a “lakehouse,” treating the data lake as external tables. This is great, but I believe no reference analytic architecture is complete without database technologies, despite the inclusion of the data lake, and the lakehouse concept, in the architecture. The characteristics of so-called ‘big data’– larger amounts of data with fluent ingest, but with a smaller, science-based user population – make the data lake appropriate as well, but there are differences in the access profiles of relational and cloud storage that make both appropriate in the actionable future we build for.

At the event on May 19, Astera will launch the Astera Data Warehouse Builder, with a focus on helping enterprises build or rebuild their data warehouse(s) and marts, or get them under control so the data warehouses and marts are mature and the enterprise can focus on using them and building around them instead of suffering with them. Could a data warehouse built in one-hour from scratch be an improvement on an existing data warehouse or mart? Come find out what it’s all about.

I will be speaking at the event about the data warehouse today and its continued relevance the enterprise. I hope to “see” you there.

McKnight Consulting Group