Data Warehousing

The backbone of any data analytics initiative

The key to accurate decision-making lies in your ability to see the complete picture. You can't make the right decision without the right insights at the right time.

Your organisation has the raw data it needs to establish accurate decision-making, but this information is scattered across enterprise silos, locked away in operational systems waiting to be mined and interpreted for deeper insights.

A data warehousing capability collects this data from disparate data sources, then aggregates and processes it to provide analyses and access points that serve the insatiable demand for business intelligence and data analytics.

It’s fair to say that a data warehousing strategy provides the keystone of a decision-making infrastructure.

But creating a data warehouse is no mean feat.

Delivering on the goals of a complete data warehousing strategy

“A purely technology-led approach to [your data warehouse] will have a far higher failure rate than a use-case and requirements-led approach.”

– Gartner, The Practical Logical Data Warehouse

Your data integration consulting needs to create a shift in how the business is informed and directed by accurate and timely insights.

Therefore, we start by viewing every data warehousing initiative through a business strategy lens before analysing how the data warehouse needs to align with an underlying data strategy.

Once we agree on ‘the north star’ for your data warehousing business and data strategy, we can start to consider infrastructure designs that align with your current and future needs.

It’s natural for organisations to feel overwhelmed at the possibilities of modern data warehouse architecture. Since Oakland’s inception 35 years ago, we’ve watched the data warehouse industry expand into the seemingly limitless variations available today.

Historically, many organisations centralised their analytics in a single warehouse architecture. Today, data and analytics leaders increasingly need to deliver a data management infrastructure that can flex and adapt to the type of diverse analytical needs that are failed by a ‘central repository’ approach.

The Oakland difference

Data warehousing requires a broad array of disciplines that are not always readily available, even within large organisations. And to compound the challenge, the data warehousing technology landscape is rapidly evolving every year.

This need for an experienced mix of technology, data, operational, process and data quality expertise leads many organisations to our door.

When helping you navigate the next generation of data warehousing (and the many hub, mart, lake and lakehouse alternatives), we strive to adopt the role of ‘impartial guide’.

Our goal is to arrive at a workable data warehouse solution underpinned with a deep sense of pragmatism – instead of a blinkered devotion to a specific tool or vendor.

Next steps

The first step is to arrange a short discovery call with one of our principal consultants to discuss your challenge.

We’ll share our past expertise and approach, then examine your data warehousing requirements and suggest a way forward, which typically involves a small, rapid pilot, to demonstrate immediate value.

Get in Touch

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