Jake Watson

Should you use Data Lakehouse instead of a Data Warehouse and / or Data Lake? 

Should you use Data Lakehouse instead of a Data Warehouse and / or Data Lake?  Intro  When using your Data Platform to improve your Business Intelligence with useful dashboards and reports, you’ll more than likely want to use a Data Warehouse. Add on your data science builds, and storing your raw data cheaply, plus adding a…

Should you build or buy your data platform?

“Build Versus Buy” is More a Scale of Options than a Binary Decision As consultants, we’ve been involved in helping our clients to decide which is the best software to invest in (or not invest in some cases). This is quite a responsibility as we are putting our reputation in the hands of a vendor,…

Why Invest in Data Quality?

This can seem like a rhetorical question: you should always invest in Data Quality! But we are still not investing enough: surveys show Data Quality issues are increasing in most organisations and on average, take up 34% of a Data Engineers time instead of them creating value by adding new features. This increases to 50% in large…

How to create a secure Azure Data Platform

There are many methods you can use to secure your data platform and the data contained within it within Azure. The security controls that will be most effective for each data platform differ based on the usage of the platform, the data sources for the platform and many other factors; Having a holistic view of…

What are the challenges of building a data platform?

Before we share our best thinking around data platform delivery, it’s worth shining a light on some of the challenges you can expect along the way so you can be well prepared. Introducing a modern data platform to the enterprise is not easy.  Challenge 1: Excessive Tech-Centric Focus  It’s easy to think of your Data…

What is a data platform?

Cloud-native platforms are an essential tool to help accelerate the execution of enterprises’ digitisation plans over the next 2-3 years. They are essential because improved access to cloud services enables the introduction of modern technologies with less operational burden than with legacy systems. They will expedite and facilitate the creation of innovative business solutions. Adopting…

Does Microsoft Purview solve the Data Governance Challenge?

Microsoft Purview Data Governance for the cloud, on-premise, multi-cloud and office 365 workloads. Introduction Most organisations are exploding with data that has been collected, transformed, and reported on, but this data is often not well-tracked as the organisation becomes more data-driven, increasing two pain problems that have been growing for the last few decades: How…

Taming your data assets with Databricks

Safely, securely, and efficiently handling data at any scale is challenging. Here at Oakland, we’ve had years of experience helping complex organisations tame their vast data assets to draw meaningful insights from them. These years of experience and the fact we are passionately tech-agnostic enable us to recommend the right tool for the job. One…

Prefect: Should you utilise the next generation of data pipelining software?

What is data pipelining, and why does it matter? Data pipelining, or orchestration is an everyday activity performed by companies to move their data from one place, likely the primary storage location, to another, such as a cloud-based data lake, often including transformations during this process. Whilst this is a standard operational activity, the number…

Replicating Data Warehouse with Databricks Lakehouse

Introduction In a recent post, we outlined what a Databricks Lakehouse encompasses and why you may want to utilise one rather than a Data Warehouse and/or Data Lake. Following that introduction, this post will walk through an example use case, including code, for how the Databricks Lakehouse replicates some common warehousing patterns while having the…

The Pro’s and Con’s of using Data Lakehouse

When using your Data Platform to improve your Business Intelligence with useful dashboards, and reports, you’ll more than likely want to use a Data Warehouse. Add on your data science builds and storing your raw data cheaply, plus adding a Data Lake just for good measure, and the costs soon start adding up. Running both…