Data Strategy

create a single source of truth a upright funnel on plinth

Single Source of Truth: Proven Guide to Avoid Costly Errors

A single source of truth is agreed in every boardroom and implemented in almost none, because the hard part is not the platform but deciding which system wins an argument. This guide gives you the working: what the term means once you have to build it, how to choose the first domain, the four architecture patterns and what each really costs, the matching and survivorship rules that settle disputes, the integration layer that keeps the record current, a costed ninety-day plan, the four measures that prove it worked, and the mistakes that quietly undo the whole thing in year two.

Read more
master data management business case a cube assembled from smaller blocks

Master Data Management Business Case: Best Proven ROI

A Master Data Management business case is rejected far more often than the problem deserves, because the paper prices a hub licence, omits the stewards who run it forever, and never says where the recovered hours went. This guide gives you the working: a costed investment schedule including the lines most models drop, the five benefit streams that carry almost every case, how to price an hour without double counting, the payback, NPV and sensitivity maths finance expects, a fully worked three-year model for a 400-person company, the benchmarks worth quoting, and the specific errors reviewers use to reject a funding request.

Read more
data warehouse vs data lake vs lakehouse a blank signpost three arrow boards

Data Warehouse vs Data Lake vs Lakehouse: Proven Guide to Avoid Costly Mistakes

Data warehouse vs data lake vs lakehouse is the architecture argument that eats the most meeting time and produces the least clarity. All three will store your numbers and feed a dashboard; the difference appears eighteen months later in the size of the bill and the number of people it takes to run. This guide compares the three on the factors that actually move the answer: what each architecture is and when you are forced to agree what the data means, how the bill is genuinely built once compute and salaries are counted, the governance and UK GDPR duties that do not change whichever you pick, the skills and monthly run effort each demands, which workloads belong where, realistic migration paths with the failure mode of each, and a weighted scoring framework you can complete with your own numbers.

Read more
CHAT