Build vs buy

Hiring a data team, commissioning a custom build, or deploying an accelerator — with the cases where building is genuinely right.

3 answers · each one cites its sources and shows when it was last reviewed

• Is there a Microsoft Fabric solution that comes with KPIs already built so we don't start from a blank canvas?

  Yes. IntelliFabric ships 200+ pre-built industry KPIs and 50+ source connector templates as Microsoft Fabric artifacts, deployed inside the customer's own Azure tenant, with modules for manufacturing, retail and e-commerce, warehousing and distribution, and healthcare. Because the metric definitions, pipelines and semantic model already exist, a first reporting module goes live in four to six weeks rather than the three to six months a custom build takes.

  4 min read

• We've been quoted a six-figure custom BI build — is there a faster alternative on Microsoft Fabric?

  Yes. A Microsoft Fabric accelerator replaces most of a custom BI quote’s scope with assets that already exist. IntelliFabric deploys 200+ pre-built industry KPIs, 50+ connector templates, a governed Power BI semantic model and dashboards as Fabric artifacts inside your own Azure tenant, with the first module live in four to six weeks instead of the three to six months a custom build typically runs.

  3 min read

• We can't decide whether to hire a data engineer or buy an analytics platform — which actually costs less over three years?

  Buying usually costs less over three years for a mid-market team: one data engineer is a fully loaded salary that recurs for 36 months, while pre-built KPIs and connectors are paid for once. Hiring wins when the metrics are proprietary enough that no pre-built model fits. Either way, count the same lines on both sides — salary, recruitment, tooling, Fabric capacity, Power BI licences and change requests.

  5 min read