Case Studies
Data engineering, Power BI, and applied AI.
Real solutions across the Microsoft ecosystem: consolidating fragmented pipelines, automating Power BI reporting at scale, and building AI applications grounded in trusted data.
Data Engineering
Cutting pipeline maintenance by 90%
350 pipelines reduced to 33
A reporting environment had grown to roughly 350 individual data pipelines, each built by hand, so a single schema change meant hunting down duplicate logic scattered across dozens of files. Rebuilding the architecture around one metadata-driven design brought that down to about 33 pipelines, each extended through configuration instead of new code. A new data source that used to require its own pipeline build now plugs into an existing pattern in a fraction of the time.
Case study led by ClarusIQ's founder. No employer or client is named here.
Power BI Reporting
Automating a 625-report reporting library
625 reports standardized
A Power BI reporting library had grown to roughly 625 individual reports, most built and maintained by hand, each one drifting slightly from the others over time. Replacing that with a single automated build process meant reports no longer had to be rebuilt or patched one at a time, cutting the manual effort of keeping the library current down to a small fraction of what it used to take.
Case study led by ClarusIQ's founder. No employer or client is named here.
Applied AI
Building an AI-connected analytics application
Data-connected AI
An analytics application was built to connect AI directly to an underlying data model rather than treating it as a bolt-on feature, so its output stayed tied to real, defined data instead of operating as a generic, ungrounded chat interface.
Case study led by ClarusIQ's founder. No employer or client is named here.
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