Data Analysis & BI

Data Analysis & BI

One source of truth. Decisions you can defend.

$12.9M

Poor data quality costs organizations at least $12.9 million a year on average — in decisions made on bad numbers, effort spent reconciling them, and reporting no one fully trusts.

Source: Gartner.

When two reports disagree and leadership decides on gut feel, the problem isn’t the dashboard — it’s the data beneath it. Helix Quantum Partners builds the reconciled data foundation, the governed pipelines, and the Power BI reporting that make performance measurable and decision-ready.

When to bring one in

When data needs to become decision-ready.

Data-rich but insight-poor

You have the data but can’t turn it into decisions.

Moving off spreadsheets

Reporting needs to graduate to managed business intelligence.

Reports that disagree

No single, trusted source of truth exists yet.

Proving ROI

You need to show, with numbers, what an initiative returned.

The recurring gaps & the difference in practice

Each gap below is common, costly, and avoidable with HQP Data Analyst.
Which ones do you recognize?

The gap
In practice
Two reports on the same thing disagree.

One reconciled source of truth, tied back to the systems.
Leadership decides on gut feel.

KPI dashboards that make the data decision-ready.
We live and die in spreadsheets.

Governed Power BI and SSRS with self-service.
We don’t trust our data quality.

Validation, quality controls, and governance standards.
We find out about problems too late.

Operational-trend monitoring and early-warning reporting.
We can’t prove the ROI of our initiatives.

Before-and-after benchmarking that shows value realized.

Discipline

A repeatable, seven-step method.

The work runs to a defined method aligned with dimensional data-warehouse design (Kimball) and data-management standards (DAMA-DMBOK) — so the reporting is trustworthy and the model holds up as you grow.

  1. 1
    Define the questions.

    Establish the KPIs and the decisions the reporting has to support.

  2. 2
    Profile the sources.

    Inventory the data, assess quality, and find where systems disagree.

  3. 3
    Model the data.

    Design a scalable warehouse / mart that absorbs new sources cleanly.

  4. 4
    Build the pipelines.

    Develop ETL that consolidates and reconciles disparate sources into one source of truth.

  5. 5
    Establish governance.

    Set ownership, stewardship, validation, and quality standards so the data stays trustworthy.

  6. 6
    Deliver the reporting.

    Build Power BI and SSRS dashboards with self-service and scheduled distribution.

  7. 7
    Analyze and forecast.

    Run root-cause and anomaly analysis, monitor trends, and benchmark before-and-after ROI.

See where this fits in HQP’s five-stage method →

Tangible, reviewable, reusable

Every engagement leaves a governed data foundation.

Every engagement leaves a governed data foundation and reporting leadership can trust, audit, and build on — not another spreadsheet that leaves with its author.

Single reconciled source of truthPower BI & SSRS dashboardsKPI & operational-trend reportingScalable data model & warehouse/martETL pipelinesData-quality controlsData-governance standardsRoot-cause, anomaly & forecast analysis

The return

Where it shows up — in decisions, trust, and analyst time.

Numbers that agreeOne reconciled source of truth ends the report-vs-report debate.

Decisions on evidenceKPI dashboards replace gut feel.

Analyst time backAutomated distribution ends manual report assembly.

Early warningTrend monitoring surfaces problems before they compound.

Scales cleanlyThe model absorbs new sources without a rebuild.

Provable ROIBefore-and-after benchmarks show what initiatives returned.

Works with

Business Analysis
Systems & Process
Project Management

Turn data you can’t trust into decisions you can defend.

Free consultation

No charge, no commitment. We reply within two business days. How an engagement works →