BI Cost & Capacity Optimization

Cut 20-25% off your BI bill in 90 days.

Datalogz finds the duplicate datasets, unused reports, and runaway refreshes silently inflating your Power BI, Fabric, Tableau, and warehouse spend, then automates the cleanup.

Read-only metadata No data movement ROI modeled on the first call

See your savings opportunity How it works

BI 360 Overview, asset counts by connector and BI health Sankey

The problem

Your BI environment is leaking money in places nobody can see.

Enterprise BI bills aren't getting bigger because companies are getting bigger. They're getting bigger because nobody is removing what stopped mattering two years ago.

Every BI environment we plug into is hitting the same wall.

A Fortune 500 consumer packaged goods enterprise we work with was spending six to seven million dollars a year on Power BI alone, spread across more than seventy premium and Fabric capacities. About ten of those capacities were under real load. The rest had been spun up for a project, a team, or a moment in time, and nobody ever turned them off.

The same source tables were being ingested into Power BI seventy or eighty times a day, by different teams, each thinking they owned the only copy. Their compute bill kept climbing. So did their bills with the warehouses underneath.

This isn't unique to them. It's what happens in every Power BI, Fabric, Tableau, or Sigma environment as it ages:

01Unused reports keep refreshing on schedule for years after their owner has left the company.
02Semantic models pull the same Snowflake table over and over because no one has visibility across workspaces.
03Capacities oversaturate, throttle, and pressure the company into buying more capacity, when the real fix was removing what shouldn't have been there.
04Premium and Fabric SKUs get rubber-stamped at every renewal because nobody can prove how much of the capacity is actually being used.

Most BI teams already know they have waste. What they don't have is a way to find it, quantify it, and remove it without breaking something the business depends on.

“

More than 20-25% of savings.

FINANCE LEADER · FORTUNE 500 CPG · REACTING TO DATALOGZ'S MODEL AGAINST THEIR $6-7M ANNUAL POWER BI SPEND

How Datalogz solves it

A read-only metadata layer for your entire BI stack.

Datalogz connects to your BI stack in under thirty minutes and instantly maps every asset, every report, dataset, semantic model, refresh schedule, and capacity, across Power BI, Fabric, Tableau, Sigma, Qlik, and beyond.

Step 01

Plug in.

Step 02

See your waste.

Step 03

Automate the cleanup.

Every unused asset.

Reports and datasets that are still refreshing on schedule but haven't been opened in 60 days or more.

Every duplicate semantic model.

The same source data being recomputed multiple times across workspaces, with similarity scores so you know what's safe to consolidate.

Every chronic refresh failure and capacity hotspot.

What's burning your CUs, when, and why: the dataset taking 80 minutes to refresh before it fails.

A dollar-value business case.

Projected savings across Power BI compute, capacity rightsizing, and downstream warehouse spend, modeled against your actual contract.

Then Datalogz automates the cleanup.

Every action is tracked against the savings model, so finance sees realized value, not just projections.

✓Bulk archive unused assets ✓Schedule consolidations ✓Pause runaway refreshes ✓Right-size capacity SKUs

Inside the Control Tower

Every asset, every refresh, every dollar, in one place.

Four views your team will live in. From the executive summary that lands in the CDO's inbox, to the similarity graph that maps your duplicates at a glance.

Power BI · 4,419 datasets 5,262 reports Sankey: healthy vs unhealthy

Executive Summary auto-generated daily from BI 360 signals

Daily delivery PDF export Refresh health · Adoption · Cost

Team Inventory Overview with semantic models and alert categories

2,016 semantic models Orphaned · Unused alerts Per-team filtering

BI Similarity Report Clusters visualization

Score >= 80% Workspace grouping Similarity, 14+ parameters

A closer look · Fortune 500 CPG

$6-7M a year on Power BI. 77 capacities. Nobody could defend the spend at renewal.

The buyer was the finance partner sitting across from the BI platform owner. Datalogz scoped a proof of concept on just ten of those capacities. Here is what we surfaced in the first scan.

Power BI compute

$900K-$1.5M

in annual savings from Power BI compute optimization alone.

Warehouse cleanup

$1.5M-$3M

additional 24-month savings from cleaning up the warehouse compute beneath.

Capacities retired

2 of 77

specific regional capacities sitting half-unused, identified ready to consolidate.

Report footprint

39K → leaner

a path from 39,000 reports trending toward 70,000 next year, down to a governable footprint.

PoC scope ·
10 of 77 capacities

Day 0, connect

Day 14, first scan

Day 30, business case

Day 90, realized savings

What customers see

Realized value. Not a maturity score.

Every action Datalogz takes is auditable, reversible, and tied to a dollar figure on your contract.

20-30%

BI Compute

Reduction in BI compute spend, modeled in the first scan and validated against your actual contract.

Hundreds

Refreshes paused

Of unused refreshes paused, without disrupting a single piece of active reporting your business depends on.

Real $