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DataOps Suite
The complete platform
Platform Overview
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DataOps Suite

Data Quality and Agentic AI platform that validates, reconciles, scores, monitors and remediates data from ingestion to BI and AI.

Why one platform

Agentic AI-powered test and rule creation
Agents generate data quality rules, validation tests and SQL from prompts, with your approval.
Data quality score per dataset
Shows the current score, what changed since the last run and the failing records behind it.
Validation and observability inside the pipeline
Every load is compared with its source, transformations are tested against business logic, and freshness, volume and schema changes are monitored.
Reports that match the source
Dashboard figures are compared with the source data behind them before users see them.
Test data without real records
Synthetic data that mirrors production replaces sensitive records in test environments.
Quality gates for releases
Pipeline and report changes are tested before they go to production.

Data Quality Monitor

Continuously profiles, validates and scores enterprise data, with Agentic AI that recommends rules and flags anomalies, so analytics and AI run on trusted data.

Capabilities

AI-recommended DQ rules and scoring
Agents suggest completeness, validity and uniqueness rules, with scores down to the column.
Data profiling
Analyzes distributions, patterns and frequencies to surface outliers.
AI-based observability
Agents monitor pipelines end to end, detect anomalies and suggest fixes.
Data catalog
Organizes models and tables in one catalog, with AI-drafted descriptions.
Data lineage
Traces data from origin to destination through every transformation.
Data quality issue tracking
Assigns every failing record to an owner and tracks it to resolution.

ETL Validator

Automates ETL/ELT testing, with Agentic AI that builds tests from mapping docs, confirming every record arrives complete, accurate and correctly transformed.

Capabilities

AI-generated ETL tests
Turns mapping docs into checks for joins, transforms and edge cases.
Source-to-target validation
Matches loaded data to the source, down to record counts and required fields.
Transformation validation
Verifies business logic with SQL, Python or Scala.
Migration validation
Checks schema, row counts and integrity for cloud migrations.
Metadata change audit
Catches schema and metadata discrepancies before they break pipelines.
Root cause and adaptive tests
Pinpoints where data broke, and agents update tests when mappings change.

BI Validator

Automates testing and governance for Power BI, Tableau and Oracle Analytics, with Agentic AI that builds tests from plain English and keeps reports accurate and reliable.

Capabilities

AI-created BI tests
Describe a test scenario in plain English, and agents build it.
Visual-to-source comparison
Compares the data behind every visual to the source using auto-generated SQL.
Regression and upgrade checks
Pixel-level comparisons across environments, with AI summaries of what changed.
Measure logic checks
Converts BI measures and calculations to SQL to confirm KPI logic.
Performance and load testing
Simulates concurrent users and measures load and refresh times.
BI governance
Finds unused measures, duplicate reports and orphaned tables.

Test Data Manager

Uses Agentic AI to detect and mask sensitive data and generate synthetic data that mirrors production, so teams can test without exposing real records.

Capabilities

AI synthetic data generation
Learns patterns from a small sample to create production-like data.
PII discovery and masking
Detects PII and PHI and replaces it with realistic fake values.
Relationship-aware data
Keeps linked tables connected with referential integrity.
Millions of records in minutes
Scales for load, stress and performance testing.
Multi-format output
CSV, Parquet or JSON, or loaded straight into test databases.
Compliant by design
Cloud or on-prem, supporting GDPR and HIPAA requirements.
Data Quality Use Case
The problem to solve
ROI calculator
Estimate the time and cost you’ll save.
Financial services
SOX, BCBS 239 and NAIC MAR

Banking, Financial Services, and Insurance (BFSI)

Stop reporting errors before examiners find them, with every number traced from core system to board dashboard.

How Datagaps helps

Core platform migrations
Cut over banking and insurance platforms, including mainframe to cloud, without losing a record.
Regulatory reporting
Hold submissions until the data meets quality thresholds.
Financial reconciliation
Match GL to subledger automatically, with every break flagged.
Risk and credit data
Catch drift before risk, lending and pricing models degrade.
Dashboard attestation
Prove capital and board dashboards match the warehouse.

Healthcare

Keep claims and clinical data accurate through every migration, without exposing patient records in testing.

How Datagaps helps

EHR migrations
Confirm every record survives the move to Epic, Cerner or Oracle Health.
Claims data quality
Catch errors in claims and remittance feeds as they arrive.
APCD submissions
Check every file against state templates before you submit.
Clinical dashboards
Catch KPI and report changes after every refresh.
Provider directories
Keep provider listings accurate, current and audit-ready.

Life Sciences

Catch issues in clinical and real-world data before submission, and keep trial subject data out of test environments.

How Datagaps helps

Clinical data migrations
Move EDC, CTMS and LIMS data to the cloud without losses.
CRM migrations
Keep rebate calculations right through Veeva and Salesforce moves.
Pharmacovigilance data
Catch adverse event data issues before regulatory submission.
Commercial and clinical dashboards
Trace every KPI back to source clinical and lab records.
De-identified trial data
Keep subject data out of test, analytics and AI environments.

Manufacturing

Avoid broken ERP cutovers and supplier overpayments, and catch sensor drift before it hits production.

How Datagaps helps

ERP migrations
Move BOM, inventory and financial data across Oracle, SAP and cloud without breaks.
Supplier reconciliation
Catch overpayments and duplicate invoices with three-way PO, ASN and invoice matching.
Sensor data quality
Catch drift before it skews predictive maintenance and yield models.
Operations dashboards
Catch report breaks after every release or upgrade.
Safe ERP test data
Keep supplier pricing and production volumes out of lower environments.

Retail and Utilities

Catch settlement, inventory and pricing errors before your customers or regulators do.

How Datagaps helps

Settlement reconciliation
Match marketplace payout files to the general ledger, record by record.
Inventory accuracy
Keep POS, ERP and warehouse numbers in sync.
Pricing and promotions
Catch price and promotion mismatches across channels.
Reliability dashboards
Keep SAIDI and SAIFI reliability reporting accurate.
BI under load
Make sure reports hold up for thousands of concurrent users.

Higher Education & Research

Get enrollment, financial-aid and transcript data right before SIS cutover, before students feel it.

How Datagaps helps

SIS migrations
Validate moves from Banner or PeopleSoft to Workday Student or Ellucian.
Financial-aid reconciliation
Match aid and Bursar data to the general ledger.
Enrollment reporting
Keep census and admissions dashboards consistent from cycle to cycle.
Federal reporting
Monitor data quality ahead of IPEDS submissions.
Safe student data
Test and train AI without exposing real student records.

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Datagaps works natively with the cloud, data and BI platforms your teams already run.

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Consulting and integration firms that deliver Datagaps validation for enterprise clients worldwide.

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Datagaps vs Wiiisdom: Choosing an AnalyticsOps Platform for Agentic Analytics

Datagaps vs Wiiisdom Choosing an AnalyticsOps Platform for Agentic Analytics

Datagaps vs Wiiisdom: An Overview

Datagaps vs Wiiisdom: Both are AnalyticsOps platforms for Power BI and Tableau. Wiiisdom is built around governance: certification, lifecycle management and monitoring. Datagaps governs and monitors the BI estate too, and adds what agentic analytics depends on: proof that each number matches the source data, across the filter states users and AI agents will query.

The Verdict at a Glance

Datagaps is the stronger choice when the question is whether the numbers are right. Wiiisdom suits teams whose priority is certifying and promoting BI content. Datagaps:

Checks each Power BI and Tableau figure against the source data, not only against an earlier version of the report.

Generates every combination of the filter values you select and runs the same check on each one.

Validates Tableau to Power BI migrations three ways: old report, new report and source.

Monitors the BI estate with the BI Governance Hub and lets AI agents build tests under admin control.

Why Does AnalyticsOps Matter More With Agentic Analytics?

AnalyticsOps applies DevOps habits to BI: automated testing, monitoring and release control. Three changes make it harder to keep BI numbers right by hand.

  • AI now answers from BI models. Copilot and agentic analytics tools query the same semantic models and measures as dashboards. Gartner predicts that by 2028, 60% of self-service analytics users will use general-purpose LLMs for ad hoc and exploratory analysis. A wrong measure now reaches people through chat as well as charts.
  • Filters multiply the work. Three filters with three values each give 27 states on a single report page. Manual testing reaches a few of them.
  • Migrations put every number in question. A Tableau to Power BI move can cover thousands of dashboards, and each one has to show the same figures afterwards.
BI filter matrix: three filters with three selected values each produce 27 combinations, each validated against the source
Figure 1. The BI filter matrix. One validation, run once for each combination of the selected filter values.

The AnalyticsOps Trust Model

We compare the two platforms on five questions. The first is about the BI estate, the middle three decide whether a number can be trusted, and the last is about doing it at scale.

The AnalyticsOps Trust Model: Govern and monitor, Prove, Cover, Protect, Automate
Figure 2. The AnalyticsOps Trust Model.

Prove, Cover and Protect carry the most weight. A well-governed report that shows a wrong number is still wrong, and an AI agent will repeat it.

How Do Datagaps and Wiiisdom Approach AnalyticsOps?

 

Wiiisdom

Datagaps

Starting point

Analytics governance; tests feed certification

BI testing; every figure proven against its source

Governance

Certification, lifecycle management, predictive monitoring

BI Governance Hub, BI Analyzer and BI Catalog

BI platforms

Tableau, Power BI, SAP BusinessObjects

Tableau, Power BI, Oracle Analytics and other BI platforms

Beyond BI

Not covered

ETL, data quality and test data on the same suite

Deployment

SaaS

On-premises or your own cloud

Status versus proof

Wiiisdom’s certification puts a “certified” badge on a dashboard when it passes its tests and removes it when a later test fails. That is more than Tableau and Power BI do natively, where an administrator sets the label by hand.

The badge records that tests passed; it does not compare the figure with the warehouse. If a broken measure drops €0.4M, the model refreshes, the figure meets its rules and the badge stays. BI Validator queries the warehouse under the same filters, gets €4.6M instead of €4.2M and fails the test.

Status versus proof: a certified dashboard shows 4.2 million euros while the warehouse returns 4.6 million
Figure 3. A certified report can still show the wrong number. A source check catches it.

How Do They Compare, Layer by Layer?

Wiiisdom entries come from its public product pages and release notes as of October 2026.

Layer

Capability

Datagaps

Wiiisdom

Edge

Prove

Power BI vs source

Each visual's DAX converted to SQL and compared with the warehouse

Checks inside the model; no source comparison described

Datagaps

Cover

Filter combinations

Every combination of selected report, page, visual and slicer values

One filter change per Power BI user journey; Tableau filter checks coming to its cloud platform

Datagaps

Govern

Certification

Flags heavily used content nobody has certified

Badge applied and removed automatically from test results

Wiiisdom

Govern

Content lifecycle

Tests run in your CI/CD pipeline; deployment stays with Tableau and Power BI tools

Promotes Tableau content from development to production with approval gates and version history

Wiiisdom

Monitor

Estate monitoring

Governance Hub: refresh, capacity, usage and compliance monitors; 12-week capacity runway; owner alerts

Predictive monitoring, capacity planning, governance agents

Level

Govern

Metadata and clean-up

BI Analyzer, BI Catalog, metadata compare; unused, duplicate and orphaned content

Duplicate content agent for Power BI

Datagaps

Prove

Tableau vs source

Worksheet data compared with SQL, with a non-AI option

Accuracy checks against the source

Level

Protect

Regression testing

Data, visual and functional comparison across versions and environments

Regression and cross-environment tests

Level

Protect

Tableau to Power BI

Old report vs new report vs source

Field-by-field reconciliation claimed; method not published

Datagaps

Protect

Load testing

Power BI, Tableau and Oracle Analytics

Tableau

Datagaps

Automate

AI and agents

AI Workflows, plain-English tests, MCP server, admin-approved tools

Governance agents, AI-assisted Tableau testing, MCP access

Level

Beyond BI

Data underneath

ETL Validator, Data Quality Monitor, Test Data Manager

Not covered

Datagaps

Other

SAP BusinessObjects

Not a focus

360Suite, a dedicated product

Wiiisdom

Other

Deployment

On-premises or your own cloud

SaaS platform; nothing to deploy on-premises

Depends

What the scorecard shows: Datagaps leads on proving numbers against the source, covering filter states and validating migrations. Wiiisdom leads on certification, content promotion and SAP BusinessObjects. Monitoring, regression testing and AI automation are close.

Where Does Datagaps Go Further?

Prove: every visual checked against the source

Visual-to-SQL pulls the query behind each visual, DAX for Power BI and worksheet logic for Tableau, converts it to SQL for the connected database and shows the two side by side for review. Report Data Compare then lists rows only in the report, rows only in the database and mismatched values. QA teams can test a dashboard without knowing DAX.

A global hospitality company runs 96 automated validation pipelines this way against Power BI and cut QA effort by 70%.

Cover: the BI filter matrix

BI Validator captures filter values at report, page, visual and slicer level, including hierarchies such as year, quarter and month. It multiplies the selected values into a filter dataset and runs the same validation once per combination. The dataset can be regenerated when values change and reused in another environment.

A global consulting firm using BI Validator saved about 70% of its report validation time and cut turnaround by 80%.

Protect: three-way migration checks

Datagaps validates migrations rather than performing them, so the check stays independent of the partner doing the work. Each new Power BI report is compared with the old Tableau report and with the source, under the same filters. KPIs, visuals and metadata are compared as well, and DAX is converted to SQL so measure logic can be checked. After cutover, the same tests run as regression.

Three-way migration check between the old Tableau report, the new Power BI report and the source data
Figure 4. Three-way migration check: all three must agree.

Automate: AI builds the tests, people approve them

  • One request to the Global AI Assistant creates a report’s test, runs it and returns the result.
  • A mismatch analyser agent explains failures in plain English and posts them to email, Teams or Slack.
  • The DAX AI Assistant writes DAX from a plain-English question for testers who don’t know DAX.
  • Agents call only the tools an administrator approves, with each user’s own permissions. Teams choose their AI provider and can run on-premises.

Beyond BI: the data underneath

Many report errors start upstream. ETL Validator, Data Quality Monitor and Test Data Manager cover pipelines, data quality and test data on the same suite, so a check can start at a source table and end at a dashboard visual. Wiiisdom’s own 2026 market landscape lists BI Validator with coverage from ETL processes and data reconciliation through to the BI report layer.

What Wiiisdom Claims, and What Holds Up

#

Wiiisdom claim

What we found

Verdict

1

Clean data alone does not make a decision correct

Agreed. Errors also enter in the BI layer, which is why BI testing matters.

Holds up

2

Accuracy tests reconcile reports with the source

Described for Tableau. Its Power BI tests run inside the model, with no source comparison described.

Tableau yes; Power BI not shown

3

The first Agentic Analytics Governance platform

A positioning claim. Its governance agents started with the October 2026 release, beginning with duplicate detection for Power BI.

Unverified

What Do Teams Moving Off Wiiisdom Report?

Teams that have moved on from Wiiisdom, or its earlier Kinesis-CI product, describe similar frustrations, and support comes up first. One BI lead said: “They would take ages to reply… they never really had a solution for anything.”

What teams report

What Datagaps provides

Support cases left open for months without a fix

Responsive support; switching teams say most issues are "quickly resolved"

After moving to Power BI, back to running SQL and checking charts by hand

Power BI reports tested against the source automatically

Filter states tested one at a time

Every combination of the selected filter values, run automatically

A BI-only tool means another tool beside data testing

BI and data testing on one platform

The same BI lead called Wiiisdom “quite far behind” and would give Datagaps five out of five for both support and product.

What Do Independent Reviews Say?

Wiiisdom’s reviews sit almost entirely with 360Suite, its SAP BusinessObjects product. Its Tableau and Power BI platform has no G2 reviews, and we found no Gartner Peer Insights, Capterra or TrustRadius listing. Datagaps holds 4.5 from 11 G2 reviews and 4.6 from eight Gartner Peer Insights reviewers, the newest from June 2026.

Which Platform Fits Your Team?

Wiiisdom fits if...

Datagaps fits if...

Certification badges are your main signal of trust

You must show that report numbers match the source

You want Tableau content promoted with approval gates and version history

You need many filter states tested, not a handful

You run SAP BusinessObjects

You are validating a Tableau to Power BI migration

You want a SaaS platform with nothing to deploy on-premises

You need on-premises or your own cloud, with data testing on the same platform

What Should You Ask in Your Evaluation?

Layer

Question to ask

How Datagaps answers it

Govern and monitor

Do we know what is in our BI estate, and is it healthy?

Governance Hub monitors, BI Analyzer and BI Catalog

Prove

Is every number right against the source?

Visual-to-SQL and Report Data Compare

Cover

Were the filter states users rely on tested?

The BI filter matrix, run automatically

Protect

Will it stay right through releases and migrations?

Regression and three-way migration checks

Automate

Can AI build and run the checks safely?

AI Workflows with admin-approved tools

Support

How fast does the vendor fix problems?

Ask each vendor for response times and a recent reference customer

Teams using Wiiisdom can run BI Validator on the same reports during a 14-day trial and compare the results side by side.

Explore BI Validator → | Start a 14-day trial → | Read: Datagaps vs iCEDQ →

Get Started Today

See BI Validator prove your Power BI and Tableau numbers against the source

Our team will run a live demo on your own reports — your BI platform, your filters, your source data.

SOC 2 Type II certified | ISO 27001 certified | No credit card required for trial | Your data never leaves your environment

Frequently Asked Questions: Datagaps vs Wiiisdom

Is Datagaps an alternative to Wiiisdom?

Yes. Both test and govern Tableau and Power BI content. Datagaps adds checks against the source data, filter combination testing, three-way migration validation, more BI platforms and data testing on the same platform.

What is AnalyticsOps?

AnalyticsOps applies DevOps practices such as automated testing, monitoring and release control to BI and analytics content. Wiiisdom and Datagaps both offer it; Datagaps also proves report numbers against the source data.

Why does agentic analytics need BI testing?

AI assistants and agents answer from the same semantic models and measures as dashboards. If a measure is wrong, the AI answer is wrong too. Testing measures against the source before release keeps both correct.

Can Wiiisdom test filter combinations automatically?

Its published Power BI examples change one filter per user journey, and Tableau filter checks are still coming to its cloud platform. Datagaps BI Validator generates every combination of the selected filter values and runs each one.

Does Wiiisdom compare Power BI reports with the source database?

Its public pages do not describe it. Wiiisdom’s Power BI tests check refreshes, rules and DAX results inside Power BI. Datagaps converts each visual’s DAX to SQL and compares the report with the warehouse.

Which tool validates a Tableau to Power BI migration?

Datagaps BI Validator compares each new Power BI report with the original Tableau report and the source data, then keeps running the tests as regression after cutover, whoever performs the migration.

Is Wiiisdom Ops the same as Kinesis-CI?

Yes. Wiiisdom acquired Kinesis-CI, a Tableau testing tool, in 2020 and renamed it Wiiisdom Ops for Tableau in 2021. It is now sold as Wiiisdom for Tableau and Wiiisdom for Power BI.

Established in the year 2010 with the mission of building trust in enterprise data & reports. Datagaps provides software for ETL Data Automation, Data Synchronization, Data Quality, Data Transformation, Test Data Generation, & BI Test Automation. An innovative company focused on providing the highest customer satisfaction. We are passionate about data-driven test automation. Our flagship solutions, ETL Validator, DataFlow, and BI Validator are designed to help customers automate the testing of ETL, BI, Database, Data Lake, Flat File, & XML Data Sources. Our tools support Snowflake, Tableau, Amazon Redshift, Oracle Analytics, Salesforce, Microsoft Power BI, Azure Synapse, SAP BusinessObjects, IBM Cognos, etc., data warehousing projects, and BI platforms.  Datagaps

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