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DataOps Suite
The complete platform
Platform Overview
See how it works

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 youโ€™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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A practitioner summit focused on the validation, observability, governance, and reconciliation practices that determine whether enterprise data is ready for AI.

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Technology Partners

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

Our technology partners

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SI Partners

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

Our SI partners

Solutions

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BI and analytics

BIWA SIG 2014

BIWA-SIG-2014-19-1-1

I pulled the full content, but I want to flag something before drafting: this is a very short, event-recap post from January 2014 about attending the BIWA SIG conference โ€” itโ€™s mostly a few paragraphs of informal commentary (a demo of Oracle Endeca, general impressions of the event, low attendance) with no real technical or product substance. There isnโ€™t much โ€œmeatโ€ here to extract into AEO-style structured content, and itโ€™s now 12 years out of date (references a โ€œnext BIWA SIGโ€ from January 2015).

Key Takeaways

  • Datagaps sponsored and attended BIWA SIG 2014, a BI-focused event in Redwood City, CA, as part of its ongoing event circuit.
  • Oracle previewed BI Platform investments, including improved user experience and expanded mobile support, alongside a first demo of Oracle Endecaโ€™s UI.
  • Datagaps received positive market feedback on its solution portfolio from bloggers, potential clients, and partners at the event.
  • Attendance was a noted weak point, with few actual customers present beyond Oracle staff and partners โ€” prompting plans to improve outreach for future events.

We just came back last night from BIWA SIG, a BI related event that was held in Redwood City, CA. The organizers did a great job of putting together wonderful sessions spanning all areas of Analytics.

Balaji Yelamanchili shared the latest and greatest from Oracle. It was nice to know that Oracle is investing in improving the user experience of the BI Platform & Applications and enhancing support for mobile platform. I saw a demo of Endeca for the first time and I should say that it is pretty cool! Not sure about the underlying algorithms and how well does it interpret unstructured text but the UI is awesome!

On our solution portfolio, we got very positive feedback from few bloggers, potential clients and partners and that is always encouraging.

BIWA SIG is definitely part of our yearly event circuit now. We sponsored the event last year, this year and most likely will do so next year as well. The only thing that disappointed us was the attendance. Other than Oracle folks and partners, there were very few customers. Hopefully next year, we will better collaborate with the organizers and help them spread the work so that more folks can benefit from this extremely focused and well organized event!

Next BIWA SIG:

When: January 27th โ€“ 29th of 2015. Visit http://www.biwasummit.com  for further updates.

Where: Oracle Conference Center, Redwood City, CA

About Datagaps:

Our vision is empowering our customers with trustworthy Business Intelligence and Data.

Who We Are:

Trusted Globally by more than 70 Companies for Data Test Automation Solutions

Datagaps is passionate about data-driven testing automation. Our flagship solutions, ETL Validator, Data Flow & 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.

Mission Statement:

Datagaps was started in the year 2010 with the mission of building trust in enterprise data and reports. We provide software for ETL Data Automation, Data Synchronization, Data Quality, Data Transformation, Test Data Generation, and BI Test Automation. Datagaps is an innovative company focused on providing the highest customer satisfaction.

Conclusion

BIWA SIG 2014 reinforced Datagapsโ€™ commitment to the Oracle Analytics community, offering a firsthand look at Oracleโ€™s roadmap for BI Platform usability and mobile support, along with early access to the Endeca UI. Positive feedback from bloggers, partners, and prospects made the event worthwhile despite lower-than-expected customer turnout โ€” a gap Datagaps aimed to close through closer collaboration with organizers in future years. The event remained part of Datagapsโ€™ ongoing sponsorship circuit heading into 2015.

FAQs: BIWA SIG 2014

1) What was BIWA SIG 2014?

BIWA SIG 2014 was a Business Intelligence-focused conference held in Redwood City, California, centered on Oracleโ€™s Analytics ecosystem, which Datagaps attended as both a participant and sponsor.

2) What Oracle updates were shared at BIWA SIG 2014?

Oracle shared plans to continue investing in its BI Platform through user experience enhancements, expanded mobile capabilities, and an early preview of the Oracle Endeca user interface.

3) How was Datagapsโ€™ presence received at the event?

Datagaps received positive feedback on its solution portfolio from bloggers, prospective customers, and partners who attended the conference.

4) Did Datagaps plan to continue participating in BIWA SIG?

Yes. Although customer attendance at the 2014 event was lower than expected, Datagaps expressed its intention to continue sponsoring and participating in future BIWA SIG conferences.

Get Started Today

Talk to a datagaps expert

Rajesh Kumar A
Rajesh Kumar A

Digital Marketing Manager, Datagaps

Digital Marketing Manager at Datagaps. Drives data-driven growth through content, performance campaigns, and marketing technology.

SPS Murthy
S P S Murthy Akella

Director, Technology Strategy, Datagaps

Director of Technology Strategy at Datagaps. Business solutions architect and Certified Scrum Master in data engineering, responsible AI, and ML across BFSI, telecom, aviation, and energy.

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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