2021 Gartner® Magic Quadrant for Data Quality Solutions
We're a Leader again! Gartner® Magic Quadrant™ for Data Quality Solutions

Enterprise Data Quality Fabric

Simplify data management and deliver high quality data products to humans and machines.

Enterprise Data Quality Fabric

Data Quality Fabric is the self-driving car of data management. We automate the tedious aspects of the journey, so that you focus on creating value from data.

Enjoy the Data ride!

These forward-thinking companies are already reaping tangible benefits

Up to 40% higher data accuracy

  • Better data available for use right away
  • More accurate reporting

Up to 60% faster data processing

  • Lower hardware and processing costs
  • Faster delivery of data

Want to see similar results?

Schedule a call

Forget lengthy “data projects”

Remove friction and automate the delivery of accurate and reliable data to those who need it, whenever they need it.

Data Quality Fabric

I need data for:
Data providing pipeline is generated automatically:
Data Catalog
Data
Catalog
Data Catalog
Data
Profiling
Data Catalog
Assess data
quality
Data Catalog
Cleanse &
enrich data
Use the data
I need data for:
Get the approval
Find the people who know the data
Request data transformations
Get data transformed and cleansed
Use the data

What exactly is a Data Quality Fabric?

A Data Quality Fabric is a new iteration of the data fabric architecture that embeds data quality services throughout the whole data lifecycle and ensures the delivery of high quality data.

Your enterprise data instantly available to humans and machines as high quality data products, with governance and compliance ensured automatically.
Business users
Business users
APIs
APIs
Valid, consistent data available to business users and machines
Explore
Data for business users
Convenient access to source or processed data for business users
Explore
Data for apps
Automated data providing to applications and systems
Explore
Explore
The fabric is modular. Start with one module and build upon it. Click and explore modules
Business users
Business users
APIs
APIs
Valid, consistent data available to business users and machines
Data for business users
Data for business users
Convenient access to source or processed data for business users
Data for Apps
Data for Apps
Automated data providing to applications and systems
Explore
Explore
The fabric is modular. Start with one module and build upon it. Click and explore modules

The result?

Your enterprise data instantly available to humans and machines as high quality data products, with governance and compliance ensured automatically.

Data Quality Fabric
simplifies everything

Simplify data governance

Avast automates data cataloging, data protection, and data discovery.

Simplify master data management

A leading Canadian retailer simplified the matching process, speeding up data processing by 40% and reducing compute costs by 25%.

Learn more
Simplify regulatory reporting
Simplify regulatory reporting

Simplify regulatory reporting

A large UK banking group automated the production of regulatory reports for BCBS 239 and implemented continuous data quality monitoring.

Learn more

Want to simplify data management in your organization?

Schedule a call

How and most importantly why does it work?

1. Connect your data sources

Add all of the systems that store critical business data.


2. Capture and ingest metadata

Data Quality Fabric captures metadata from the connected sources by profiling its data.

You can also import and create business term definitions, data quality rules, DDLs, data models, and any other metadata.


3. AI infers additional metadata

Data Quality Fabric constantly monitors data for anomalies, data quality problems, and changes in data content.

But your data stewards are always in control to accept or reject metadata created by AI.


4. Use metadata to automate data governance processes

Set up metadata-driven data pipelines that work regardless of the actual data source, such as:

Data validation
Data standardization
Data integration
Data consolidation
Data quality monitoring


5. Consume reliable, accurate data

No matter whether it’s a business user consuming data or an API, both will get valid, accurate data.

Why did we put data quality into the data fabric?

Because connecting data silos is not enough. To derive meaning from data and integrate data from these silos, you need to embed data quality processes throughout the data lifecycle. Here is how:

Data entry and external data ingestion
DQ Firewall: catching and correcting errors in incoming data through data quality validations and enrichment.
Anomaly detection: using AI to detect irregularities in incoming data and alerting responsible stakeholders.
Data profiling: understanding data content and calculating statistics about data.
Data integration
Data standardization: aligning data formats to a common standard to enable data integration and consolidation.
Data transformation: automated changes to data to fit the target data structure.
Data consumption
Data preparation: self-service transformation of data to fit the indended purpose.
Data quality monitoring: continuously reporting the state of existing data for compliance with user-defined rules and custom aggregations and visualizations.
Anomaly detection: using AI to detect irregularities in incoming data and alerting responsible stakeholders.
Data sharing
Data validation: automated data checks for compliance with expected standards.
Data enrichment: adding missing information from external data sources and reference data.
Data transformation: automated changes to data to fit the data structure and format required for sharing.

Build a Data Quality Fabric in your organization

Schedule a call
Build a Data Quality Fabric in your organization Build a Data Quality Fabric in your organization


Discover the Ataccama
ONE Platform

Ataccama ONE is a full stack data management platform.
See what else you can do.