Data Quality and Observability

Ensure timely, trusted and relevant data for your AI and business initiatives.

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“The vision I describe to my colleagues is that they’ll be able to implicitly trust the data that informs them, no matter where in our organization it comes from – that goes for our cloud data stored on Microsoft Azure.”

Robin Miller

Group Data Manager, Lowell

Use fit-for-purpose data at enterprise scale

Automate and scale data profiling

Perform continual analysis to better understand your data and detect problems.

Automate and scale data profiling
Improve data accuracy and reliability at scale

Improve data accuracy and reliability at scale

Integrate data cleansing, standardization, address verification and more for multiple use-cases.

Prebuilt AI-powered rules and accelerators

Autogenerate common data quality rules across virtually any data from practically any source.

Prebuilt AI-powered rules and accelerators
Boost data observability for better insights

Boost data observability for better insights

Understand the health of your data through the multiple lenses of data, pipelines and business.

Get consumption-based pricing

Pay only for what you use with our flexible pricing.

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Explore related Data Quality and Observability services

As a leading part of the AI-powered Informatica Intelligent Data Management Cloud (IDMC), Data Quality and Observability works with a range of complementary services.

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Key Data Quality and Observability resources

Why You Need Cloud Modernization to Unlock AI
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White Paper

5 Best Ways to Build a Business Case for High-Quality Data
Show the potential productivity, revenue and customer experience gains of your data quality improvement project with these five business value frameworks.
eBook
The Art of Mastering Data Quality for AI and Analytics
Get this eBook to learn how data and IT leaders can master data quality for artificial intelligence (AI) and analytics and build a successful strategy.
White Paper

Data Observability: The Key to Successful Data and Analytics

Learn how data observability is the key to successful data and analytics. Start delivering high-quality, trusted data to make informed business decisions.
Analyst Report

2024 Gartner® Magic Quadrant™ for Augmented Data Quality Solutions

Informatica named a Leader in the Gartner® Magic Quadrant® for Augmented Data Quality Solutions for the 16th time

FAQ for Data Quality and Observability

Data quality is the degree to which data is accurate, complete, consistent, timely and relevant for its intended use.

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Data quality is important because it can have a significant impact on the accuracy of AI and analytics results, decision-making, operational efficiency and overall business performance.

Learn more about importance of having quality data

Common types of data quality issues include data duplication, missing values, incorrect formatting, outdated information and inconsistent data across systems.

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The main benefits of improving data quality are that it enhances decision-making by providing accurate, complete, consistent, timely and relevant data to enable more accurate AI and analytics results and ultimately more-informed decisions.

Learn more about the benefits of improving data quality