15 Data Catalog Tools & Software to Use in 2023 

A toolbox filled with data catalog tools.

Managing your organization’s data catalog is challenging. You need robust data catalog tools to ingest data from multiple sources, monitor data quality, and provide actionable insights.  What data catalog tools and software should your organization use? Read on to discover 12 tools that will help you better manage your data and get the most use…

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Data Integrity: The Last Mile Problem of Data Observability

Data Integrity

Data quality issues have been a long-standing challenge for data-driven organizations. Even with significant investments, the trustworthiness of data in most organizations is questionable at best. Gartner reports that companies lose an average of $14 million per year due to poor data quality.  Data observability has been all the rage in data management circles for a…

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Strategies for Achieving Data Quality in the Cloud

Data Quality in the Cloud

Previously published in Entrepreneur.com You’ve finally moved to the Cloud. Congratulations! But now that your data is in the Cloud, can you trust it?  With more and more applications moving to the cloud, the quality of data is becoming a growing concern. Erroneous data can cause all sorts of problems for businesses, including decreased efficiency,…

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Why do Data Quality Programs Fail?

Data Quality Programs

Fortune 1000 organizations spend approximately $5 billion each year to improve the trustworthiness of data. Yet only 42 percent of the executives trust their data. According to multiple surveys, executives across industries do not completely trust the data in their organization for accurate, timely business critical decision-making. In addition, organizations routinely incur operational losses, regulatory…

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Enhance AWS Glue Pipeline with Autonomous Data Validation

An illustration of binary codes traveling in speed

Data operations and engineering teams spend 30-40% of their time firefighting data issues raised by business stakeholders. A large percentage of these data errors can be attributed to the errors present in the source system or errors that occurred or could have been detected in the data pipeline. Current data validation approaches for the data…

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