Posts by Angsuman Dutta
15 Data Catalog Tools & Software to Use in 2023
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…
Read MoreData Integrity: The Last Mile Problem of Data Observability
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…
Read MoreStrategies for Achieving 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,…
Read MoreHow to ensure Data Trustability in your Data Lakes, Pipelines, and Warehouses?
If data is the new oil, then high-quality data is the new black gold. Just like with actual oil, if you don’t have good data quality, you’re not going to get very far. In fact, you might not even make it out of the starting gate. So, what can you do to make sure your…
Read MoreEstablish autonomous data observability and trustability for AWS Glue Pipeline in 60 Seconds
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…
Read MoreWhy do Data Quality Programs Fail?
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…
Read MoreEnhance AWS Glue Pipeline with Autonomous Data Validation
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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