Posts by Angsuman Dutta
Strategies 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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