Posts by Seth Rao
Improve Data Trust by 40% in Your Data Catalog With DataBuck & Alation’s Open Data Quality Initiative
Quality data provides insights that organizations can trust when making big picture decisions. However, the weight of these individual records can often overwhelm even the biggest firms with a seemingly endless number of resources. The Open Data Quality Initiative from Alation aims to help companies deploy the latest tools and technologies like DataBuck to streamline…
Read MoreHow to Scale Your Data Quality Operations With AI and ML?
How can you cost-effectively scale your data quality operations as your business scales? The key is to employ artificial intelligence and machine learning technology that can take on an increasing amount of the data quality management chores as they learn more about your organization’s data. It’s all in the about making the best use of…
Read MoreWhat Are the 6 Key Data Quality Metrics and How to Automate Them on Azure and Snowflake for Data Trustability
Measuring the right Data Quality metrics ensures that you have the most trustable data. The more accurate is your data on Azure, Snowflake and other clouds, the more efficiently you can run your business. High-quality data reduces wasted time and effort, it also helps you make more informed decisions about your business operations. Next is being…
Read MoreThe Ultimate Guide to Data Pipeline Tools in 2025
Welcome to our comprehensive guide on data pipeline tools for 2025! As businesses increasingly rely on accurate and timely data for decision-making, the significance of maintaining an error-free data pipeline has never been more crucial. Errors in data can propagate across an organization, leading to significant impacts on business operations. This guide will provide you…
Read MoreHow to Achieve AWS Data Quality: 6 Proven Strategies for Cloud Success
Data stored in the cloud is notoriously error-prone. In this post, you’ll learn why data quality is important for cloud data management – especially data stored with Amazon Web Services (AWS). With every step that error-ridden data moves downstream, those errors get compounded – and it takes 10 times the original cost to fix them.…
Read More3 Top Big Data Uses in Financial Services
Data warehouses, lakes, and cloud services are notoriously error prone. In the financial services (FinServ) sector, this is unacceptable. Unmonitored, unvalidated, and unreliable data places these firms at risk due to the sensitive nature of the big data they manage. If your FinServ firm needs solutions for its dark data issues, you’ll need to learn…
Read MoreThe Ultimate Guide to Data Quality Testing for Reliable Insights
Introduction to Data Quality Data quality testing is essential for safeguarding your business from the pitfalls of poor-quality data. When the integrity of your company’s information assets is compromised, it can lead to revenue loss and operational inefficiencies. Accurate data is crucial across all industries for analysis and data-driven decision-making. Without it, businesses cannot remain…
Read MoreWhat is Data Monitoring? Discover How a Data Monitoring System Can Elevate Your Data Quality
What is Data Monitoring and Why Do You Need It? Organizations leverage information to make decisions that affect people and revenue. Data monitoring plays a role by ensuring that any data submitted is reliable and meets the criteria of an organization. It keeps checking the data to verify that it still holds to the rules…
Read MoreHow to Architect Data Quality on Snowflake – Serverless, Autonomous, In-Situ Data Validation
With the accelerating adoption of Snowflake as the cloud data warehouse of choice, the need for autonomously validating data has become critical. Architect Data Quality on Snowflake – Serverless, Autonomous, In-Situ Data Validation.
Read MorePoor Data Quality regulatory nightmare for a major Bank
Bank wrongly collects debt from customers due to IT errors. One of Europe’s reputed progressive banks is Danske Bank (Denmark). They pride themselves in excellent customer service and ethical treatment of their customers. Recently, much to their reputational embarrassment they collected outdated and excessive debt from up to 106,000 customers due to errors in its…
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