Posts by Seth Rao
How to Build a Data Stack That Ensures Data Quality
How does your organization manage the volumes of data ingested each day? The most effective way to ingest and manage large amounts of data is with a modern data stack. To build a data stack that meets your business needs, follow the five essential steps to ensuring the highest quality, most useable data possible outlined…
Read MoreHow to Reduce Data Transfer Costs in AWS?
One out of three organizations today use Amazon Web services (AWS) to store and manage their online data and applications. Unfortunately, Amazon charges hefty fees to transfer between locations, whether that’s to your on-premises network or to users on the public Internet. Learning how to reduce AWS data transfer costs is essential in minimizing expenses…
Read MoreData Mesh vs Data Lake: Understanding Key Architecture Differences, Benefits, and Trustability
Data Lake relies on a centralized data repository, while Data Mesh decentralizes data storage and management. It’s a war between different philosophies of data architecture, but your organization will eventually have to choose sides. So which is better for your business? Which is better for quick decisions and which is better for more reliable and…
Read More10 Leading Data Observability Tools Trusted by Top Tech Companies in 2026
In today’s data-driven world, ensuring the health and reliability of data systems is paramount for any organization. Data observability tools play a crucial role in achieving this by providing comprehensive monitoring and analysis of data flows and system performance. These tools help identify and resolve data issues in real-time, ensuring that your data is accurate,…
Read MoreImprove 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 MoreSix Key Data Quality Metrics and Ways to Automate Them on Azure and Snowflake
Measuring the right Data Quality metrics ensures that you have the most trustable data. The more accurate your data is on Azure, Snowflake, and other clouds, the more efficiently you can run your business. High-quality data helps improve data quality, reduces wasted time and effort, and helps you make more informed decisions about your business operations. Next…
Read MoreThe Ultimate Guide to Data Pipeline Tools in 2026
Welcome to our comprehensive guide on data pipeline tools for 2026! 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…
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