Blog Posts on Cloud, Data Lake, Data Quality Validation and Data Reconciliation
How 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.…
Read MoreSelf-Service Data Ingestion Made Simple: 3 Essential Steps to Automate and Optimize
How much data does your organization ingest each day? If yours is like most companies, the amount of data you…
Read More12 Top Data Governance Tools & Software for 2025
Is your organization looking to employ new data governance tools in the coming year? Data governance is necessary to ensure…
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…
Read MoreBuilding Trust in Data: The Janitorial Work Critical for Business Success
Rahul Rao Arizona State University Data is the lifeblood of any organization, and ensuring that it is accurate and trustworthy…
Read MoreThe Real Impact of Poor Data Quality and Governance on Your Business
Bad data can cost you money. It can also damage your reputation, drive good customers away, and negatively affect your…
Read More10 Best Data Catalog Tools for Enterprises to Consider in 2025
Many tools help build and manage data catalogs. Here, we outline key features, capabilities, and components of 10 well-known data…
Read MoreData Warehouse Architecture: What Are the Types, Traditional vs. Cloud
What is Data Warehouse Architecture? Data Warehouse Architecture refers to the design and structure of a system used to gather,…
Read More10 Leading Data Observability Tools Trusted by Top Tech Companies in 2025
In today’s data-driven world, ensuring the health and reliability of data systems is paramount for any organization. Data observability tools…
Read MoreData Testing or Data Observability: The Ultimate Guide to Data Quality Enhancement
Poor-quality data is a blight on every organization that depends on data to run its operations. Using inaccurate and incomplete…
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