Posts Tagged ‘Data Quality’
12 Top Data Governance Tools & Software for 2023
Is your organization looking to employ new data governance tools in the coming year? Data governance is necessary to ensure the accurate and reliable information your company needs to make the best possible business decisions. When you want robust data governance, here are 10 top-rated software solutions to consider, all of which can help your…
Read MoreData Mesh Vs. Data Lake: Data Architecture Wars and its impact on Data 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 MoreThe Real (and Scary) Cost of Bad Data
Bad data can cost you money. It can also damage your reputation, drive good customers away, and negatively affect your entire workforce. Bad data, more often than not, results in bad decisions – and bad decisions can destroy a business. The true costs of bad data are so overwhelming that they’re scary. If you don’t…
Read More10 Best Data Catalog Tools for Enterprises to Consider in 2024
Many tools help build and manage data catalogs. Here, we outline key features, capabilities, and components of 10 well-known data catalog tools. In today’s data-driven world, managing data sprawl across various databases and repositories poses significant challenges for organizations. Without effective data management, BI and data analytics initiatives struggle to yield insights. Data catalogs offer…
Read MoreData Warehouse Architecture: Traditional vs. Cloud
A data warehouse is a system that gathers data from various sources and makes it available to management and others to support and improve their decision-making. Data warehouses can employ either a traditional architecture or a cloud-based one. That brings us to the traditional vs. cloud data warehouse architecture topic. Which is best for your…
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…
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