Blog Posts on Cloud, Data Lake, Data Quality Validation and Data Reconciliation
Why Is Data Monitoring Important?
Running a business requires a lot of work and attention, but you can make your job a lot easier with data monitoring. With data monitoring, there are fewer risks of errors and incorrect analytics. On top of that, it can help your bottom line. If you would like to know more about data monitoring, keep reading.
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How to Automate Data Monitoring: 3 Key Areas to Streamline
For 62% of businesses, a lack of agility in data processes hurt their response to changing business needs. A practical…
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How to Minimize Data Analysis Costs for Your Enterprise
Data collection and analysis are vital for organizations. Although, they are becoming more costly than ever. Does your organization know…
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The Importance of Data Quality for the Cloud and AWS
Data stored in the cloud is notoriously error-prone. In this post, you’ll learn why data quality is important for cloud…
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3 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,…
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The A-to-Z Guide to Data Quality Testing
Data quality testing guards your business against low-quality data. If the quality of your company’s information assets is impacting revenue,…
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What is Data Monitoring and Why Do You Need It?
What is Data Monitoring and Why Do You Need It? Organizations leverage information to make decisions that affect people and…
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How 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.
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Cloud Data Pipeline Leaks: Challenge of Data Quality in the Cloud
Organizations, especially those in financial services, struggle to ensure data quality in the cloud. Data pipelines often drop rows thanks to issues with infrastructure that companies don’t control, but the scale at which these organizations process data means that manual methods of identifying these leaks are insufficient.
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Poor 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).…
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