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The Ultimate Guide to Modern Data Quality Management (DQM) For An Effective Data Quality Control Driven by The Right Metrics

datapine

With quality data at their disposal, organizations can form data warehouses for the purposes of examining trends and establishing future-facing strategies. Industry-wide, the positive ROI on quality data is well understood. This means there are no unintended data errors, and it corresponds to its appropriate designation (e.g.,

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The importance of data ingestion and integration for enterprise AI

IBM Big Data Hub

Data ingestion must be done properly from the start, as mishandling it can lead to a host of new issues. The groundwork of training data in an AI model is comparable to piloting an airplane. The entire generative AI pipeline hinges on the data pipelines that empower it, making it imperative to take the correct precautions.

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The Modern Data Stack Explained: What The Future Holds

Alation

Extract, load, Transform (ELT) tools. Data ingestion/integration services. Data orchestration tools. These tools are used to manage big data, which is defined as data that is too large or complex to be processed by traditional means. How Did the Modern Data Stack Get Started? Reverse ETL tools.

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Enable data analytics with Talend and Amazon Redshift Serverless

AWS Big Data

About Talend Talend is an AWS ISV Partner with the Amazon Redshift Ready Product designation and AWS Competencies in both Data and Analytics and Migration. Talend Cloud combines data integration, data integrity, and data governance in a single, unified platform that makes it easy to collect, transform, clean, govern, and share your data.

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The disruptive potential of open data lakehouse architectures and IBM watsonx.data

IBM Big Data Hub

watsonx.data is truly open and interoperable The solution leverages not just open-source technologies, but those with open-source project governance and diverse communities of users and contributors, like Apache Iceberg and Presto, hosted by the Linux Foundation. This provides further opportunities for cost optimization.

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How smava makes loans transparent and affordable using Amazon Redshift Serverless

AWS Big Data

The data products from the Business Vault and Data Mart stages are now available for consumers. smava decided to use Tableau for business intelligence, data visualization, and further analytics. The data transformations are managed with dbt to simplify the workflow governance and team collaboration.