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Data Trustability: The Bridge Between Data Quality and Data Observability

Dataversity

So, what can you do to ensure your data is up to par and […]. The post Data Trustability: The Bridge Between Data Quality and Data Observability appeared first on DATAVERSITY. You might not even make it out of the starting gate.

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Testing and Monitoring Data Pipelines: Part One

Dataversity

Suppose you’re in charge of maintaining a large set of data pipelines from cloud storage or streaming data into a data warehouse. How can you ensure that your data meets expectations after every transformation? That’s where data quality testing comes in.

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Alation 2022.2: Open Data Quality Initiative and Enhanced Data Governance

Alation

generally available on May 24, Alation introduces the Open Data Quality Initiative for the modern data stack, giving customers the freedom to choose the data quality vendor that’s best for them with the added confidence that those tools will integrate seamlessly with Alation’s Data Catalog and Data Governance application.

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Five benefits of a data catalog

IBM Journey to AI blog

It uses metadata and data management tools to organize all data assets within your organization. It synthesizes the information across your data ecosystem—from data lakes, data warehouses, and other data repositories—to empower authorized users to search for and access business-ready data for their projects and initiatives.

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Maximize the Power of dbt and Snowflake to Achieve Efficient and Scalable Data Vault Solutions

phData

The implementation of a data vault architecture requires the integration of multiple technologies to effectively support the design principles and meet the organization’s requirements. Data Acquisition: Extracting data from source systems and making it accessible. Implement Data Lineage and Traceability Path: Data Vault 2.0

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Data Mesh Architecture and the Data Catalog

Alation

Making the experts responsible for service streamlines the data-request pipeline, delivering higher quality data into the hands of those who need it more rapidly. Some argue that data governance and quality practices may vary between domains. Interoperable and governed by global standards. Self-describing.

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Mainframe Data: Empowering Democratized Cloud Analytics

Precisely

The cloud is especially well-suited to large-scale storage and big data analytics, due in part to its capacity to handle intensive computing requirements at scale. BI platforms and data warehouses have been replaced by modern data lakes and cloud analytics solutions. Secure data exchange takes on much greater importance.