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Turnkey Cloud DataOps: Solution from Alation and Accenture

Alation

They must put high-quality data into the hands of users as efficiently as possible. DataOps has emerged as an exciting solution. As the latest iteration in this pursuit of high-quality data sharing, DataOps combines a range of disciplines. It synthesizes all we’ve learned about agile, data quality , and ETL/ELT.

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Supercharge your data strategy: Integrate and innovate today leveraging data integration

IBM Journey to AI blog

Scalable data pipelines: Seasoned data teams are facing increasing pressure to respond to a growing number of data requests from downstream consumers, which is compounded by the drive for users to have higher data literacy and skills shortage of experienced data engineers.

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Alation 2023.1: Easing Self-Service for the Modern Data Stack with Databricks and dbt Labs

Alation

Building data pipelines is challenging, and complex requirements (as well as the separation of many sources) leads to a lack of trust. Troubleshooting data issues , for an exploding number of disjointed systems and tools, breaks self-service for data users and creates gaps in visibility for dataOps.

DataOps 52
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Understanding Zero-Code Development Life Cycle in Matillion

phData

With the “Data Productivity Cloud” launch, Matillion has achieved a balance of simplifying source control, collaboration, and dataops by elevating Git integration to a “first-class citizen” within the framework. In Matillion ETL, the Git integration enables an organization to connect to any Git offering (e.g.,

ETL 52