ABSTRACT:
Data architecture-as-a-service (DAaaS) is a new self-service paradigm that empowers business users to create architecturally compliant data pipelines and repositories. By injecting architectural guardrails into commercial, self-service data engineering tools, DaaS solves the problem of data silos.
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ABSTRACT:
The data pipeline market comprises four segments: data ingestion, data transformation, DataOps, and orchestration. This blog defines three principles for successful pipelines: (1) watch the innovative startups; (2) use suites where you can; and (3) use point tools where you must.
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Happy April Fool's Day! May you never be old enough not to take your inner child seriously!
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ABSTRACT :
This blog recommends four guiding principles for effective data engineering in a lakehouse environment.
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ABSTRACT :
Does one version of the truth still make sense? We explore this question about data and analytics, drawing lessons from the film My Cousin Vinny.
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ABSTRACT :
Recent research into the dynamics of social networks provides lessons for data leaders about how to spread and sustain change.
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ABSTRACT :
For many years data architecture efforts have focused on analytics. Now it is time to give attention to operational data architecture.
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ABSTRACT :
This blog explores the opportunity for automated workflows to help cross-functional teams collaborate and standardize organizational master data.
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ABSTRACT :
Data fabric may be a buzzword. But it’s shorthand for data issues that we must manage. Read on to learn what data fabric is and why it’s important.
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ABSTRACT :
The data mesh framework doesn’t specify a key component that completes the last mile of the architecture: a data provisioning environment.
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ABSTRACT :
The webinar will examine the convergence of data mesh and DAaaS and demonstrate DAaaS-enabled tools in action.
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