Remove Data Transformation Remove Metadata Remove Software
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Bridging the gap between mainframe data and hybrid cloud environments

CIO Business Intelligence

A high hurdle many enterprises have yet to overcome is accessing mainframe data via the cloud. Connecting mainframe data to the cloud also has financial benefits as it leads to lower mainframe CPU costs by leveraging cloud computing for data transformations. Four key challenges prevent them from doing so: 1.

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Data’s dark secret: Why poor quality cripples AI and growth

CIO Business Intelligence

We also examine how centralized, hybrid and decentralized data architectures support scalable, trustworthy ecosystems. As data-centric AI, automated metadata management and privacy-aware data sharing mature, the opportunity to embed data quality into the enterprises core has never been more significant.

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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

He/she assists the organization by providing clarity and insight into advanced data technology solutions. As quality issues are often highlighted with the use of dashboard software , the change manager plays an important role in the visualization of data quality. 2 – Data profiling. How Do You Measure Data Quality?

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Introducing a new unified data connection experience with Amazon SageMaker Lakehouse unified data connectivity

AWS Big Data

With the ability to browse metadata, you can understand the structure and schema of the data source, identify relevant tables and fields, and discover useful data assets you may not be aware of. Noritaka Sekiyama is a Principal Big Data Architect on the AWS Glue team. He loves exploring different cultures and cuisines.

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Ensuring Data Transformation Quality with dbt Core

Wayne Yaddow

How dbt Core aids data teams test, validate, and monitor complex data transformations and conversions Photo by NASA on Unsplash Introduction dbt Core, an open-source framework for developing, testing, and documenting SQL-based data transformations, has become a must-have tool for modern data teams as the complexity of data pipelines grows.

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Expanding data analysis and visualization options: Amazon DataZone now integrates with Tableau, Power BI, and more

AWS Big Data

Publish data assets – As the data producer from the retail team, you must ingest individual data assets into Amazon DataZone. For this use case, create a data source and import the technical metadata of four data assets— customers , order_items , orders , products , reviews , and shipments —from AWS Glue Data Catalog.

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Top 6 Benefits of Automating End-to-End Data Lineage

erwin

Data automation reduces the loss of time in collecting, processing and storing large chunks of data because it replaces manual processes (and human errors) with intelligent processes, software and artificial intelligence (AI). Automating data capture frees up resources to focus on more strategic and useful tasks.