Remove Data Processing Remove Data Warehouse Remove Definition Remove Metadata
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The Top Three Entangled Trends in Data Architectures: Data Mesh, Data Fabric, and Hybrid Architectures

Cloudera

This team or domain expert will be responsible for the data produced by the team. The data itself is then treated as a product. The data product is not just the data itself, but a bunch of metadata that surrounds it — the simple stuff like schema is a given. Data fabric defined.

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Setting up and Getting Started with Cloudera’s New SQL AI Assistant

Cloudera

This can include assumptions about the intent of the natural language used, like the definition of “top selling products,” values of needed literals, and how joins can be created. Supported AI models and services The SQL AI Assistant is not bundled with a specific LLM; instead it supports various LLMs and hosting services.

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How smava makes loans transparent and affordable using Amazon Redshift Serverless

AWS Big Data

To speed up the self-service analytics and foster innovation based on data, a solution was needed to provide ways to allow any team to create data products on their own in a decentralized manner. To create and manage the data products, smava uses Amazon Redshift , a cloud data warehouse.

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Why Enterprise Data Lineage is Critical for the Success of Your Modern Data Stack

Octopai

Data lineage is the ability to view the path of data as it flows from source to target within your data ecosystem, along with everything that happened to it along the way. And data lineage solutions will also show you any transformations the data underwent on its journey.

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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

Reporting being part of an effective DQM, we will also go through some data quality metrics examples you can use to assess your efforts in the matter. But first, let’s define what data quality actually is. What is the definition of data quality? Industry-wide, the positive ROI on quality data is well understood.

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What is Data Mapping?

Jet Global

The quick and dirty definition of data mapping is the process of connecting different types of data from various data sources. Data mapping is a crucial step in data modeling and can help organizations achieve their business goals by enabling data integration, migration, transformation, and quality.

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Themes and Conferences per Pacoid, Episode 11

Domino Data Lab

In other words, using metadata about data science work to generate code. In this case, code gets generated for data preparation, where so much of the “time and labor” in data science work is concentrated. ” Spark programs are DAGs by definition, designed to use a wide variety of different kinds of data sources.

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