Remove Data Architecture Remove Data Transformation Remove Enterprise
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Data Architecture Crash Course: Key Terms

Dataiku

We’ve set out to demystify the jargon surrounding data architecture to enable every team to understand how it impacts their objectives. Not sure what Hadoop actually is? A little fuzzy on what the difference is between cloud and on-prem storage?

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Making OT-IT integration a reality with new data architectures and generative AI

CIO Business Intelligence

The data transformation imperative What Denso and other industry leaders realise is that for IT-OT convergence to be realised, and the benefits of AI unlocked, data transformation is vital. The company can also unify its knowledge base and promote search and information use that better meets its needs.

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Power enterprise-grade Data Vaults with Amazon Redshift – Part 1

AWS Big Data

As with all AWS services, Amazon Redshift is a customer-obsessed service that recognizes there isn’t a one-size-fits-all for customers when it comes to data models, which is why Amazon Redshift supports multiple data models such as Star Schemas, Snowflake Schemas and Data Vault. Data Vault 2.0

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Ingest data from Google Analytics 4 and Google Sheets to Amazon Redshift using Amazon AppFlow

AWS Big Data

With Amazon AppFlow, you can run data flows at nearly any scale and at the frequency you chooseon a schedule, in response to a business event, or on demand. You can configure data transformation capabilities such as filtering and validation to generate rich, ready-to-use data as part of the flow itself, without additional steps.

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Supercharge Your Data Lakehouse with Apache Iceberg in Cloudera Data Platform

Cloudera

These tools empower analysts and data scientists to easily collaborate on the same data, with their choice of tools and analytic engines. No more lock-in, unnecessary data transformations, or data movement across tools and clouds just to extract insights out of the data.

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

erwin

It’s paramount that organizations understand the benefits of automating end-to-end data lineage. Critically, it makes it easier to get a clear view of how information is created and flows into, across and outside an enterprise. The importance of end-to-end data lineage is widely understood and ignoring it is risky business.

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Create a modern data platform using the Data Build Tool (dbt) in the AWS Cloud

AWS Big Data

It does this by helping teams handle the T in ETL (extract, transform, and load) processes. It allows users to write data transformation code, run it, and test the output, all within the framework it provides. It’s raw, unprocessed data straight from the source.