Remove 2023 Remove Data Transformation Remove Data Warehouse
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Top 10 Data Pipeline Interview Questions to Read in 2023

Analytics Vidhya

A well-designed data pipeline can help organizations extract valuable insights from their data, automate tedious manual processes, and ensure the accuracy of data processing.

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SAP Datasphere Powers Business at the Speed of Data

Rocket-Powered Data Science

In fact, by putting a single label like AI on all the steps of a data-driven business process, we have effectively not only blurred the process, but we have also blurred the particular characteristics that make each step separately distinct, uniquely critical, and ultimately dependent on specialized, specific technologies at each step.

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BMW Cloud Efficiency Analytics powered by Amazon QuickSight and Amazon Athena

AWS Big Data

The dashboards, which offer a holistic view together with a variety of cost and BMW Group-related dimensions, were successfully launched in May 2023 and became accessible to users within the BMW Group. The difference lies in when and where data transformation takes place.

Analytics 111
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Exploring the AI and data capabilities of watsonx

IBM Big Data Hub

It is supported by querying, governance, and open data formats to access and share data across the hybrid cloud. Through workload optimization across multiple query engines and storage tiers, organizations can reduce data warehouse costs by up to 50 percent.

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Tackling AI’s data challenges with IBM databases on AWS

IBM Big Data Hub

  Redefining cloud database innovation: IBM and AWS In late 2023, IBM and AWS jointly announced the general availability of Amazon relational database service (RDS) for Db2.  With Db2 Warehouse’s fully managed cloud deployment on AWS, enjoy no overhead, indexing, or tuning and automated maintenance.

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Unified Data Clears the Roadblocks of Your Hybrid Cloud Journey

Jet Global

Accept and Address the Financial Impact of Cloud Adoption, 2023 Download Now Hybrid ERP – The Best of Both Worlds? It streamlines data integration, ensures real-time access to accurate information, enhances collaboration, and provides the flexibility needed to adapt to evolving ERP systems and business requirements.

Finance 52
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How BMW Group built a serverless terabyte-scale data transformation architecture with dbt and Amazon Athena

AWS Big Data

While enabling organization-wide efficiency, the team also applied these principles to the data architecture, making sure that CLEA itself operates frugally. After evaluating various tools, we built a serverless data transformation pipeline using Amazon Athena and dbt. The Source stage maintains raw data in its original form.