Remove 2012 Remove Data Engineering Remove Data Warehouse
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CI/CD for Data Pipelines: A Game-Changer with AnalyticsCreator

Data Science Blog

Continuous Integration and Continuous Delivery (CI/CD) for Data Pipelines: It is a Game-Changer with AnalyticsCreator! The need for efficient and reliable data pipelines is paramount in data science and data engineering. It offers full BI-Stack Automation, from source to data warehouse through to frontend.

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Process Mining – Ist Celonis wirklich so gut? Ein Praxisbericht.

Data Science Blog

Process Mining Tools, die als pure Process Mining Software gestartet sind Hierzu gehört Celonis, das drei-köpfige und sehr geschäftstüchtige Gründer-Team, das ich im Jahr 2012 persönlich kennenlernen durfte. Reduzierte Personalkosten , sind oft dann gegeben, wenn interne Data Engineers verfügbar sind, die die Datenmodelle intern entwickeln.

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How The Explosive Growth Of Data Access Affects Your Engineer’s Team Efficiency

Smart Data Collective

In fact, you may have even heard about IDC’s new Global DataSphere Forecast, 2021-2025 , which projects that global data production and replication will expand at a compound annual growth rate of 23% during the projection period, reaching 181 zettabytes in 2025. zettabytes of data in 2020, a tenfold increase from 6.5

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Import data from Google Cloud Platform BigQuery for no-code machine learning with Amazon SageMaker Canvas

AWS Machine Learning Blog

The workflow includes the following steps: Within the SageMaker Canvas interface, the user composes a SQL query to run against the GCP BigQuery data warehouse. SageMaker Canvas relays this query to Athena, which acts as an intermediary service, facilitating the communication between SageMaker Canvas and BigQuery.

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Super charge your LLMs with RAG at scale using AWS Glue for Apache Spark

AWS Machine Learning Blog

An AI technique called embedding language models converts this external data into numerical representations and stores it in a vector database. RAG introduces additional data engineering requirements: Scalable retrieval indexes must ingest massive text corpora covering requisite knowledge domains.

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