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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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Exploring the Power of Microsoft Fabric: A Hands-On Guide with a Sales Use Case

Data Science Dojo

These experiences facilitate professionals from ingesting data from different sources into a unified environment and pipelining the ingestion, transformation, and processing of data to developing predictive models and analyzing the data by visualization in interactive BI reports. Choose a visual of interest.

Power BI 233
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How to Optimize Power BI and Snowflake for Advanced Analytics

phData

How to Optimize Power BI and Snowflake for Advanced Analytics Spencer Baucke May 25, 2023 The world of business intelligence and data modernization has never been more competitive than it is today. Table of Contents Why Discuss Snowflake & Power BI?

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Sneak peek at Microsoft Fabric price and its promising features

Dataconomy

Microsoft Fabric combines multiple elements into a single platform – Image courtesy of Microsoft The contribution of Power BI The integration of Microsoft Power BI and Microsoft Fabric offers a powerful combination for organizations seeking comprehensive data analytics and insights.

Power BI 194
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CI/CD für Datenpipelines – Ein Game-Changer mit AnalyticsCreator

Data Science Blog

Die Bedeutung effizienter und zuverlässiger Datenpipelines in den Bereichen Data Science und Data Engineering ist enorm. Es bietet vollständige Automatisierung des BI-Stacks und unterstützt ein breites Spektrum an Data Warehouses, analytischen Datenbanken und Frontends.

Azure 130
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How to Change Data Sources in Power BI

phData

In a perfect scenario, everything a data analyst would need to answer business users’ questions would live in cleaned, curated, and modeled tables in a data warehouse. The analyst could connect to the data warehouse and start developing reports. M is the formula language behind the scenes of Power Query.

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Ist Process Mining in Summe zu teuer?

Data Science Blog

Unabhängiges und Nachhaltiges Data Engineering Die Arbeit hinter Process Mining kann man sich wie einen Eisberg vorstellen. Diese AI ist in noch keiner Process Mining Software zu finden, kann jedoch bausteinartig dem Process Mining Data Warehouse vorgeschaltet werden.