Azure ETL Tableau 
Data Science Blog
MAY 20, 2024
It also supports a wide range of data warehouses, analytical databases, data lakes, frontends, and pipelines/ETL. Support for Various Data Warehouses and Databases : AnalyticsCreator supports MS SQL Server 2012-2022, Azure SQL Database, Azure Synapse Analytics dedicated, and more. Data Lakes : It supports MS Azure Blob Storage.
Tableau
MARCH 30, 2021
In Tableau 2021.1, we’ve added new connectors to help our customers access more data in Azure than ever before: an Azure SQL Database connector and an Azure Data Lake Storage Gen2 connector. Our customers leverage various different services in Azure to store and manage their data. Azure Data Lake Storage Gen2.
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Data Science Dojo
OCTOBER 31, 2024
Key Skills Proficiency in SQL is essential, along with experience in data visualization tools such as Tableau or Power BI. Strong analytical skills and the ability to work with large datasets are critical, as is familiarity with data modeling and ETL processes.
Data Science Blog
JULY 20, 2024
Vielfältige Unterstützung: Kompatibel mit verschiedenen Datenbankmanagementsystemen wie MS SQL Server und Azure Synapse Analytics. Data Lakes: Unterstützt MS Azure Blob Storage. Frontends : Kompatibel mit Tools wie Power BI, Qlik Sense und Tableau.
Tableau
MARCH 29, 2021
In Tableau 2021.1, we’ve added new connectors to help our customers access more data in Azure than ever before: an Azure SQL Database connector and an Azure Data Lake Storage Gen2 connector. Our customers leverage various different services in Azure to store and manage their data. Azure Data Lake Storage Gen2.
Data Science Dojo
JULY 3, 2024
Tools like Tableau, Power BI, and Python libraries such as Matplotlib and Seaborn are commonly taught. Data Engineering : Building and maintaining data pipelines, ETL (Extract, Transform, Load) processes, and data warehousing. R : Often used for statistical analysis and data visualization.
ODSC - Open Data Science
APRIL 3, 2023
Data Wrangling: Data Quality, ETL, Databases, Big Data The modern data analyst is expected to be able to source and retrieve their own data for analysis. Competence in data quality, databases, and ETL (Extract, Transform, Load) are essential. Cloud Services: Google Cloud Platform, AWS, Azure.
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