Data Science Blog

MAY 20, 2024

It supports a holistic data model, allowing for rapid prototyping of various models. It also supports a wide range of data warehouses, analytical databases, data lakes, frontends, and pipelines/ETL. Data Lakes : It supports MS Azure Blob Storage. pipelines, Azure Data Bricks.

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Data Pipeline Data Warehouse Azure Data Lakes 262

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. As our customers increasingly adopt the cloud, we continue to make investments that ensure they can access their data anywhere.

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Azure Tableau Data Lakes SQL 102

Data Science Dojo

JULY 6, 2023

Data engineering tools are software applications or frameworks specifically designed to facilitate the process of managing, processing, and transforming large volumes of data. It allows data engineers to define and manage complex workflows as directed acyclic graphs (DAGs).

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Data Engineering Data Engineering Data Engineering Data Engineer 195

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. As our customers increasingly adopt the cloud, we continue to make investments that ensure they can access their data anywhere.

Azure 52

Azure Tableau Data Lakes SQL 52

Women in Big Data

OCTOBER 9, 2024

A traditional data pipeline is a structured process that begins with gathering data from various sources and loading it into a data warehouse or data lake. Once ingested, the data is prepared through filtering, error correction, and restructuring for ease of use.

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Big Data Big Data Apache Kafka Data Pipeline 59

Alation

FEBRUARY 20, 2020

Data lakes, while useful in helping you to capture all of your data, are only the first step in extracting the value of that data.

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Data Lakes ETL Data Analyst Data Preparation 40

Pickl AI

JANUARY 28, 2025

Data Integration Once data is collected from various sources, it needs to be integrated into a cohesive format. Data Quality Management : Ensures that the integrated data is accurate, consistent, and reliable for analysis. This can involve: Data Warehouses: These are optimized for query performance and reporting.

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Business Intelligence Business Intelligence ETL Data Lakes 52