Remove 2022 Remove Azure Remove Data Lakes
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CI/CD for Data Pipelines: A Game-Changer with AnalyticsCreator

Data Science Blog

It offers full BI-Stack Automation, from source to data warehouse through to frontend. 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. pipelines, Azure Data Bricks.

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Best 8 Data Version Control Tools for Machine Learning 2024

DagsHub

DagsHub DagsHub is a centralized Github-based platform that allows Machine Learning and Data Science teams to build, manage and collaborate on their projects. In addition to versioning code, teams can also version data, models, experiments and more. However, these tools have functional gaps for more advanced data workflows.

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Databricks’ Data+AI Summit 2022: A Show of Partner “Unity”

Alation

Are your data users overwhelmed by silos and frustrated by untrusted data? Tell them to grab a catalog … and go jump in a lake. That was the message — delivered a little more elegantly than that — at Databricks’ Data+AI Summit 2022. A simple model to control access to data via a UI or SQL. and much more!

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Introduction to Power BI Datamarts

ODSC - Open Data Science

Microsoft announced the public preview availability of Datamarts in May 2022. The Datamarts capability opens endless possibilities for organizations to achieve their data analytics goals on the Power BI platform. Power BI Datamarts provide no-code/low-code datamart capabilities using Azure SQL Database technology in the background.

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What Are The Best Third-Party Data Ingestion Tools For Snowflake?

phData

If using a network policy with Snowflake, be sure to add Fivetran’s IP address list , which will ensure Azure Data Factory (ADF) Azure Data Factory is a fully managed, serverless data integration service built by Microsoft. Fivetran works with all three Snowflake cloud providers.

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Top Data Analytics Skills and Platforms for 2023

ODSC - Open Data Science

Data analysts often must go out and find their data, process it, clean it, and get it ready for analysis. This pushes into Big Data as well, as many companies now have significant amounts of data and large data lakes that need analyzing. Cloud Services: Google Cloud Platform, AWS, Azure.

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Discover the Most Important Fundamentals of Data Engineering

Pickl AI

As organisations increasingly rely on data to drive decision-making, understanding the fundamentals of Data Engineering becomes essential. The global Big Data and Data Engineering Services market, valued at USD 51,761.6 million in 2022, is projected to grow at a CAGR of 18.15% , reaching USD 140,808.0