Data Science Dojo

JULY 6, 2023

Data engineering tools offer a range of features and functionalities, including data integration, data transformation, data quality management, workflow orchestration, and data visualization. Essential data engineering tools for 2023 Top 10 data engineering tools to watch out for in 2023 1.

Data Engineering 195

Data Engineering Data Engineer Data Engineering Data Engineering 195

ODSC - Open Data Science

JUNE 7, 2023

To make your data management processes easier, here’s a primer on data lakes, and our picks for a few data lake vendors worth considering. What is a data lake? First, a data lake is a centralized repository that allows users or an organization to store and analyze large volumes of data.

Data Lakes 52

Data Lakes Azure Data Warehouse Hadoop 52

phData

NOVEMBER 8, 2024

Note : Cloud Data warehouses like Snowflake and Big Query already have a default time travel feature. However, this feature becomes an absolute must-have if you are operating your analytics on top of your data lake or lakehouse. It can also be integrated into major data platforms like Snowflake.

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Data Lakes Data Warehouse Database Azure 52

DagsHub

DECEMBER 11, 2023

A complete overview revealing a diverse range of strengths and weaknesses for each data versioning tool. However, these tools have functional gaps for more advanced data workflows. Reference diagram of lakeFS (Source: official documentation ) Strengths It works with all data formats without requiring any changes from the user side.

Machine Learning 98

Machine Learning Machine Learning Data Lakes Database 98

Precisely

JANUARY 19, 2023

In 2023 and beyond, we expect the open source trend to continue, with steady growth in the adoption of tools like Feilong, Tessla, Consolez, and Zowe. Platforms like Hadoop and Spark prompted many companies to begin thinking about big data differently than they had in the past.

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AWS Cloud Computing Data Pipeline Big Data 52

IBM Journey to AI blog

SEPTEMBER 25, 2023

Uber understood that digital superiority required the capture of all their transactional data, not just a sampling. They stood up a file-based data lake alongside their analytical database. Because much of the work done on their data lake is exploratory in nature, many users want to execute untested queries on petabytes of data.

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Data Lakes Analytics Analytics Clustering 102

phData

SEPTEMBER 20, 2023

This blog was originally written by Keith Smith and updated for 2023 by Nick Goble & Dominick Rocco. You’ve probably heard of the Snowflake Data Cloud , but did you know that Snowflake also offers a revolutionary set of libraries and runtimes called Snowpark?

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SQL Python Data Lakes Machine Learning 98