Alation

FEBRUARY 12, 2020

At the time LinkedIn embarked on its data catalog journey, it had 50 thousand datasets, 15 petabytes of storage (across Teradata, Hadoop, and other data sources), 14 thousand comments, and 35 million job executions. Download White Paper. Subscribe to Alation's Blog.

Machine Learning 52

Machine Learning Machine Learning Analytics Analytics 52

DagsHub

DECEMBER 11, 2023

Released in 2022, DagsHub’s Direct Data Access (DDA for short) allows Data Scientists and Machine Learning engineers to stream files from DagsHub repository without needing to download them to their local environment ahead of time. This can prevent lengthy data downloads to the local disks before initiating their mode training.

Machine Learning 98

Machine Learning Machine Learning Data Lakes Data Science 98

Pickl AI

NOVEMBER 4, 2024

To get started, download the Anaconda installer from the official Anaconda website and follow the installation instructions for your operating system. Additionally, learn about data storage options like Hadoop and NoSQL databases to handle large datasets. Once Anaconda is installed, launch the Anaconda Navigator.

Data Science 52

Data Science Python Machine Learning Machine Learning 52

AWS Machine Learning Blog

APRIL 19, 2024

This notebook will download a publicly available slide deck , convert each slide into the JPG file format, and upload these to the S3 bucket. Prior to joining AWS, Archana led a migration from traditional siloed data sources to Hadoop at a healthcare company. We run these notebooks one by one. I need numbers." get('hits')[0].get('_source').get('image_path')

AWS 130

AWS ML ML Database 130

AWS Machine Learning Blog

MAY 16, 2024

With Amazon EMR, which provides fully managed environments like Apache Hadoop and Spark, we were able to process data faster. The data preprocessing batches were created by writing a shell script to run Amazon EMR through AWS Command Line Interface (AWS CLI) commands, which we registered to Airflow to run at specific intervals.

AWS 131

AWS ML ML Deep Learning 131

Pickl AI

AUGUST 21, 2024

Data Extraction: Scraping tools or scripts download the HTML content of the selected pages. Apache Nutch A powerful web crawler built on Apache Hadoop, suitable for large-scale data crawling projects. Nutch is often used in conjunction with other Hadoop tools for big data processing.

Apache Hadoop 52

Apache Hadoop Hadoop Database Data Quality 52

DagsHub

OCTOBER 23, 2024

Popular data lake solutions include Amazon S3 , Azure Data Lake , and Hadoop. Apache Hadoop Apache Hadoop is an open-source framework that supports the distributed processing of large datasets across clusters of computers. Data Processing Tools These tools are essential for handling large volumes of unstructured data.

Machine Learning 52

Machine Learning Machine Learning Data Lakes AI 52

Pickl AI

MARCH 11, 2025

Software as a Service (SaaS) : Services like Gmail, Zoom, and Dropbox let you use applications online without downloading them. It supports Big Data tools like Hadoop and Spark, allowing businesses to scale analytics operations efficiently. Google App Engine is an example. The Cloud Computing market is growing rapidly.

Cloud Computing 52

Cloud Computing Big Data Big Data Big Data Analytics 52

Heartbeat

JULY 31, 2023

Comet’s data management feature allows users to manage their training data, including downloading, storing, and preprocessing data. Comet also integrates with popular data storage and processing tools like Amazon S3, Google Cloud Storage, and Hadoop.

Machine Learning 52

Machine Learning Machine Learning Deep Learning Deep Learning 52

The MLOps Blog

JANUARY 23, 2023

When we download a Git repository, we also get the.dvc files which we use to download the data associated with them. LakeFS is fully compatible with many ecosystems of data engineering tools such as AWS, Azure, Spark, Databrick, MlFlow, Hadoop and others. Also, this file is meant to be stored with code in GitHub.

ML 52

ML ML Data Lakes Machine Learning 52

phData

OCTOBER 20, 2023

It is specifically designed to work seamlessly with Hadoop and other big data processing frameworks. This file format is optimized for use with Hadoop and other big data processing frameworks and is highly compressed, offering excellent performance for batch processing and interactive querying.

Big Data 40

Big Data Big Data Database Hadoop 40