IBM Journey to AI blog

AUGUST 12, 2024

Wearable devices (such as fitness trackers, smart watches and smart rings) alone generated roughly 28 petabytes (28 billion megabytes) of data daily in 2020. And in 2024, global daily data generation surpassed 402 million terabytes (or 402 quintillion bytes). Massive, in fact.

Big Data 106

Big Data Big Data ML ML 106

DataRobot Blog

APRIL 1, 2018

This shift is driving a hybrid data integration mentality, where business teams are given curated data sandboxes so they can participate in building future use cases such as mobile applications, B2B solutions, or IoT analytics. DataRobot Data Prep. 3) The emergence of a new enterprise information management platform. Free Trial.

Analytics 40

Analytics Analytics Data Preparation Augmented Analytics 40

AWS Machine Learning Blog

SEPTEMBER 11, 2024

In 2018, other forms of PBAs became available, and by 2020, PBAs were being widely used for parallel problems, such as training of NN. Historical data is normally (but not always) independent inter-day, meaning that days can be parsed independently. All the way through this pipeline, activities could be accelerated using PBAs.

AWS 117

AWS ML ML Clustering 117

Snorkel AI

MAY 26, 2023

What’s really important in the before part is having production-grade machine learning data pipelines that can feed your model training and inference processes. And that’s really key for taking data science experiments into production. And this is not just us saying it.

SQL 52

SQL ML ML Python 52

Snorkel AI

MAY 26, 2023

What’s really important in the before part is having production-grade machine learning data pipelines that can feed your model training and inference processes. And that’s really key for taking data science experiments into production. And this is not just us saying it.

SQL 52

SQL ML ML Python 52

Kaggle

JULY 29, 2020

David: My technical background is in ETL, data extraction, data engineering and data analytics. I spent over a decade of my career developing large-scale data pipelines to transform both structured and unstructured data into formats that can be utilized in downstream systems.

ETL 71

ETL Data Scientist Data Science Machine Learning 71