Smart Data Collective

OCTOBER 17, 2022

In fact, you may have even heard about IDC’s new Global DataSphere Forecast, 2021-2025 , which projects that global data production and replication will expand at a compound annual growth rate of 23% during the projection period, reaching 181 zettabytes in 2025. zettabytes of data in 2020, a tenfold increase from 6.5

Big Data 119

Big Data Big Data Data Engineering Data Engineering 119

IBM Data Science in Practice

MARCH 8, 2023

Hidden Technical Debt in Machine Learning Systems More money, more problems — Rise of too many ML tools 2012 vs 2023 — Source: Matt Turck People often believe that money is the solution to a problem. A feature platform should automatically process the data pipelines to calculate that feature. Spark, Flink, etc.)

Machine Learning 264

Machine Learning Machine Learning ML ML 264

AWS Machine Learning Blog

SEPTEMBER 11, 2024

Around this time, industry observers reported NVIDIA’s strategy pivoting from its traditional gaming and graphics focus to moving into scientific computing and data analytics. in 2012 is now widely referred to as ML’s “Cambrian Explosion.” An important part of the data pipeline is the production of features, both online and offline.

AWS 115

AWS ML ML Clustering 115

Flipboard

MARCH 21, 2025

To establish trust between the data producers and data consumers, SageMaker Catalog also integrates the data quality metrics and data lineage events to track and drive transparency in data pipelines.

SQL 136

SQL Data Analyst Data Warehouse AWS 136

AWS Machine Learning Blog

OCTOBER 24, 2024

Data pipelines must seamlessly integrate new data at scale. Diverse data amplifies the need for customizable cleaning and transformation logic to handle the quirks of different sources. You can build and manage an incremental data pipeline to update embeddings on Vectorstore at scale.

AWS 123

AWS Data Pipeline Database Big Data 123