IBM Big Data Hub

APRIL 15, 2024

Or we create a data lake, which quickly degenerates to a data swamp. Generative AI makes other AI and analytics technologies more consumable, which helps manufacturing enterprises realize the value of their investments. Or we keep adding applications, so our technical debt continues to increase.

Manufacturing 97

Manufacturing Contextual Data Knowledge Discovery Data Lake 97

Sisense

JANUARY 13, 2020

From a practical perspective, the computerization and automation of manufacturing hugely increase the data that companies acquire. And cloud data warehouses or data lakes give companies the capability to store these vast quantities of data. How data enhances product development.

Manufacturing 52

Manufacturing Data Lake Big Data Data Warehouse 52

datapine

AUGUST 29, 2022

The saying “knowledge is power” has never been more relevant, thanks to the widespread commercial use of big data and data analytics. The rate at which data is generated has increased exponentially in recent years. Essential Big Data And Data Analytics Insights. trillion each year.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

CIO Business Intelligence

MARCH 9, 2022

But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI. Traditional data warehouses, for example, support datasets from multiple sources but require a consistent data structure.

Data Lake 115

Data Lake Unstructured Data Data Warehouse Data Quality 115

AWS Big Data

NOVEMBER 30, 2023

With AWS Glue, you can discover and connect to more than 100 diverse data sources and manage your data in a centralized data catalog. You can visually create, run, and monitor extract, transform, and load (ETL) pipelines to load data into your data lakes. About the Authors Kamen Sharlandjiev is a Sr.

IT 100

IT Visualization Machine Learning Data Integration 100

Alation

FEBRUARY 13, 2020

“We hear little about initiatives devoted to changing human attitudes and behaviors around data. Unless the focus shifts to these types of activities, we are likely to see the same problem areas in the future that we’ve observed year after year in this survey.” — Big Data and AI Executive Survey 2019.

Digital Transformation 59

Digital Transformation Insurance Data-driven Machine Learning 59

Cloudera

NOVEMBER 22, 2021

In addition, data pipelines include more and more stages, thus making it difficult for data engineers to compile, manage, and troubleshoot those analytical workloads. Increased integration costs using different loose or tight coupling approaches between disparate analytical technologies and hosting environments.

Data Processing 88

Data Processing Data Warehouse Enterprise Visualization 88