IBM Journey to AI blog

FEBRUARY 2, 2023

In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. The rise of cloud has allowed data warehouses to provide new capabilities such as cost-effective data storage at petabyte scale, highly scalable compute and storage, pay-as-you-go pricing and fully managed service delivery.

Data Warehouse 58

Data Warehouse Cloud Data Analytics Analytics 58

Pickl AI

NOVEMBER 15, 2023

Discover the nuanced dissimilarities between Data Lakes and Data Warehouses. Data management in the digital age has become a crucial aspect of businesses, and two prominent concepts in this realm are Data Lakes and Data Warehouses. It acts as a repository for storing all the data.

Data Lakes 52

Data Lakes Data Warehouse Database ETL 52

AWS Machine Learning Blog

DECEMBER 29, 2022

Many of the RStudio on SageMaker users are also users of Amazon Redshift , a fully managed, petabyte-scale, massively parallel data warehouse for data storage and analytical workloads. It makes it fast, simple, and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools.

AWS 140

AWS Machine Learning Machine Learning Clustering 140

Dataconomy

APRIL 27, 2023

Conversely, OLAP systems are optimized for conducting complex data analysis and are designed for use by data scientists, business analysts, and knowledge workers. OLAP systems support business intelligence, data mining, and other decision support applications. An OLAP database may also be organized as a data warehouse.

Database 159

Database Data Scientist Data Mining Data Mining 159

Alation

MARCH 29, 2022

The 1980s ushered in the antithesis of this version of computing — personal computing and distributed database management — but also introduced duplicated data and enterprise data silos. During the 1990s, attempts were made to tackle challenges including: Inefficient data silos.

Business Intelligence 96

Business Intelligence Business Intelligence Data Silos Citizen Data Scientist 96

Dataconomy

APRIL 6, 2023

While data democratization has many benefits, such as improved decision-making and enhanced innovation, it also presents a number of challenges. From lack of data literacy to data silos and security concerns, there are many obstacles that organizations need to overcome in order to successfully democratize their data.

Data Governance 118

Data Governance Data Silos Data Analysis Data Analysis 118

Pickl AI

OCTOBER 6, 2024

It is a crucial data integration process that involves moving data from multiple sources into a destination system, typically a data warehouse. This process enables organisations to consolidate their data for analysis and reporting, facilitating better decision-making. ETL stands for Extract, Transform, and Load.

ETL 52

ETL Data Warehouse Data Quality Data Lakes 52