Data Virtualization

MAY 5, 2020

Bring any data to any data consumer, simply and easily: that’s the goal of data virtualization. Yet contrary to what may first come to mind, data consumers are more than simply BI, analytics, or data science applications. Just about every.

Data Science 52

Data Science Analytics OLAP Optimization 52

Sisense

SEPTEMBER 3, 2019

This blog is intended to give an overview of the considerations you’ll want to make as you build your Redshift data warehouse to ensure you are getting the optimal performance. OLTP vs OLAP. First, we’ll dive into the two types of databases: OLAP (Online Analytical Processing) and OLTP (Online Transaction Processing).

Data Warehouse 78

Data Warehouse OLAP Statistics Cost-Benefit 78

AWS Big Data

OCTOBER 18, 2023

Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse that provides the flexibility to use provisioned or serverless compute for your analytical workloads. You can get faster insights without spending valuable time managing your data warehouse. Fault tolerance is built in. Choose Create workgroup.

Analytics 97

Analytics Data Warehouse Testing Dashboards 97

CIO Business Intelligence

JANUARY 20, 2023

Improved employee satisfaction: Providing business users access to data without having to contact analysts or IT can reduce friction, increase productivity, and facilitate faster results. Increased competitive advantage: A sound BI strategy can help businesses monitor their changing market and anticipate customer needs.

Business Intelligence 144

Business Intelligence Dashboards Data mining OLAP 144

Domino Data Lab

JULY 2, 2019

In other words, using metadata about data science work to generate code. In this case, code gets generated for data preparation, where so much of the “time and labor” in data science work is concentrated. The approach they’ve used applies to other popular data science APIs such as NumPy , Tensorflow , and so on.

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

Jet Global

MAY 28, 2019

Whether the reporting is being done by an end user, a data science team, or an AI algorithm, the future of your business depends on your ability to use data to drive better quality for your customers at a lower cost. So, when it comes to collecting, storing, and analyzing data, what is the right choice for your enterprise?

Data Warehouse 85

Data Warehouse Reporting Business Intelligence Sales 85

IBM Big Data Hub

SEPTEMBER 25, 2023

They set up a couple of clusters and began processing queries at a much faster speed than anything they had experienced with Apache Hive, a distributed data warehouse system, on their data lake. Uber chose Presto for the flexibility it provides with compute separated from data storage.

OLAP 87

OLAP Data Lake Data-driven Snapshot 87