Jet Global

APRIL 19, 2021

This puts tremendous stress on the teams managing data warehouses, and they struggle to keep up with the demand for increasingly advanced analytic requests. To gather and clean data from all internal systems and gain the business insights needed to make smarter decisions, businesses need to invest in data warehouse automation.

Data Warehouse 98

Data Warehouse Cost-Benefit OLAP Business Intelligence 98

AWS Big Data

FEBRUARY 28, 2023

Amazon Redshift is a fully managed, petabyte-scale, massively parallel data warehouse that makes it fast, simple, and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools. This will allow for a smoother migration of OLAP workloads, with minimal rewrites.

Online Analytical Processing 75

Online Analytical Processing OLAP Slice and Dice Analytics 75

CIO Business Intelligence

NOVEMBER 14, 2022

A DSS leverages a combination of raw data, documents, personal knowledge, and/or business models to help users make decisions. The data sources used by a DSS could include relational data sources, cubes, data warehouses, electronic health records (EHRs), revenue projections, sales projections, and more.

Data mining 128

Data mining Data-driven Statistics OLAP 128

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.

Analytics 96

Analytics Data Warehouse Testing Dashboards 96

Jet Global

OCTOBER 22, 2020

Microsoft’s launch of the Power BI platform several years ago marked the company’s entrance into an important space within the business applications market. As the Microsoft Dynamics ERP products transition to a cloud-first model, Microsoft has positioned Power BI as the future of business intelligence for its Dynamics family of products.

Modeling 52

Modeling OLAP Reporting Sales 52

Sisense

FEBRUARY 16, 2021

Data warehouses have become intensely important in the modern business world. For many organizations, it’s not uncommon for all their data to be extracted, loaded unchanged into data warehouses, and then transformed via cleaning, merging, aggregation, etc. Jinja’s important features.

Modeling 52

Modeling OLAP Data Warehouse Cost-Benefit 52

Smarten

JANUARY 4, 2018

Extract, Transform and Load (ETL) refers to a process of connecting to data sources, integrating data from various data sources, improving data quality, aggregating it and then storing it in staging data source or data marts or data warehouses for consumption of various business applications including BI, Analytics and Reporting.

Data Warehouse 40

Data Warehouse OLAP Data Governance Optimization 40