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 144

Data mining Data-driven Statistics OLAP 144

Jet Global

OCTOBER 7, 2020

Confusing matters further, Microsoft has also created something called the Data Entity Store, which serves a different purpose and functions independently of data entities. The Data Entity Store is an internal data warehouse that is only available to embedded Power BI reports (not the full version of Power BI).

Data Warehouse 90

Data Warehouse OLAP Reporting Finance 90

AWS Big Data

MARCH 7, 2023

Data lakes are more focused around storing and maintaining all the data in an organization in one place. And unlike data warehouses, which are primarily analytical stores, a data hub is a combination of all types of repositories—analytical, transactional, operational, reference, and data I/O services, along with governance processes.

Analytics 71

Analytics Data Warehouse Data Lake Metadata 71

erwin

AUGUST 15, 2022

I was pricing for a data warehousing project with just 4 TBs of data, small by today’s standards. I chose “ON Demand” for up to 64 virtual CPUs and 448 GB of memory since I wanted this data warehouse to fit entirely, or at least mostly, within memory. Figure 1: Pricing for a 4 TB data warehouse in AWS.

Data Lake 52

Data Lake Modeling Unstructured Data Data Warehouse 52

Jet Global

APRIL 30, 2019

There are 5 categories of data entities based on their functions and the type of data that they serve: Parameter (Ex. Document (Ex. In D365FO, ad hoc reporting requires you to take the data out of D365FO and put it in de-normalized data entities. General ledger). Reference (Ex. Tax Codes). Master (Ex. Customers).

Finance 73

Finance OLAP Reporting Data Warehouse 73

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

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