erwin

JUNE 7, 2022

This blog is based upon webcast which can be watched here. As with the part 1 of this blog series, the cloud is not nirvana. As we’ve seen in this blog, data modeling for a data warehouse is very different from doing one for an OLTP system. Related links: Like this blog? Like this blog? Business Focus. Operational.

Data Warehouse 52

Data Warehouse Modeling Sales Data Lake 52

Jet Global

APRIL 30, 2019

In this blog post, we are going to cover Data Entities. You also get a pre-built data warehouse and cubes (tabular or OLAP) that uses these data entities to de-normalize the tables and keep all your governed data in one place. What is a Data Entity? A data entity is an extract of core data from your D365FO system.

Finance 73

Finance OLAP Reporting Data Warehouse 73

Sisense

AUGUST 11, 2019

BI lets you apply chosen metrics to potentially huge, unstructured datasets, and covers querying, data mining , online analytical processing ( OLAP ), and reporting as well as business performance monitoring, predictive and prescriptive analytics. For your business to thrive, you need to know what’s working, what’s not, and how to improve.

Business Intelligence 75

Business Intelligence Business Analytics Analytics OLAP 75

Sisense

NOVEMBER 12, 2020

Data warehouse vs. databases Traditional vs. Cloud Explained Cloud data warehouses in your data stack A data-driven future powered by the cloud. We live in a world of data: There’s more of it than ever before, in a ceaselessly expanding array of forms and locations. The primary differentiator is the data workload they serve.

Data Warehouse 52

Data Warehouse Data Lake OLAP Data-driven 52

Ontotext

JUNE 10, 2021

To handle such scenarios you need a transalytical graph database – a database engine that can deal with both frequent updates (OLTP workload) as well as with graph analytics (OLAP). Not Every Graph is a Knowledge Graph: Schemas and Semantic Metadata Matter.

Metadata 119

Metadata Cost-Benefit OLAP Modeling 119

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

BizAcuity

AUGUST 1, 2022

TIBCO Jaspersoft offers a complete BI suite that includes reporting, online analytical processing (OLAP), visual analytics , and data integration. Online Analytical Processing (OLAP). The web-scale platform enables users to share interactive dashboards and data from a single page with individuals across the enterprise. Ad Hoc Analysis.

Reporting 52

Reporting OLAP Online Analytical Processing Dashboards 52

IBM Big Data Hub

SEPTEMBER 27, 2023

Get a fast track to clarity: Single view with near real-time visibility and interactive dashboards QRadar Log Insights uses a modern open-source OLAP data warehouse, ClickHouse, which ingests, automatically indexes, searches and analyzes large datasets at sub-second speed.

Cost-Benefit 103

Cost-Benefit OLAP Dashboards Visualization 103

Sisense

FEBRUARY 16, 2021

Data warehouses provide a consolidated, multidimensional view of data along with online analytical processing ( OLAP ) tools. OLAP tools help in the interactive and effective processing of data in a multidimensional space. Every aspect of analytics is powered by a data model.

Modeling 52

Modeling OLAP Data Warehouse Cost-Benefit 52

BizAcuity

APRIL 1, 2023

The BI infrastructure: This includes designing and implementing data warehouses, data lakes, data marts, and OLAP cubes along with data mining, and modeling. And as a result, the number of KPIs being tracked are subjected to increase over time. The BI infrastructure can prove to be quite expensive if not done right.

Business Intelligence 52

Business Intelligence Consulting KPI Data Warehouse 52

BizAcuity

JANUARY 31, 2023

The BI infrastructure: This includes designing and implementing data warehouses, data lakes, data marts, and OLAP cubes along with data mining, and modeling. And as a result, the number of KPIs being tracked are subjected to increase over time. The BI infrastructure can prove to be quite expensive if not done right.

Business Intelligence 52

Business Intelligence Consulting KPI Data Warehouse 52

DataRobot Blog

MAY 14, 2018

by Jen Underwood. Recently I engaged in a guided “hands-on” evaluation of Infoworks, a “no code” big data engineering solution that expedites and automates Hadoop and cloud workflows. Within four hours of logging. Read More.

Big Data 40

Big Data OLAP IoT 40

Jen Stirrup

OCTOBER 30, 2022

” Data mining is particularly useful when it can be applied to customer insight, and this blog will aim to apply DM to customer insight. One particular technology which is good for summarising and aggregating data is called OLAP (On Line Analytical Processing). Customer insight is a cornerstone of the activity of any business.

Data mining 52

Data mining Predictive Analytics Cost-Benefit OLAP 52

IBM Big Data Hub

SEPTEMBER 25, 2023

This blog takes you on a journey into the world of Uber’s analytics and the critical role that Presto, the open source SQL query engine, plays in driving their success. The post Unleashing the power of Presto: The Uber case study appeared first on IBM Blog. EMA Technical Case Study, sponsored by Ahana.

OLAP 92

OLAP Data Lake Data-driven Snapshot 92