Jet Global

OCTOBER 22, 2020

Power BI provides users with some very nice dashboarding and reporting capabilities. Unfortunately, it also introduces a mountain of complexity into the reporting process. OLAP Cubes vs. Tabular Models. Let’s begin with an overview of how data analytics works for most business applications. The first is an OLAP model.

Modeling 52

Modeling OLAP Reporting Sales 52

Jet Global

SEPTEMBER 4, 2020

Data warehouses gained momentum back in the early 1990s as companies dealing with growing volumes of data were seeking ways to make analytics faster and more accessible. Online analytical processing (OLAP), which enabled users to quickly and easily view data along different dimensions, was coming of age.

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

Sisense

SEPTEMBER 3, 2019

OLTP vs OLAP. First, we’ll dive into the two types of databases: OLAP (Online Analytical Processing) and OLTP (Online Transaction Processing). An OLAP database is best for situations where you read from the database more often than you write to it. Redshift is a type of OLAP database.

Data Warehouse 78

Data Warehouse OLAP Statistics Cost-Benefit 78

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. See an example: Explore Dashboard. Confused yet?

Business Intelligence 75

Business Intelligence Business Analytics Analytics OLAP 75

Jet Global

AUGUST 14, 2019

The optimized data warehouse isn’t simply a number of relational databases cobbled together, however—it’s built on modern data storage structures such as the Online Analytical Processing (or OLAP) cubes. So how is the data extracted?

Enterprise 70

Enterprise OLAP Business Intelligence Cost-Benefit 70

Jet Global

APRIL 20, 2020

This practice, together with powerful OLAP (online analytical processing) tools, grew into a body of practice that we call “business intelligence.” A few decades ago, technology professionals developed methods for collecting, aggregating, and staging their most important information into data warehouses.

Business Intelligence 78

Business Intelligence Finance Data Warehouse OLAP 78

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. Live models run queries directly against the data source.

Modeling 52

Modeling OLAP Data Warehouse Cost-Benefit 52

AWS Big Data

AUGUST 1, 2024

This includes the expected response time limits for dashboard queries or analytical queries, elapsed runtime for daily ETL jobs, desired elapsed time for data sharing with consumers, total number of tenants with concurrency of loads and reports, and mission-critical reports for executives or factory operations.

Data Warehouse 98

Data Warehouse KPI Optimization Cost-Benefit 98

Jet Global

OCTOBER 2, 2019

The optimized data warehouse isn’t simply a number of relational databases cobbled together, however—it’s built on modern data storage structures such as the Online Analytical Processing (or OLAP) cubes. So how is the data extracted?

Enterprise 40

Enterprise OLAP Business Intelligence Cost-Benefit 40

AWS Big Data

MARCH 7, 2023

Consumption This pillar consists of various consumption channels for enterprise analytical needs. It includes business intelligence (BI) users, canned and interactive reports, dashboards, data science workloads, Internet of Things (IoT), web apps, and third-party data consumers.

Analytics 77

Analytics Data Warehouse Data Lake Metadata 77

IBM Big Data Hub

SEPTEMBER 25, 2023

As a result, they continue to expand their use cases to include ETL, data science , data exploration, online analytical processing (OLAP), data lake analytics and federated queries. It can ingest data from offline batch data sources (such as Hadoop and flat files) as well as online data sources (such as Kafka).

OLAP 86

OLAP Data Lake Data-driven Snapshot 86