OLAP, Online Analytical Processing and Optimization

How OLAP and AI can enable better business

IBM Big Data Hub

DECEMBER 7, 2023

Online analytical processing (OLAP) database systems and artificial intelligence (AI) complement each other and can help enhance data analysis and decision-making when used in tandem. As AI techniques continue to evolve, innovative applications in the OLAP domain are anticipated.

OLAP

OLAP Slice and Dice Cost-Benefit Data Warehouse

Build a real-time analytics solution with Apache Pinot on AWS

AWS Big Data

AUGUST 6, 2024

Online Analytical Processing (OLAP) is crucial in modern data-driven apps, acting as an abstraction layer connecting raw data to users for efficient analysis. OLAP combines data from various data sources and aggregates and groups them as business terms and KPIs.

OLAP

OLAP Analytics Visualization Dashboards

Unleashing the power of Presto: The Uber case study

IBM Big Data Hub

SEPTEMBER 25, 2023

Uber’s DNA as an analytics company At its core, Uber’s business model is deceptively simple: connect a customer at point A to their destination at point B. With a few taps on a mobile device, riders request a ride; then, Uber’s algorithms work to match them with the nearest available driver and calculate the optimal price.

OLAP

OLAP Data Lake Data-driven Online Analytical Processing

Webinars

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The Enterprise AI Revolution Starts with BI

Jet Global

APRIL 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.

Enterprise

Enterprise OLAP Business Intelligence Internet of Things

How to Build a Performant Data Warehouse in Redshift

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. Redshift, like BigQuery and Snowflake, is a cloud-based distributed multi-parallel processing (MPP) database, built for big data sets and complex analytical workflows.

Data Warehouse

Data Warehouse OLAP Statistics Cost-Benefit

What Role Does Data Mining Play for Business Intelligence?

Jet Global

JUNE 5, 2019

Business intelligence (BI) software can help by combining online analytical processing (OLAP), location intelligence, enterprise reporting, and more. If data is the fuel driving opportunities for optimization, data mining is the engine—converting that raw fuel into forward motion for your business.

Data mining

Data mining Business Intelligence OLAP Key Performance Indicator

Business Intelligence Solutions: Every Thing You Need to Know

FineReport

JUNE 24, 2021

Business intelligence can assist decision-making and operation optimization, either at the operational or tactical, or strategic levels. Technicals such as data warehouse, online analytical processing (OLAP) tools, and data mining are often binding. Data preparation and data processing.

Business Intelligence

Business Intelligence OLAP Data mining Visualization

Navigating Data Entities, BYOD, and Data Lakes in Microsoft Dynamics

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

Data Lake OLAP Data Warehouse Unstructured Data

Unlock scalability, cost-efficiency, and faster insights with large-scale data migration to Amazon Redshift

AWS Big Data

AUGUST 1, 2024

This includes the ETL processes that capture source data, the functional refinement and creation of data products, the aggregation for business metrics, and the consumption from analytics, business intelligence (BI), and ML. The data warehouse is highly business critical with minimal allowable downtime.

Data Warehouse

Data Warehouse KPI Optimization Cost-Benefit

Financial Intelligence vs. Business Intelligence: What’s the Difference?

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.” It seeks to optimize performance by identifying opportunities and challenges as soon as they emerge.

Business Intelligence

Business Intelligence Finance Data Warehouse OLAP

How Aura from Unity revolutionized their big data pipeline with Amazon Redshift Serverless

AWS Big Data

APRIL 4, 2024

Amazon Redshift is a recommended service for online analytical processing (OLAP) workloads such as cloud data warehouses, data marts, and other analytical data stores. These campaigns are optimized by using an AI-based bid process that requires running hundreds of analytical queries per campaign.

Big Data

Big Data Data Warehouse Advertising OLAP

The Future of AI in the Enterprise

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.

Enterprise

Enterprise OLAP Business Intelligence Cost-Benefit

Build an Amazon Redshift data warehouse using an Amazon DynamoDB single-table design

AWS Big Data

JUNE 21, 2023

Deriving business insights by identifying year-on-year sales growth is an example of an online analytical processing (OLAP) query. The case for a data warehouse A data warehouse is ideally suited to answer OLAP queries. An optimal design choice is to use a dimensional model.

Data Warehouse

Data Warehouse Data Lake OLAP Cost-Benefit

How gaming companies can use Amazon Redshift Serverless to build scalable analytical applications faster and easier

AWS Big Data

MARCH 7, 2023

They should also provide optimal performance with low or no tuning. Data repository services Amazon Redshift is the recommended data storage service for OLAP (Online Analytical Processing) workloads such as cloud data warehouses, data marts, and other analytical data stores.

Analytics

Analytics Data Warehouse Data Lake Metadata

The Future of AI in the Enterprise

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.

Enterprise

Enterprise OLAP Business Intelligence Cost-Benefit

Deploy real-time analytics with StarTree for managed Apache Pinot on AWS

AWS Big Data

MARCH 13, 2025

Indexes are then configured to optimize query performance, as per the flow in the diagram below. StarTrees tiered storage enables automation for real-time query processing with index pinning, prefetching, and intelligent data movement between hot and cold storage, optimizing both performance and cost.

Management

Management Analytics OLAP Online Analytical Processing

Data Leaders Brief

How OLAP and AI can enable better business

Build a real-time analytics solution with Apache Pinot on AWS

Webinars

Trending Sources

Unleashing the power of Presto: The Uber case study

Webinars

The Enterprise AI Revolution Starts with BI

How to Build a Performant Data Warehouse in Redshift

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Navigating Data Entities, BYOD, and Data Lakes in Microsoft Dynamics

Unlock scalability, cost-efficiency, and faster insights with large-scale data migration to Amazon Redshift

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How Aura from Unity revolutionized their big data pipeline with Amazon Redshift Serverless

The Future of AI in the Enterprise

Build an Amazon Redshift data warehouse using an Amazon DynamoDB single-table design

How gaming companies can use Amazon Redshift Serverless to build scalable analytical applications faster and easier

The Future of AI in the Enterprise

Deploy real-time analytics with StarTree for managed Apache Pinot on AWS

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