OLAP vs. OLTP: A Comparative Analysis of Data Processing Systems
KDnuggets
AUGUST 21, 2023
A comprehensive comparison between OLAP and OLTP systems, exploring their features, data models, performance needs, and use cases in data engineering.
Unlocking the Games: The Power of OLAP Cubes in Sports Analysis
Paris Technologies
OCTOBER 30, 2023
PARIS Tech and partner David Newton from Newton Carmen have collaborated to create an OLAP model for analysing the 2023 Rugby World Cup. Using this data model, full of every Rubgy stat imaginable, we’ve run a video series of over20 different scenarios. Turns out we were able to predict the South African winners!
OLAP 
52
52 Join 52,000+
Insiders
Sign Up for our Newsletter
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Webinars
Peak Performance: Continuous Testing & Evaluation of LLM-Based Applications
The Key to Sustainable Energy Optimization: A Data-Driven Approach for Manufacturing
From Developer Experience to Product Experience: How a Shared Focus Fuels Product Success
Understanding User Needs and Satisfying Them
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You Need to Know
Trending Sources
Dreamkillers – Analyzing the 2023 Rugby World Cup with OLAP Cube Technology
Paris Technologies
AUGUST 21, 2023
We’ve created a Rugby World Cup model with an array of versions, predicting diverse outcomes for matches at different stages of the event. The post Dreamkillers – Analyzing the 2023 Rugby World Cup with OLAP Cube Technology first appeared on PARIS Tech.
OLAP 40
40 Webinars
Peak Performance: Continuous Testing & Evaluation of LLM-Based Applications
The Key to Sustainable Energy Optimization: A Data-Driven Approach for Manufacturing
From Developer Experience to Product Experience: How a Shared Focus Fuels Product Success
Understanding User Needs and Satisfying Them
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You Need to Know
Data Modeling 301 for the cloud: data lake and NoSQL data modeling and design
erwin
AUGUST 15, 2022
For NoSQL, data lakes, and data lake houses—data modeling of both structured and unstructured data is somewhat novel and thorny. As with the part 1 and part 2 of this data modeling blog series, the cloud is not nirvana. Data modeling basics. Data Modeling. This blog is based upon a recent webcast that can be viewed here.
Data Lake 52
52 
Data Modeling 201 for the cloud: designing databases for data warehouses
erwin
JUNE 7, 2022
Accordingly, data modelers must embrace some new tricks when designing data warehouses and data marts. Data modeling for the cloud: good database design means “right size” and savings. Now to cover some data modeling basics that applies no matter whether on-premises or in the cloud. Data Modeling. Business Focus.
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 62
62 
What Are OLAP (Online Analytical Processing) Tools?
Smart Data Collective
JUNE 16, 2022
One of the most valuable tools available is OLAP. Using OLAP Tools Properly. Trend analysis, financial reporting, and sales forecasting are frequently aided by OLAP business intelligence queries. ( Several or more cubes are used to separate OLAP databases. You need to utilize the best tools to handle these tasks.
What are decision support systems? Sifting data for better business decisions
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. According to Gartner, the goal is to design, model, align, execute, monitor, and tune decision models and processes. Model-driven DSS. They emphasize access to and manipulation of a model.
Data mining 137
137 
Navigating Data Entities, BYOD, and Data Lakes in Microsoft Dynamics
Jet Global
SEPTEMBER 4, 2020
Consultants and developers familiar with the AX data model could query the database using any number of different tools, including a myriad of different report writers. Data entities are more secure and arguably easier to master than the relational database model, but one downside is there are lots of them! Data Lakes.
Data Lake 88
88 
Complexity Drives Costs: A Look Inside BYOD and Azure Data Lakes
Jet Global
NOVEMBER 5, 2020
That stands for “bring your own database,” and it refers to a model in which core ERP data are replicated to a separate standalone database used exclusively for reporting. For more powerful, multidimensional OLAP-style reporting, however, it falls short. OLAP reporting has traditionally relied on a data warehouse.
Data Lake 98
98 
Reporting Analytics vs. Financial Reporting: Is There a Difference?
Jet Global
OCTOBER 26, 2021
Multi-dimensional analysis is sometimes referred to as “OLAP”, which stands for “online analytical processing.” Technically speaking, OLAP refers to methodologies for producing multidimensional analysis on high-volume data sets.). That may prompt further investigation and could reveal insights as to the appropriate corrective action.
Reporting 98
98 
What is OLAP?
Jedox
JULY 1, 2020
In this blog post, we’ll look at the definition of OLAP as well as an overview of the technology. We explain what lies behind OLAP, what cubes have to do with it and what makes the technology so powerful for modern planning, budgeting, and forecasting. Most modern EPM solutions rely on multidimensional OLAP, also called MOLAP.
OLAP 92
92 
Time to Act: Key Considerations When Leaving the Legacy Behind
Jedox
DECEMBER 3, 2020
Users should be able to create their own integrated plans and reports based on the same data model and business logic. Legacy solution users will also want to look for familiar features: an in-memory OLAP database, an easy to model multi-cube architecture and cell-based spreadsheet style reporting.
OLAP 56
56 
The Enterprise AI Revolution Starts with BI
Jet Global
APRIL 2, 2019
Many of the features frequently attributed to AI in business, such as automation, analytics, and data modeling aren’t actually features of AI at all. In a recent McKinsey survey of 3,000 business executives, 41% responded that they were uncertain of the benefits of AI for their business.
Enterprise 80
80 
RDF-Star: Metadata Complexity Simplified
Ontotext
JUNE 10, 2021
And yeah, the real-world relationships among the entities represented in the data had to be fudged a bit to fit in the counterintuitive model of tabular data, but, in trade, you get reliability and speed. They create reliable, consistent and communicable models for representing data. Graph Databases vs Relational Databases.
Metadata 119
119 
The Business Intelligence Market – What’s Old is New
In(tegrate) the Clouds
OCTOBER 7, 2016
Thanks to The OLAP Report for lots of great market materials. Comshare, Pilot, Metaphor, watch out here comes some more: OLAP, ROLAP, HOLAP, MOLAP now my head hurts. OLAP for the masses, gents? OLAP Services, TM1, Pablo, Wired, and Crystal fun. Showcase, SQRIBE all get imbibed and don’t forget OLAP@ Work.
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. Store and manage: Next, businesses store and manage the data in a multidimensional database system, such as OLAP or tabular cubes. to analyze past events to forecast future events.
Data mining 75
75 
Cloud Migrations: Big Challenges, Big Opportunities
Sisense
APRIL 21, 2019
With a comprehensive, BI-focused data strategy, you and your stakeholders will know what your ideal data model should look like once all your data is moved over. What does all this have to do with my data model ?” Your data infrastructure underpins your data model and powers all of your business-critical IT systems.
OLAP 72
72 
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. Cubes are multi-dimensional datasets that are optimized for analytical processing applications such as AI or BI solutions.
Enterprise 70
70 
A Complete Guide For BI Reporting
FineReport
MAY 29, 2020
Business understanding’ is realizing in-depth data analysis and smart data forecasting via analysis and prediction functions such as data mining, predictive modeling, and so on. If you have advanced requirements for OLAP analysis or prediction, the BI suite is a better choice. . The ‘data’ part is the statistics and data display. .
Reporting 94
94 
Understanding Data Entities in Microsoft Dynamics 365
Jet Global
OCTOBER 7, 2020
Jet Analytics provides a pre-built data warehouse , OLAP cubes , and tabular models with a platform for non-technical users to easily create their own reports in Excel or Power BI. With a short time to value, you can be up and running in an hour and seeing tangible benefits before the end of your next reporting cycle.
AI vs. BI for Business, What Do You Need?
Jet Global
MARCH 5, 2019
AI, colloquially, is used to refer to a number of computer-powered business decision drivers, including automation (not AI), data modeling (not AI), and reporting and analytics (also not AI). But are those tools powered by artificial intelligence? What are some of the core components of business intelligence?
What’s the Difference Between Business Intelligence and Business Analytics?
Sisense
AUGUST 11, 2019
Typically, this involves using statistical analysis and predictive modeling to establish trends, figuring out why things are happening, and making an educated guess about how things will pan out in the future. What About “Business Intelligence”? BI is also about accessing and exploring your organization’s data.
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. Cubes are multi-dimensional datasets that are optimized for analytical processing applications such as AI or BI solutions.
Enterprise 40
40 
Panduan Lengkap Untuk Pelaporan BI
FineReport
MAY 31, 2020
“Pemahaman bisnis” adalah untuk menganalisis data secara mendalam dan memperkirakan data melalui fungsi analisis dan prediksi seperti data mining, predictive modeling, dan sebagainya. Jika Anda memerlukan analisis atau prediksi OLAP, maka software BI lebih cocok untuk Anda. Bagaimana Cara Kerja Software Pelaporan BI?
OLAP 52
52 
Here’s Why Automation For Data Lakes Could Be Important
Smart Data Collective
APRIL 2, 2019
The way to work around this shortcoming is to use OLAP cubes or data models generated within memory, but these will take time to develop and test, especially since they need to be scalable to the level of use in a data lake. The Third Problem – Preparation of Data.
Data Lake 83
83 
Master Your Power BI Environment with Tabular Models
Jet Global
OCTOBER 22, 2020
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. OLAP Cubes vs. Tabular Models. The first is an OLAP model. Fortunately, there is a way to have the best of both worlds.
Modeling 52
52 
Pivot Table vs. PowerExcel Pivot
Paris Technologies
OCTOBER 12, 2023
If you've built your models in Excel, this becomes very difficult. You need to go down to the bottom, change some assumptions, roll it all up, and check if you have the number that management wants. If you don’t, you must go down to the bottom again and start over until you roll it all up again.
Modeling 52
52 
How gaming companies can use Amazon Redshift Serverless to build scalable analytical applications faster and easier
AWS Big Data
MARCH 7, 2023
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. It helps you build, train, and deploy models consuming the data from repositories in the data hub.
Analytics 68
68 
Prevent Customer Churn: Customer Retention in the Transition to Microsoft D365 F&SCM
Jet Global
JANUARY 15, 2021
In many respects, it is more akin to some of the very complex data warehousing and OLAP tools of the past–perhaps with an even steeper learning curve. When the underlying data model changes, Jet Analytics provides an updated adapter to accommodate those changes without additional effort on the part of the partner or the customer.
Cost-Benefit 72
72 
Data Model Development Using Jinja
Sisense
FEBRUARY 16, 2021
Every aspect of analytics is powered by a data model. A data model presents a “single source of truth” that all analytics queries are based on, from internal reports and insights embedded into applications to the data underlying AI algorithms and much more. Data modeling organizes and transforms data. DBT: Data Build Tool.
Modeling 52
52 
Aplikasi Laporan: Panduan Komprehensif 2020
FineReport
MARCH 13, 2020
Contohnya, dengan memakai aplikasi laporan perusahaan seperti FineReport , pengguna dapat mengubah model bisnis dan menganalisis data perusahaan menjadi sebuah sistem informasi yang praktis dan dapat dioperasikan. Fitur refresh secara otomatis memastikan data analisis up-to-date.
Dashboards 59
59 
Aplikasi Laporan: Panduan Komprehensif 2020
FineReport
MARCH 13, 2020
Contohnya, dengan memakai aplikasi laporan perusahaan seperti FineReport , pengguna dapat mengubah model bisnis dan menganalisis data perusahaan menjadi sebuah sistem informasi yang praktis dan dapat dioperasikan. Fitur refresh secara otomatis memastikan data analisis up-to-date.
Dashboards 52
52 
Business Intelligence Solutions: Every Thing You Need to Know
FineReport
JUNE 24, 2021
Technicals such as data warehouse, online analytical processing (OLAP) tools, and data mining are often binding. On the opposite, it is more of a comprehensive application of data warehouse, OLAP, data mining, and so forth. Predictive analytics and modeling. BI software solutions (by FineReport).
Top 10 Free and Open Source BI Tools in 2020
FineReport
MAY 13, 2020
It also can be used to create a predictive model for various business domains and kinds of models, such as classification, regression, and clustering. . When requiring high customization and sophisticated models, the speed is needed. But KNIME is less flexible and slow. . From Google. Pentaho Community Edition .
OLAP 105
105 
What is business intelligence? Transforming data into business insights
CIO Business Intelligence
JANUARY 20, 2023
It uses data mining , data modeling, and machine learning to answer why something happened and predict what might happen in the future. BI analysts use data analytics, data visualization, and data modeling techniques and technologies to identify trends.
How to Build a Performant Data Warehouse in Redshift
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. OLAP databases excel at queries that require large table scans (e.g.
Best Reporting Tools List You Can’t Miss in 2020
FineReport
JANUARY 6, 2020
The former is more professional in report making, presentation, and printing, while the latter can make OLAP and predict analysis thanks to the BI capabilities. As reporting software, it does not support OLAP. Visual ETL and UI for data relationships and modeling with ETL. . FineReport. Crystal Reports. Price: Quote-based.
Reporting 97
97 
Closing the breach window, from data to action
IBM Big Data Hub
SEPTEMBER 27, 2023
QRadar Log Insights’ AI model acts as a security analyst who knows exactly what to hunt for. Threat hunting is provided with Kestrel, an open source threat hunting language that integrates lightning-fast federated search, threat intelligence, and analytics all in one engine.
Cost-Benefit 102
102 
How to Get Data from Microsoft D365 BC into Power BI
Jet Global
FEBRUARY 8, 2021
This change also complicates matters considerably whenever you make changes to the underlying database, such as when your company builds custom extensions or installs third-party products alongside Microsoft D365 BC, or when Microsoft adds new features to the product that result in changes to the underlying data model.
Reporting 98
98 
How to Become a BI Developer without Learning How to Script
Jet Global
DECEMBER 1, 2020
In addition, you will also need some knowledge of tabular models, as well as understanding the underlying database architecture of the ERP system or other applications that you are reporting against. A non-developer can easily build a basic data warehouse including OLAP Cube or Tabular Model with Jet Analytics in as little as 30 minutes.
Finance 78
78 
What is Business Intelligence Consulting
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.
What is Business Intelligence Consulting
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.
Increase the Performance of Your Logical Data Fabric with Smart Query Acceleration
Data Virtualization
OCTOBER 28, 2020
Organizations today need a data architecture that can overcome a double challenge: satisfy new business needs that require more agility and self-service capabilities, while at the same time dealing with a growing, diverse, and fast-moving data ecosystem (new data sources,
Let's personalize your content