If you are looking into MDX, XMLA and the connection between, you arrived at the right place. We have put together this post to provide some basic information about MDX XMLA.
OLAP Performance Tuning Tips
In this post, we’ve collected a number of typical OLAP performance issues, with tips on how to perform OLAP performance tuning.
Real Time BI
Many businesses need the ability to aggregate and analyze complex business data in real time. This isn’t possible with traditional business intelligence solutions, which perform resource-intensive analysis and usually run in overnight batches. To overcome this limitation, several vendors have introduced real time BI, or real time OLAP solutions.
In Memory Business Intelligence – Challenges of Real Time Processing
In classic OLAP solutions, which usually store data on a hard disk, a key bottleneck is data access speed. Storing data in memory speeds up data access dramatically is a first step to performing real time OLAP analysis. In in memory business intelligence solutions, data access can be further accelerated, due to its in memory storage and smart data compression.
OLAP, MOLAP, ROLAP or HOLAP? OLAP Acronyms Explained
If you’re looking into OLAP technology, you’ve probably come across a large number of acronyms describing different flavors or types of OLAP. We’ve put together this post to help you make sense of the mess with brief definitions of each acronym.
Streaming OLAP – Handling Data in Motion
As traditional OLAP systems are usually designed to analyze large databases of historic data, they lack the ability to process the most current events as they are introduced into the system. Streaming OLAP provides the ability to continuously monitor new events and, as data changes, query, and analyze the new data, providing the ability to handle data in motion.
RTOLAP – Real Time OLAP Explained
Real time OLAP, or RTOLAP, is the capability to quickly retrieve, aggregate, analyze and present multi-dimensional data for cubes whenever there are changes to the data in the relational data source, without having to run heavy batch processing on the cube. A big advantage of real time OLAP is that it calculates all relevant data and provides immediate output.
OLAP and OLTP Hybrid Systems – Fact or Fiction?
Classic OLAP and OLTP systems are considered to be opposites – OLTP systems process simple, ongoing data such as sales, job orders, stock fluctuations, etc., and need to deal with it in real-time; OLTP is about processing masses of data in real time, but not about doing complex processing, that is where OLAP comes in.
Challenge #2: Integrating Counterparty Credit Risk Management, Liquidity Risk Management, and Other Risk Apps into a Single Risk Management System
In the previous post, we explained the risk intelligence concept, and some of the general challenges that arise when implementing a risk management system. This post lists some of the important conclusions made by the 2006-2009 Chartis Research surveys (read the Chartis Research white paper), including why existing risk management systems don’t succeed in integrating the entire spectrum of risk applications (such as counterparty credit risk management or liquidity risk management) into one system.
Challenge #1: Implementing a Risk-Intelligent BI Solution
This series of blog posts discusses the importance of the risk intelligence concept, as raised by Chartis Research surveys (read the full Chartis Research white paper). In this post, we explain the concept of risk intelligence, and some of the challenges in implementing a risk management system in general.
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