Author Archives: Quartet
Streaming Analytics – Handling Continuous Data Flow
Many industries use different analytics solutions, but as the ongoing flow of relevant data is becoming more frequent we see that pure analytics does not really address the need to continuously process this data. Streaming analytics expands system’s processing capabilities … Continue reading
Counterparty Risk Analysis – Enhancing Existing Solutions
The current complex global financial markets include risks that are distributed across many entities. Credit risk in no longer limited to two parties, a bank and borrower, it now includes a variety of financial products and instruments, which makes counterparty … Continue reading
Risk Management Analytics
Nearly every move in the current business world involves some type of risk. These risks can stem from uncertainty in financial markets, project failures, legal liabilities, credit risk, or any uncertain or unpredictable cause or event. This is why organizational … Continue reading
PnL VaR – Drivers and Implications
When discussing PnL VaR, we refer to the implication profit and loss calculations of an enterprise, mostly financial institutions, on its value at risk measures. This data is used to provide an estimate of the amount of economic capital the … Continue reading
Value at Risk Aggregation – A Major Challenge of Risk Management
One of the major challenges in the management and measurement of risk that many financial institutions face is finding a coherent approach to value at risk aggregation. Some of the drivers behind this challenge are developments in regulatory standards and … Continue reading
CVaR Value at Risk – an Introduction
Value at Risk (VaR) is a general tool for assessing market risk; it measures the worst expected loss over a given horizon under normal market conditions at a given level of confidence. CVaR value at risk is the most common … Continue reading
MDX XMLA Basics
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 … Continue reading
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 … Continue reading