I noticed some interest in biomedical and healthcare-related data across the forums.

See for example the earlier posts about the gene expression data:

http://www.infobright.org/Forums/viewthread/265/

How about merging further relevant discussions into a single thread?

I believe we may learn a lot from each other in the following two areas:

—What are major aspects of data warehousing applications in biomedicine and healthcare?

—Is Infobright’s technology a good choice for such types of applications?

In particular, I looked around and found the following links that may be useful:

1. http://hdwa.org/hdwa/home/—Healthcare Data Warehousing Association (HDWA).

2. http://www.bio-medicine.org/—I’ve put “data warehouse” into the search window.

3. http://www.bioinformatics.org/—I’ve done the same as above.

I’m sure that people working actively in these areas may know even more interesting, specific links…

Best greetings,

Dominik

Financial organizations need to store and analyze ever-growing data volumes, faster and more effectively than ever, in order to compete. Near real-time response is required for the purposes of trade speed execution, immediate response to credit risk and fraud situations, better targeted customer loyalty programs, and the ability to maintain compliance and regulatory requirements. And, financial services is one of the sectors where the pressure to do more with less has never been stronger.

Some specific areas (as mentioned above) where ICE’s analytic query speed has a real advantage in financial services include:

Trade Execution - Firms that trade in capital markets know that the business depends on the speed at which they can analyze and process trades. They simply cannot allow the ever-increasing trade and tick data volumes to impact analytic response times.

Risk Management - Financial services institutions must prevent risk and identify fraud in real-time. The ability to analyze trends and spot inconsistencies across huge volumes of live and historical data helps organizations prevent losses of money and reputation.

Regulatory Compliance - Financial organizations know that rising data volumes and analytic speed requirements cannot impact accuracy. Compliance with rising regulatory requirements, from trading compliance (Reg NMS, MiFID) to corporate governance (Sarbanes-Oxley, Basel II), directly impacts their ability to stay in business.

There has been explosive growth in telecommunications applications over the last two decades, and service providers are using data as one of the main ways to win and keep customers. Telecommunications companies spend hundreds of millions of dollars each year
collecting, testing, measuring and acquiring use data. The analysis of the data determines how to acquire new customers, reduce churn, and effectively compete. But the amount of data is simply staggering. Call center analysis, Call data records (CDR), customer billing data, as well as statistical data from the network, and alarms, alerts and event management…

Not only to telcos face increasing challenges managing explosive growth in the volumes of data, but also on the analytics required. The vast cross-section of telco applications means widely differing requirements for data access and queries. While some applications
require little to no querying (ie, archive compliance), others require access to large amounts of data to perform highly complex, ad hoc queries (ie, call agent optimization, targeted user services).

The problems of storing the vast volume of data (and the costs involved of keeping it all together) and ensuring that analysts and internal systems have timely access to the data typically results in multiple development projects, creating silos of data - which is untenable over time.

Again, this is a good fit for ICE where the compression and metadata querying allows for all the data to be stored in one warehouse, and gives good performance on unpredicted new queries.

Additional reading:
http://www.dmreview.com/issues/19981201/260-1.html

The spend on online marketing analysis is growing significantly (from about $6B in 2002, projected to $40B in 2011). This growth is driven by companies who are looking to manage their marketing spend more effectively: understanding who buys, figuring out where they come from and what interests them, and promoting their products to the best fit targets. Marketing analysis companies provide these insights to their clients by analyzing online behavior (tracking customer origins, clicks and site-to-site movement, lengths of stays, etc.).

Not surprisingly, collecting and analyzing this data has huge technical issues, not least of which is the staggering volumes of data that needs to be captured and analyzed. Plus, the data needs to be analyzed as close to real-time as possible in order to facilitate the need for rapid response to campaigns and specific targeting. Worse, with the huge growth rate in the space comes added competition. That drives the need for online marketing firms themselves to target and differentiate the offerings, requiring deeper analytics across more granular data—in short, even more data to deal with, and even more ad-hoc analytics.

Beyond needing to store large amounts of data for unpredictable ad-hoc analysis, this is also a young market. Most companies are 5 years or less in business. They are seeing insane growth leaving them resource constrained, so they need high-volume, low-cost solutions that need as little maintenance as possible.

All in all, a good fit for ICE.

Some additional reading on the subject can be found here:

http://www.webanalyticsassociation.org/
http://data-warehouses.net/webanalytics/dimensional.html