History of Business Intelligence

A fascinating story from Nic at Microsoft BI

Hat tip:The BI Blog

Interact 09 Conference

Fair Issac is hosting a decision management conference Interact 09 in New York City from March 10-13, 2009.

Some interesting topics are being covered which are very relevant to the turbulent economic times that we are living in:

Managing Risk in Credit Crunch
How to learn from Bad Debt
How Lending has changed

If you are interested, go here to register and use the promo code FMH00 to get $350 off the price of attendance. Thanks to Chris from Fleishman.

Algorithm

An algorithm is a set of instructions that allows you to solve a problem.

Each instruction is simple and repeatable. It’s important to understand that the instructions work on all similar problems, not just one.

Here’s an algorithm for sorting any set of numbers, to get them into order. Start with 4,3,5,6,2 for example.

The bubble sort algorithm is simple. Compare two numbers. If the first number is higher than the second, switch them. So now it’s 3,4,5,6,2. Next step is to compare positions two and three. If the second is higher than the third (it’s not) switch them. Repeat for the whole string. Then start over. Do it over and over again until you can go the whole way with no switching. Done.

More here from Seth.

Numerati

Recently completed reading Numerati by Stephen Baker.

Good read for someone looking for an introduction to analytics and how it is being used in various industries today.

Data mining in the credit crisis

In recent months, American Express has gone far beyond simply checking your credit score and making sure you pay on time. The company has been looking at home prices in your area, the type of mortgage lender you’re using and whether small-business card customers work in an industry under siege. It has also been looking at how you spend your money, searching for patterns or similarities to other customers who have trouble paying their bills.

More here

Database Analytics Startup Aster Data launched

Grid-computing startup Aster Data Systems will officially launch today, three years after it was founded. Aster, which began in the Ph.D program at Standford, is a provider of “massively parallel processing databases” for organizations that have mammoth quantities of data that need to be stored and analyzed quickly. The Redwood City, California-based company is backed by Sequoia Capital, Cambrian Ventures, and First-Round Capital.

Aster’s nCluster software allows companies with large amounts of data to store it on commodity hardware and scale with one-click, adding new servers as the data set grows. The company’s first major client is MySpace, which generates 100s of terabytes of traffic data from its 110 million monthly unique users. Mining that data to understand how customers use and interact with the site requires some pretty robust architecture.

Read more here.

ONLINE SEARCH ADS FARING BETTER THAN EXPENSIVE DISPLAYS

In the past few years, Web publishers have made a big bet on booming online advertising revenues. But the economic slowdown may be throwing a wrench into those plans.

While search advertising remains strong, there are signs that the growth in online advertising — particularly in more elaborate display ads — is slowing down. In the past few weeks, major online-advertising players, like Yahoo and Time Warner, have posted mixed results.

And online publishers may be getting less money for the ad space they do sell. The prices paid for online ads bought through ad networks dropped 23 percent from March to April, according to PubMatic, an advertising-technology company in Palo Alto, Calif., that runs an online-pricing index. Large Web publishers fared the worst in PubMatic’s study, with the prices they received through networks dropping 52 percent.

More here from NYTimes.

Microsoft and Data Mining Dominance

When it comes to data mining and predictive analytics, Microsoft Corp. might not be the first company that comes to mind.

That could change, however, especially if Donald Farmer, Redmond’s principal program manager for SQL Server Data Mining, has his way.

Microsoft has come a long way in the data mining and predictive analytics segment, Farmer says, and with a game-changing Excel 2007 release under its belt — and a promising SQL Server 2008 revision in the pipeline — Redmond hopes to challenge established powers SAS Institute Inc. and SPSS Inc. for data mining and predictive analytic bragging rights.

“[We don’t] have all the functionality of something like a SAS or an SPSS, because that’s just not our market,” he conceded.

It comes down to a difference of scale, according to Farmer. SAS and SPSS typically target larger, more expensive deployments, typically with users well-versed in the usage of their tools. Microsoft is targeting a different kind of data mining consumer: the Excel analyst, for example, who might not have much (if any) experience with data mining, predictive analytics or statistical analysis, for that matter.

Read more from RedmondMag here.

BI series from CIO

CIO is running a special BI series, which is good reading for someone looking for a primer on the consolidation in the BI industry and who are the megavendors in BI and their role in the BI space, BI On Demand and how to reduce the total cost of ownership of BI.

Part 1: A Technology Category in Tumult
Part 2 : Nine BI Vendors to Watch
Part 3 : BI and On-Demand:The Perfect Marriage?
Part 4: What You Need to Know About the BI TCO

Q&A Session with Sabermetrician, Bill James

The father of sabermetrics, Bill James takes questions from the readers of the freakanomics blog. He makes some interesting points about what can and cannot be done in the field of sports using statistics and number crunching.