American Network and large data

IBM has been working with the US Tennis League, the behind-the-scenes organization of the US Open, which has lasted for 22 years now. Throughout the period, the company has been providing infrastructure to transmit scores and statistics, but in the past few years things have become interesting.

For example, the 2012 U.S. Open had its first ipad app (iphone app implemented in 2009), breaking scoring information, live and on-demand video and analysis. Even from a complex social media point of view: When an ipad application is opened, you will see a set of columns, each showing a series of messages, which are hashed labels, specific to the open National Tennis Center of the individual Stadium (and competition).

With just a few taps, you can navigate the video stream's menu, either the pitch or the live game, of course, HD. You can also easily see the latest picture of all 5 major tournaments (men, women singles and doubles, and mixed doubles). This week, in the island rented beach house, I used the main app, where the digital subscriber line (below 3Mbps downstream) was the only broadband option, and the reader worked well.

Back to the network

But you don't necessarily need an ipad to take advantage of this technology. For example, if you log on to www.usopen.org on your desktop or laptop, you can take advantage of many of the same feature programs, even some that you won't get on the ipad. For example, select a video and broadcast from the top navigation bar, then click the US Open Live from the Drop-down menu, select a course, and start watching. While I was writing this article, I was watching Angelique Cobre and Venus Williams playing their second leg. Since I'm on the internet, I don't just want to watch linear video and listen to all kinds of reviews; In the live video, I also want to do some superposition of data analysis. As you can imagine, IBM has not let me down.

First of all, I can click on the game Data button to see the real-time updated statistics, such as the percentage of the first serve, the number of service double errors and natural errors, and I can see these calculated numbers about the entire match or specific settings. In the upper-left corner of the screen, there is a button labeled "Enter the game button." "If I click on it, some very interesting data will appear." For the first time in last year's open program, three of the most important factors can be identified for a given match, tailored specifically for each particular competitor. On the site's SlamTracker feature, you can see the same data (not as an overlay on a live video) that can be used for fractions and statistics:

These measures also include the number of targets and states. In fact, they are key performance indicators (KPIs), back to competitive sports, the game shows the key is a scorecard, so that the term can be used in a full cycle. But not directly on-line Analytical Processing (OLAP), these key performance metrics are based on the execution forecast analysis of data from all four Grand Slam tournaments in the past 7 years, with a total of 39 million positions.

By analyzing the most popular cobre in most competitions, she was the ultimate winner. Although the Cobeby Venus has a higher ranking, the result of the race is indeed somewhat unsettling, as is IBM's accurate predictive analysis.

This is truly valuable data, and IBM is working with the Entertainment Sports television Network (ESPN) to keep the conversation going by providing the data to the latter's live-broadcast critic. But it is clear that in this network age and interactive analysis, you no longer need to rely on commentators to get it. Instead, you just need a browser and a mouse, or an ipad and your finger, to be your own grand Slam data analyst.

What is hidden behind the scenes?

Naturally, readers would be interested to know what the backend of the IBM product is and how its technology is used in the U.S. Open. Here's what I know.

SlamTracker technology (including competition data and game key) is heavily using the SPSS technology acquired by IBM in 2009.

IBM has a powerful relational database, and the database is used very frequently for scoring data and operations.

WebSphere MQ (FKA MQ series), IBM based messaging based middleware is used for scoring delivery, allowing you to get online scores more quickly.

The technology for WebSphere is used for the overall service architecture.

The most interesting thing about

is how all of the techniques in the list above can be used for more than 10 years (some of them are also more). Core statistics, relationships, SOA, and middleware technologies have not become unimportant at this stage of data and analysis. In addition, it is particularly noteworthy that the Hadoop, Netezza and Cognos Business intelligence technologies have not been cut. Hadoop, data warehousing, and business Intelligence (BI) are of course important, but the traditional enterprise technology of IBM applications shows that large data and BI-specific technologies are not necessarily prerequisites for good analysis implementations.