Tony Pearson is a Master Inventor and Senior IT Architect for the IBM Storage product line at the
IBM Executive Briefing Center in Tucson Arizona, and featured contributor
to IBM's developerWorks. In 2016, Tony celebrates his 30th year anniversary with IBM Storage. He is
author of the Inside System Storage series of books. This blog is for the open exchange of ideas relating to storage and storage networking hardware, software and services.
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With all the excitement of the [IBM Challenge], where the [IBM Watson computer] will compete against humans on [Jeopardy!], I thought it would be good to provide the following homework exercise to help you appreciate how challenging the game is and the strategies required.
Overview of the game of Jeopardy!
If you are familiar with the show, you can safely skip this section.
Known as "America's Favorite Quiz Show", the Jeopardy pits three contestants against each other. The board is divided into six columns and five rows of answers. Each column indicates the category for that column of answers. The rows are ranked from easiest to most difficult, with more difficult answers being worth more money to wager.
The contestants take turns. The returning champion gets to select a spot on the board, by indicating the category (column) and wager (row), such as "I will take Animals for 800 dollars!" Contestants must then press a button to "buzz in", be recognized by the host, and respond correctly. If the contestant responds incorrectly, the other two contestants have the opportunity to respond. The contestant with the correct response gets to chose the next answer.
For each turn, the host, Alex Trebek, shows the answer on the board, and spends three seconds reading it aloud to give everyone a chance to come up with a corresponding question. This is perhaps what Jeopardy is most famous for. In a traditional "Quiz Show", the host asks questions, and the contestants answer that question. On Jeopardy, however, the host poses "answers", and the contestants provide their response in the form of a "questions" that best fit the category and answer clues. For example, if the categories were "Large Corporations" and the answer was "Sam Palmisano", the contestant would answer "Who is the CEO of IBM Corporation?" Both the categories, and the answers are filled with puns, slang and humor to make it more challenging. Often, the answer itself is not sufficient clue, you have to factor in the category as well to have a complete set of information.
The game is played in three rounds:
In the first round, there are six categories, and the rows are worth $200, $400, $600, $800 and $1000 dollars. If you respond correctly on all five answers in a category column, you would win $3000. If you respond to all thirty answers correctly, you would earn $18,000.
In the second round, there are six different categories, and the rows are worth twice as much.
The final round has a single category and a single question. Each player can decide to wager up to the full amount of their score in this game. This wager is done after they see the category, but before they see the answer.
After the host finishes reading the answer aloud, the buzzers are lighted so that the contestants can buzz in. If a contestant gets the question correctly, he earns the corresponding money for the row it was in. If the contestant guesses incorrectly, the money is subtracted from his score. If the first contestant fails, the buzzers are re-lit so the other two contestants can then buzz in with their answers, learning from previous failed attempts.
To provide added challenge, some of the answers are surprise "Daily Double". Instead of the dollar amount for the row, the contestant can wager any amount, up to their total score they have won so far in that game, or the largest dollar amount for that round, whichever is higher, based on his confidence in that category. There is one "Daily Double" surprise in the first round, and two in the second round.
In the final round, each contestant wagers an amount up to their total score, based on their confidence on the final category. A common strategy for the leading contestant with the highest score is to wager a low amount, so that if he fails to guess the response correctly, he will still have a large dollar amount. For example, if the leader has $2000 and the second place is $900, the leader can wager only $100 dollars, and the second place might wager his full $900. If the leader loses the round, he still has $1900, beating the second place regardless of how well he does.
Whomever has the most money at the end of all three rounds wins that amount of cash, and gets to return to the show for another game the next day to continue his winning streak. The other two contestants are given consolation prizes and a nominal appearance fee for being on the show, and are never seen from again.
The show is only 30 minutes long, so the folks at Sony Pictures who produce the show can film a full weeks' worth of television shows in just two days of real-life, Tuesday and Wednesday, allowing the host Alex Trebek and his "Clue Crew" time to research new categories and answers.
So, here is your homework assignment. Record a full episode of Jeopardy on your VCR or Digital Video Recorder (DVR) and have your thumb ready to press the pause button. For each round, listen to each category, pause, and try to guess what all the answers in that column will have in common. For each category, write down a statement like "All the responses in this category are ...".
The answers could be people, places or things. Suppose the category "Chicks Dig Me". In English, "chicks" can be slang for women, or refer to young chickens. The term "dig" can be slang for admires or adores, so this could be "Male Celebrities" that women find attractive, it could be objects of desire that women fancy (diamonds, puppies, etc.), or it could be places that women like to go to. As it turns out, the "dig" referred to archaeology, and the responses were all famous female archaeologists.
Once you have those all your statements written down, press play button again.
Next, as each answer is shown, you have three seconds to hit the pause again, so that you have the question on the screen, but before any contestants have responded. Go on your favorite search engine like Google or Bing and try to determine the correct response based on the category and answer. Consider these [tips for being an Internet Search ninja]. Once you think you have figured out your response, write it down, and the dollar amount you wager, or decide you will not respond for that answer, if you are not sure about your findings.
Even if you think you already know the correct response, you may decide to gain more confidence of your response by finding confirming or supporting evidence on the Internet.
Press play. Either one of the contestants will get it right, or the host will provide the question that was expected as the correct response.
How well did you do? Were you able to find on the the correct response online, or at least confirm that what you knew was correct. If you got it correct, add in your dollar amount to your score. If you got it wrong, subtract the amount.
At the end of each round, look back at your statements for each category. Did you guess correctly the common theme for each category column of answers? Did you misinterpret the slang, pun or humor intended?
At the end of the game, you might have done better than the contestant that won the game. However, check how much added time you took to do those Internet searches. The average winner only questions half of the answers and only gets 80 percent of them correctly.
If you are really brave, take the [Jeopardy Online Test]. If you do this homework assignment, feel free to post your insights in the comments below.
We are only days away from the big IBM Challenge of Watson computer against two human contestants on the show Jeopardy!
I watched two episodes of Jeopardy! on my Tivo, pausing it to follow the [homework assignment] I suggested in my last post. Here are my own results and observations.
Episode  involved a web programmer, a customer service representative, and a bank teller.
Of the first six categories in Round 1, I guessed four of the six themes for each category. For the category "Diamonds are Forever", I wrote down "All answers are some kind of gem or mineral", but the reality was that all the answers were some physical characteristic of diamonds specifically. For the category "...Fame is not", I wrote down "All answers are TV or Movie celebrities". I was close, but actually it was famous celebrities, rock bands and pop culture of the 1980s. (The movie "Fame" came out in 1980).
In the round, there were 27 of the 30 answers given before they ran out of time. Of these, I was able to get 24 of 27 correct by searching the Internet. That is 88 percent correct. Here were the ones that eluded me:
Answer related to a "multi-chambered mollusk". I could not find anything on the Internet definitively on this, so abstained from wager. The correct question was "What is Nautilus?".
Answer was the Irish variant of "Kathryne". I found Kathleen as a variant, but did not investigate if it had Irish origins. The correct question was "What is Caitlin?"
Answer was this Norse name for "ruler" whether you had red hair or not. I found "Roy" and "Rory" so guessed "What is Rory?" The correct question was "What is Eric?"
The second round, I guesed three of the six themese for the categories. For category "Musical Titles Letter Drop" I wrote down "All the answers are titles of musical songs" but it was actually "Musicals" as in the Broadway shows. For category "Place called Carson", I wrote down "All the answers are places" and was way off on that one, with answers that were people, places and names of corporations. And for "State University Alums", I wrote down "All the answers are college graduates", but instead they were all "State Universities" such as the University of Arizona.
In this second round, only 26 answers were posed. I got 80 percent correct with Internet searching. I missed three on the "Musical Titles", one in "Pope-pourri" and one State University (sorry SMU). The "Musical Titles Letter Drop category" was especially difficult, as for each title of a Musical, you had to remove a single letter out of it to form the correct response.
For the answer "Good luck when you ask the singers "What I Did For Love"; they never tell the truth", you would need to take "Chorus Line" the musical, where the song "What I did for Love" appears, and ask "What is Chorus Lie?" Note that "line" changed to "lie" and the letter "n" was dropped out.
For the answer "Embrace the atoms as Simba and company lose and gain electrons en masse in this production", you would need to recognize that Simba was the main character of "The Lion King" and change it to "What is The Ion King".
I think these play-on-words are the questions that would stump the IBM Watson computer.
In the final round, the category was "Ancient Quotes". I thought the answer would be a famous adage or quotation, but it was instead famous people who uttered those phrases. The answer was "He said, to leave this stream uncrossed will breed manifold distress for me; to cross it, for all mankind". I was able to determine the correct response readily from searching the Internet: The river was the Rubicon, the border of the Gaul region governed by an ambitious general. The correct response "Who was Julius Caesar?"
Total time for the entire exercise: 87 minutes.
The following night, episode  brought back Paul Wampler, the returning champion web programmer, against two new contestants: an actor, and high school principal.
Of the first six categories in Round 1, I guessed five of the six themes for each category. For the category "Nonce Words", I wrote all the answers would be nonsense words. I was close, the clues had words invented for a particular occasion, but the correct responses did not.
I was able to get 29 of 30 correct by searching the Internet. That is 96 percent correct. The one I missed was in the category "Nonce Words" and the answer was "In an arithmocracy, this portion of the population rules, not trigonometry teachers.." My response was "What is Math?" but the correct answer was "What are the majority?" It did not occur for me to even look up [Arithmocracy] as a legitimate word, but it is real.
The second round, I guesed five of the six themese for the categories. For category "Hawk" eyes, the "Hawk" was in quotation marks, so I wrote "All answers would start with the word Hawk or end with the word "eyes". I was close, the correct theme was that the word "hawk" would appear in the front, middle or end of the correct response.
In this second round, I got 28 of 30 correct. I got 93 percent correct with Internet searching. Ironically, it was the category "German Foods" that caught me off guard.
For, the answer was "Pichelsteiner Fleisch, a favorite of Otto von Bismarck, is this one-pot concoction, made with beef & pork". I know that "fleisch" is a German word for meat, so I guessed "What is sausage?" but the correct response was "What is stew?" I should have paid more attention to the "one-pot concoction" part of the answer.
For the answer was "Mimi Sheraton says German stuffed hard-boiled eggs are always made with a great deal of this creamy product". I didn't realize that "stuffed eggs" was German for "deviled eggs". Instead, I found Mimi Sheraton's "The German Cookbook" on Google Books, and jumped to the page for "Stuffed Eggs" The ingredients I read included whippedc cream, cognac, and worcestershire sauce. Taking the "creamiest" ingredient of these, I wrote down "What is whipped cream?" However, it turned out I was actually reading the ingredients for "Crabmeat Cocktail" that was coninuing from the previous page. I thought it was gross to put whipped cream with eggs, and should have known better. The correct response was "What is mayonnaise?"
In the final round, the category was "Political Parties". This could either be political organizations like Republicans and Democrats, or festivities like the Whitehouse Correspondents Dinner. The answer was "Only one U.S. president represented this party, and he said, I dread...a division of the republic into two great parties." So, we can figure out the answer refers to political organizations, but both Democrat and Republican are ruled out because each has had multiple presidents. So, looking at a [List of Political Parties of each US President], I found that there were four presidents in the Whig party, four in the Democrat-Republic party, but only one president in the Federalist party (John Adams), and one in the War Union party (Andrew Johnson). Looking at [famous quotes from John Adams] first, I found the quote, it matched, and so I wrote down "What is the Federalist party?". I got it right, as did two of the three contestants. Ironically, the one contestant who got it wrong, the returning champion web programmer, wagered a small amount, so he still had more money after the round and won the game overall.
Total time for the entire exercise: 75 minutes. I was able to do this faster as I skipped searching the internet for the responses I was confident on.
To find out when Jeopardy is playing in your town, consult the [Interactive Map].
"When Watson is booted up, the 15TB of total RAM are loaded up, and thereafter the DeepQA processing is all done from memory. According to IBM Research, the actual size of the data (analyzed and indexed text, knowledge bases, etc.) used for candidate answer generation and evidence evaluation is under 1 Terabyte (TB). For performance reasons, various subsets of the data are replicated in RAM on different functional groups of cluster nodes. The entire system is self-contained, Watson is NOT going to the internet searching for answers."
I had several readers ask me to explain the significance of the "Terabyte". I'll work my way up.
A bit is simply a zero (0) or one (1). This could answer a Yes/No or True/False question.
Most computers have standardized a byte as a collection of 8 bits. There are 256 unique combinations of ones and zeros possible, so a byte could be used to storage a 2-digit integer, or a single upper or lower case character in the English alphabet. In pratical terms, a byte could store your age in years, or your middle initial.
The Kilobyte is a thousand bytes, enough to hold a few paragraphs of text. A typical written page could be held in 4 KB, for example.
The IBM Challenge to play on Jeopardy! is being compared to the historic 1969 moon landing. To land on the moon, Apollo 11 had the "Apollo Guidance Computer" (AGC) which had 74KB of fixed read-only memory, and 2KB of re-writeable memory. Over [3500 IBM employees were involved] to get the astronauts to the moon and safely back to earth again.
The importance of this computer was highlighted in a [lecture by astronaut David Scott] who said: "If you have a basketball and a baseball 14 feet apart, where the baseball represents the moon and the basketball represents the Earth, and you take a piece of paper sideways, the thinness of the paper would be the corridor you have to hit when you come back."
The Megabyte is a thousand KB, or a million bytes. The 3.5-inch floppy diskette, mentioned in my post [A Boxfull of Floppies] could hold 1.44MB, or about 360 pages of text.
In the article [Wikipedia as a printed book], the printing of a select 400 articles resulted in a book 29 inches thick. Those 5,000 pages would consume about 20 MB of space.
One of my favorite resources I use to search is the Internet Movie Data Base [IMDB]. Leaving out the photos and videos, the [text-only portion of the IMDB database is just over 600 MB], representing nearly all of the actors, awards, nominations, television shows and movies. A standard CD-ROM can hold 700MB, so the text portion of the IMDB could easily fit on a single CD.
The Gigabyte is a thousand MB, or a billion bytes. My Thinkpad T410 laptop has 4GB of RAM and 320GB of hard disk space. My laptop comes with a DVD burner, and each DVD can hold up to 4.7GB of information.
The popular Wikipedia now has some 17 million articles, of which 3.5 million are in English language. It would only take [14GB of space to hold the entire English portion] of Wikipedia. That is small enough to fit on twenty CDs, three DVDs, an Apple iPad or my cellphone (a Samsung Galaxy S Vibrant).
Perhaps you are thinking, "Someone should offer Wikipedia pre-installed on a small handheld!" Too late. The [The Humane Reader] is able to offer 5,000 books and Wikipedia in a small device that connects to your television. This would be great for people who do not have access to the internet, or for parents who want their kids to do their homework, but not be online while they are doing it.
In the latest 2009 report of [How Much Information?] from the University of California, San Diego, the average American consumes 34 GB of information. This includes all the information from radio, television, newspapers, magazines, books and the internet that a person might look at or listen to throughout the day. This project is sponsored by IBM and others to help people understand the nature of our information-consuption habits.
Back in 1992, I visited a client in Germany. Their 90 GB of disk storage attached to their mainframe was the size of three refrigerators, and took five full-time storage administrators to manage.
The Terabyte is a thousand GB, or a trillion bytes. It is now possible to buy external USB drive for your laptop or personal computer that holds 1TB or more. However, at 40MB/sec speeds that USB 2.0 is capable of, it would take seven hours to do a bulk transfer in or out of the device.
IBM offers 1TB and 2TB disk drives in many of our disk systems. In 2008, IBM was preparing to announce the first 1TB tape drive. However, Sun Microsystems announced their own 1TB drive the day before our big announcement, so IBM had to rephrase the TS1130 announcement to [The World's Fastest 1TB tape drive!]
A typical academic research library will hold about 2TB of information. For the [US Library of Congress] print collection is considered to be about 10TB, and their web capture team has collected 160TB of digital data. If you are ever in the Washington DC, I strongly recommend a visit to the Library of Congress. It is truly stunning!
Full-length computer animated movies, like [Happy Feet], consume about 100TB of disk storage during production. IBM offers disk systems that can hold this much data. For example, the IBM XIV can hold up to 151 TB of usable disk space in the size of one refrigerator.
A Key Performance Indicator (KPI) for some larger companies is the number of TB that can be managed by a full-time employee, referred to as TB/FTE. Discussions about TB/FTE are available from IT analysts including [Forrester Research] and [The Info Pro].
The website [Ancestry.com] claims to have over 540 million names in its genealogical database, with a storage of 600TB, with the inclusion of [US census data from 1790 to 1930]. The US government took nine years to process the 1880 census, so for the 1890 census, it rented equipment from Herman Hollerith's Tabulating Machine Company. This company would later merge with two others in 1911 to form what is now called IBM.
A Petabyte is thousand TB, or a quadrillion bytes. It is estimated that all printed materials on Earth would represent approximately 200 PB of information.
IBM's largest disk system, the Scale-Out Network Attach Storage (SONAS) comprised of up to 7,200 disk drives, which can hold over 11 PB of information. A smaller 10-frame model, the same size as IBM Watson, with six interface nodes and 19 storage pods, could hold over 7 PB of information.
For those of us in the IT industry, 1TB is small potatoes. I for one, was expecting it to be much bigger. But for everyone else, the equivalent of 200 million pages of text that IBM Watson has loaded inside is an incredibly large repository of information. I suspect IBM Watson probably contains the complete works of Shakespeare as well as other fiction writers, the IMDB database, all 3.5 million articles of Wikipedia, religious texts like the Bible and the Quran, famous documents like the Magna Carta and the US Constitution, and reference books like a Dictionary, a Thesaurus, and "Gray's Anatomy". And, of course, lots and lots of lists.
For those on Twitter, follow [@ibmwatson] these next three days during the challenge.
The Tucson Executive Briefing Center hosted 20 dignitaries from local companies and academia.
This is a historic competition, an exhibition match pitting a computer against the top two celebrated Jeopardy champions:
Brad Rutter, won $3.2 million USD on Jeopardy!, winning 5 days on the show, and then three later tournamets.
Ken Jennings, winning $2.5 million in a 74-day winning streak on Jeopardy!
One of the members of the audience had never seen an episode of Jeopardy! in his life.
(Note: there are NO SPOILERS in this blog post. If you have not yet watched the show, you are safe to continue reading the rest of this post. I will not
disclose the correct responses to any of the clues nor how well each contestant scored.)
Calline Sanchez, IBM Director, Systems Storage Development for Data Protection and Retention, kicked off today's ceremonies.
The IBM Watson computer, named after IBM founder Thomas J. Watson, has been developed over the past 4 years by a team of IBM scientists who set out to accomplish a grand challenge - build a computing system that rivals a human's ability to answer questions posed in natural language with speed, accuracy and confidence. IBM Research labs in the United States, Japan, China and Israel [collaborated with Artificial Intelligence (AI) experts at eight universities], including Massachusetts Institute of Technology (MIT), University of Texas (UT) at Austin, University of Southern California (USC), Rensselaer Polytechnic Institute (RPI), University at Albany (UAlbany), University of Trento (Italy), University of Massachusetts Amherst, and Carnegie Mellon University.
(Disclaimer: I attended the University of Texas at Austin. My father attended Carnegie Mellon University.)
Last week, NOVA on PBS had a special episode on the making of IBM Watson, you can [watch it online] on their website. Delaney Turner, IBM Social Media Communications Manager for Business Analytics Software, has posted [his observations of Nova].
Since IBM Watson is the size of 10 refrigerators and weighs over 14,000 pounds, it was easier to design the Jeopardy! set at the TJ Watson Research lab in Yorktown Heights, NY, than to ship it over to California where the show is normally recorded. Two of the visual designers that worked on this set, as well as on the visual appearance of Watson, live in Tucson and were part of our audience today.
The IBM Challenge consists of a two-game tournament, where the scores of both games will be added to determine winner rankings. The producers of Jeopardy! will give $1 million dollars USD to first place, $300,000 to second place, and $200,000 to third place. Regardless of outcome, [IBM will donate all of its winings to charity]. The two human contestants plan to donate half of their earnings to their favorite charities as well.
Jeopardy! The IBM Challenge
Alex Trebek introduces IBM Watson, explaining that it can neither hear nor see. It will receive all information electronically. Categories and clues will be sent as text files via TCP/IP over Ethernet at the same time the two human contestants see them so that all have the same time to think about the right answer.
Watson has two rows of five racks, back to back. This was done so that cold air could rise up from holes in the tile floors around the unit, and all the hot air would be forced into the center and up to the ceiling return. This technique is known as "hot aisle/cold aisle" design. Alex Trebek opens one of the rack doors to show a series of 4U-high IBM Power 750 servers.
The avatar is a representation of Watson, as the machine itself is too big to fit behind the podium. The avatar is IBM's "Smarter Planet" logo with orbiting streaks and circles. It shows "Green" when it has high confidence, and orange when it gets an answer wrong. When busy thinking, the streaks and circles speed up, the closest we will see to "watching a computer sweat."
During the show, an "Answer panel" shows Watson's top three candidate responses, with confidence level compared to its current "buzz threshold".
Watson knows what it knows, and knows what it doesn't know. Here is an [Interactive Watson Game] on New York Times website to give you an idea of how the answer panel works. I was impressed with how close all three candidate answers were. In a question about Olympic swimmers, all three candidates are Olympic swimmers. In a question about the novel "Les Miserables", all three candidates were characters of that novel.
Well, IBM Watson did well, but missed answered some questions incorrectly. This [parody Slate video] pokes fun at this. Here were some discussions we had after the show ended:
IBM did not do well in categories that required [abductive reasoning]. For example, to identify two or three things that happened in different years, and then postulate that what they all have in common is a specific decade (such as the 1950s) is difficult.
Watson does not hear the wrong answers from the two human contestants. For one question, Ken buzzes in first, guesses wrong, then Watson buzzes in with the same exact response. Alex Trebek rebukes Watson with "No, Ken just said that!" Brad would learn from their mistakes and guess correctly for the score.
Watson is provided the correct answer after a contestant guesses it correctly, or if nobody does, when Alex provides the correct response. This is sent as a text message to Watson immediately, so that it can use this information to adjust its algorithms and machine-learning for future clues in that same category. This was evident in the "Answer panel" on the fourth and fifth attempts on the category of "Decades".
With this demonstration, IBM Research has advanced science by leaps and bounds for the Articial Intelligence community. IBM is a leader in Business Analytics, and this technology will find uses in a variety of industries. The average knowledge worker spends 30 percent of her time looking for information on corporate data repositories. By demonstrating a computer that can provide answers quickly, employees will be more productive, make stronger business decisions, and have greater insight.
Day 1 was only able to cover the first round of Game 1. This allowed more time to talk about the history and technology of IBM Watson. Tomorrow, the contestants will finish Game 1 and head into Game 2.
The IBM Challenge was a big success. One of the contestants, Ken Jennings, [welcomes our new computer overlords]. Congratulations are in order to the IBM Research team who pulled off this Herculean effort!
Some folks have poked fun at some of the odd responses and wager amounts from the IBM Watson computer during the three-day tournament. Others were surprised as I was that the impressive feat was done with less than 1TB of stored data. Here is what John Webster wrote in CNET yesterday, in hist article [What IBM's Watson says to storage systems developers]:
"All well and good. But here's what I find most interesting as a result of what IBM has done in response to the Grand Challenge that motivated Watson's creators. We know, from Tony Pearson's blog, that the foundation of Watson's data storage system is a modified IBM SONAS cluster with a total of 21.6TB of raw capacity. But Pearson also reveals another very significant, and to me, surprising data point: "When Watson is booted up, the 15TB of total RAM are loaded up, and thereafter the DeepQA processing is all done from memory. According to IBM Research, the actual size of the data (analyzed and indexed text, knowledge bases, etc.) used for candidate answer generation and evidence evaluation is under 1 Terabyte."
What Pearson just said is that the data set Watson actually uses to reach his push-the-button decision would fit on a 1TB drive. So much for big data?"
To better appreciate how difficult the challenge was, and how a small amount of data can answer a billion different questions, I thought I would cover Business Intelligence, Data Retrieval and Text Mining concepts.
"In this paper, business is a collection of activities carried
on for whatever purpose, be it science, technology,
commerce, industry, law, government, defense, et cetera.
The communication facility serving the conduct of a business
(in the broad sense) may be referred to as an intelligence
system. The notion of intelligence is also defined
here, in a more general sense, as the ability to apprehend
the interrelationships of presented facts in such a way as
to guide action towards a desired goal."
Ideally, when you need "Business Intelligence" to help you make a better decision, you perform data retrieval from a structured database for the specific information you are looking for. In other cases, you might be looking for insight, patterns or trends. In that case, you go "data mining" against your structured databases.
Here's a simple example. John runs a fruit stand. One day, he kept track of how many apples and oranges were bought by men and women. How many questions can we ask against this small set of data? Let's count them:
How many apples were sold to men?
How many apples were sold to women?
How many oranges were sold to men?
How many oranges were sold to women?
But wait! For each row and column, we can combine them into totals.
How many apples were sold in total?
How many oranges were sold in total?
How many fruit in total were sold to men?
How many fruit in total were sold to women?
How many fruit in total were sold?
But wait, there's more! Each row and column can be evaluated for relative percentages, as well as percentages of each cell compared to the total. You could make five relevant pie-charts from this data. This results in 16 more questions, such as:
Of the fruit purchased by men, what percentage for apples?
Of all the apples purchased, what percentage by women?
And that's not including more ethereal questions, such as:
Are there gender-specific preferences for different types of fruit?
What type of fruit do men prefer?
This is just for a small set, two market segments (by gender) and two products (apples and oranges). However, if you have many market segments (perhaps by age group, zip code, etc.) and many products, the number of queries that can be supported is huge. For small sets of data, you can easily do this with a spreadsheet program like IBM Lotus Symphony or Microsoft Excel.
But why limit yourself to two dimensions? The above example was just for one day's worth of activity, if John captures this data for every day for historical and seasonal trending, it can be represented as a three-dimensional cube. The number of queries becomes astronomical. This is the basis for Online Analytical Processing (OLAP), and three-dimensional tables are often referred to as [OLAP cubes].
Back in 1970, IBM invented the Structured Query Language [SQL], and today, nearly all modern relational databases support this, including IBM DB2, Informix, Microsoft SQL Server, and Oracle DB. SQL poses two challenges. First, you had to structure the data in advance to the way you expect to perform your ad-hoc queries. Deciding the groups and categories in advance can limit the way information is recorded and captured.
Second, you had to be skilled at SQL to phrase your queries correctly to retrieve the data you are after. What ended up happening was that skilled SQL programmers would develop "canned reports" with fixed SQL parameters, so that less-skilled business decision makers could base their decisions from these reports.
IBM has fully integrated stacks to help process structured data, combining servers, storage, and advanced analytics software into a complete appliance. IBM offers the [Smart Analytics System] for robust, customized deployments, and recently acquired [Netezza] for pre-configured, and more rapid deployments.
However, the bigger problem is that more than 80 percent of information is not structured!
Semi-structured data like email provides some searchable fields like From and Subject. The rest of the information is unstructured, such as text files, photographs, video and audio. To look for specific information in unstructured sources can be like looking for a needle in a haystack, and trying to get insight, patterns or trends involves text mining.
This, in effect, is what IBM Watson was able to perform so well this week. Finding the needle in the haystacks of unstructured data from 200 million pages of text stored in its system, combined with the ability to apprehend the interrelationships of meaning and subtle nuance, resulted in an impressive technology demonstration. Certainly, this new technology will be powerful for a variety of use cases across a broad set of industries!