Knowledge-based computing: next generation of business intelligence?

pablopPablo Picasso once said “Computers are useless.  They only give you answers.”  The truth is that computers have to work very hard to provide answers to what appear to be simple questions.  While we are buried in terabytes, petabytes and exobytes of data – answers and information can be very hard to come by, especially information necessary for serious business decisions.   Data must be viewed in context of a subject area to become information, and analytic techniques must be applied to information in order to create knowledge worthy of taking action.  The challenge is getting data into context within a subject area and applying the right analytic techniques to get “real” answers.

Enter Wolfram Alpha, as an “answer” engine.  Once touted as the next generation of search engine, this web application combines free form natural language input, i.e. simple questions, and dynamically computed results.  Behind the scenes, a series of supercomputers provide linguistic analysis (context for both the question and the answer), ten terabytes of curated data that is constantly being updated, dynamic computation using 50,000 types of algorithms and equations, and computed presentation with 5,000+ types of visual and tabular output.  Sound impressive?  It could easily be a glimpse of the next generation of business intelligence and decision-support systems.

Wolfram Alpha lets you input a query that requires data analysis or computation, and it delivers the results for you. It’s “curated” data is specially prepared for computation— data that’s been hand-selected by experts working with Wolfram, who go through steps to make sure the raw data is tagged semantically and is presented unambiguously and precisely enough that it can be used for accurate computation.  Alpha demonstrates the real power of metadata – data about data, and the importance of semantic tags for categorizing data into a context necessary for providing knowledge and, thus, answers.

Wolfram Alpha is not a search engine according to Wolfram Research co-founder Theodore Grey.  It is not a replacement for Google.  He says that Alpha is very, very different from a search engine. “Search engines are like reference librarians,” Grey explained. “Reference librarians are good at finding the book you might need, but they’re useless at interpreting the information for you.”  Alpha takes reams of raw information and performs computations using those data.  It produces pages of new information that have never existed on the Internet. “Search engines can’t find an answer for you that a Web page doesn’t have,” Grey explained.

“It’s been a dream of many people for a long time to have a computer that can answer questions,” said Grey. “A lot of people may think of a search engine as that, but if you think about it, what search engines do is an extreme limited subset of that sort of thing.”  Examples of how Alpha can be used today range from solving difficult math equations to doing genetic analysis, examining the historic earnings of public companies, comparing the gross domestic products of different countries, even measuring the caloric content of a meal you plan to make. You can find out what day of the week it was on your birthday, or show the average temperature in your area going back days, months or years.

Wolfram Alpha would make an “ultimate” business intelligence application by computing over an enterprise data warehouse once the data was properly “curated.”  The ability to create knowledge from data, particularly to create actionable answers is what business executives really expect – not prettier presentations.  The only questions left for Alpha are:

  1. who can curate your data for you, and
  2. how quick can you see Alpha running over your data?

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