Those who know how SAS has bundled text analytics as an add-on to SAS Enterprise Miner, the fact that organizations are implementing analytical solutions to retain current customers and win new ones -- you can conclude that seeds have been sown (Data Mining installed). For 2009 our challenge is to continue to pour water (to spread awareness) so Text Mining can indeed blossom .
Theodore Tanner blogged on predictions regarding the future of predictive analytics,semantic intelligence and vanilla BI applications made by industry analysts. I applaud Jim Kobielus who cites Text Analytics as key to staying strong (along with predictive analytics and Data Mining).
Last month when Sascom asked us for our 2009 predictions, you saw me jump in and add mine. For the past five years, we've seen Text Analytics sprout as an "emerging technology" attracting some interest by manufacturing companies for warranty solutions and occasional call centers. Many have no clue what steps to take to implement text analytics much less reap ROI. How about you ? do you think the time is ripe for text analytics to MAKE A DIFFERENCE ?
In describing SAS’ qualifications for this honor the report authors noted: “SAS's recent acquisition of Teragram will not only serve to enhance its position by adding natural language processing and advanced linguistic technology to its text mining offering, but it will also enable SAS to add enterprise and mobile search to its BI offerings.”
This comment by Gartner is revelatory in light of the current trend to view unstructured data as the “dark matter” of the enterprise ( i.e. the evolving source of income and profitability). Text mining, text analytics, document search, term/concept retrieval and classification capabilities – such as provided by SAS® Text Miner and SAS® Content Categorization – were all missing criteria in the evaluation of the vendors. The only other vendor noted for text analytics ability was SAP.
In a symposium given last year by TDWI (The Data Warehouse Institute), entitled “The Shifting Data Continuum: Or Why Your Data Warehouse Needs Unstructured Data”, Philip Russom shared results collected from a survey on sources of warehouse data. There he displayed a graphic that indicate huge, exponential growth in unstructured data sources in organizations today.
The huge red triangle in the TDWI report indicates all the unstructured sources of data that are likely to grow in the next three years. Given that – according to Gartner -- SAS has only one acknowledged competitor in this BI area -- SAP. Therefore this creates a huge opportunity to gain competitive advantages compared to the other acknowledged vendors in the report … as well as the other vendors that we meet in the market who do not appear in the Gartner report.
This growth in the “dark matter” of the enterprise will be enabled and facilitated by the kind of text mining/text analytics capabilities that SAS has built and which Gartner acknowledges in its “Magic Quadrant” report.
If the TDWI analysis holds true then it is likely that text mining/text analytics capabilities will soon surface as explicit qualifiers for “leaders” in the BI (not to mention Business Analytics) area.
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Post-Conference Data Mining Workshop
This post-conference, half day workshop on data mining will be held Wednesday, March 25 at 1:30-5:00 p.m. It will offer another opportunity to expand your SAS data mining and predictive modeling skills. Stay later to take advantage of exclusive training opportunities. Find out more about the post-conference workshop.
Pre-conference Seminars & Statistical Tutorials
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Updated Jan 27:
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Original post, 7 Jan, 2009
A Controversial Review by Anee Milley from SAS
7 Jan, 2009, SAS-L
7 Jan, 2009, R-help
8 Jan, 2009, Ashlee Vance‘s blog
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9 Jan, 2009, Anee Milley
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There are some new financial functions in SAS9.2 Base, including 8 options pricing functions(formerly in SAS Risk Dimension). These functions can compute the price of both call and put options on different underlying assets (stock, futures, currency, and exchange asset), using the following models respectively:
- Black-Scholes model，the traditional stock options pricing model, see Fischer Black and Myron Scholes (1973) ;
- Black model，extension of Black-Scholes model on futures option (also called Black-76 model)，see Fischer Black(1976);
- Garman-Kohlhagen model，pricing model on foreign currency options，see Mark Garman and Steven Kohlhagen(1983) ;
- BLACKCLPRC: calculates the call price for European options on futures, based on the Black model.
- BLACKPTPRC: calculates the put price for European options on futures, based on the Black model.
- BLKSHCLPRT: calculates the call price for European options, based on the Black-Scholes model.
- BLKSHPTPRT: calculates the put price for European options, based on the Black-Scholes model.
- GARKHCLPRC: calculates the call price for European options on currencies, based on the Garman-Kohlhagen model.
- GARKHPTPRC: calculates the put price for European options on currencies, based on the Garman-Kohlhagen model.
- MARGRCLPRC: calculates the call price for European options on exchange assets, based on the Margrabe model.
- MARGRPTPRC: calculates the put price for European options on exchange assets, based on the Margrabe model.
For more，see SAS9.2 online help，Functions and CALL Routines by Category: Financial：
Note: A good web site for options pricing with different models, http://www.montegodata.co.uk/