• Dennis reported on an internal SAP Enterprise Twitter research project, and pointed at a number of the other pages I’ll mention. (Note: If that goes anywhere, it will have to be in conjunction with Business Objects.)
• Jevon MacDonald listed pros (many) and cons (few) of Enterprise Twitter.
• Andrew McAfee argues at length that an enterprise needs multiple social networking tools, to match up with different intensities of collaboration among coworkers.
• Niall Cook offers a short, convincing use case for Enterprise Twitter.
• JP Rangaswami also offers use cases.
• Ed Yourdon argues that Twitter is “good enough” for enterprises. But he seems to concede it could indeed be a lot better.
• Paul Gillin praises Twitter’s business potential for us self-employed consultant types.
• Sid offers a number of quick-hit use cases for Enterprise Twitter.
• Bill Ives takes a more skeptical view, focusing on enterprises uses of today’s Twitter.
• Nancy offers many Twitter use cases, some of which are enterprise-relevant.

Here’s my take on the subject.

I see four basic (and somewhat overlapping) use cases for Enterprise Twitter:

Real-time short communication. This is a major part of enterprise communication, especially when face-to-face meetings need to be arranged. Enterprise Twitter could do this better than email. It would require limited archiving, decent URL-attaching, and good targeting or filtering by user (work)groups.

Real-time wide outreach. The CEO could (briefly!) share her thought for the day. The cafeteria could announce specials. The salesman on the Universal ACME account could see if anybody else is familiar with UA. The users who help others with crashed PCs could let themselves be interrupted only when they actually don’t mind helping. This is probably the Enterprise Twitter use that requires the fewest changes from Twitter’s current form, although stuffier enterprises may require profanity filters and the like.

IM integration. Instant messaging is a very useful enterprise tool, since the alternatives are less timely or more distracting. That can and should be wholly integrated with Enterprise Twitter. Sometimes IM conversations expand to more than two people. That’s all the more reason for Twitter integration.

Beyond the firewall. IM discussions can and should penetrate the firewall, including employees, partners, customers, suppliers, and so on, just as email does. The Enterprise Twitter form of this is like a permanent (and hence very low average volume) IRC/AOL chatroom. To make that happen you need good group selectivity, good security, and perhaps also some nannyware oversight (profanity, intellectual property, hucksterism, etc.) .

If the messaging and office productivity software vendors don’t provide filter-rich Enterprise Twitter, somebody else most likely will.

… there are few to no instances of a single enterprise search engine being the only search solution for any major enterprise. Even when an organization “standardizes” on one product for its enterprise search, there will be dozens of other instances of search deployed for groups, divisions, and embedded within applications. Just two examples are the use of Vivisimo now used for USA.gov to give the public access to government agency public content, even as each agency uses different search engines for internal use. Also, there is IBM, which offers the OmniFind suite of enterprise search products, but uses Endeca internally for its Global Services Business enterprise.

Brava to her.

One consequence, apparently, is that federated search is a bigger deal than I realized. If different corpuses are indexed by different systems, there’s something to be said for using each search engine to get the result sets it naturally can, and then reranking them at the end of the search. Accordingly, she’s high on MuseGlobal. And maybe there’s potential for the analogous technology at SAP/BOBJ/Inxight after all.

Technorati Tags: enterprise search, federated search, MuseGlobal, Inxight

• Voice of the Customer is definitely tops.
• Some of the other applications Attensity and Clarabridge mentioned appear as well (e.g., antifraud).
• Business Objects also has a couple of customers looking at text mining as an aid to medical records, e.g. by helping to catch errors in tabular-field coding.
• There are some projects in actual investment research/analysis/trading, e.g. in correlating news announcements and stock price movements.

The Business Objects/Inxight folks also made a couple of interesting general technical points. When I challenged the usefulness of text analytics in dashboards, they pointed out how it can at least be a good drill-down. (Example: You’re getting unusually many of customer complaints in a particular time frame; you drill down into a text mining-based graphic to see which particular areas of complaint have spiked.) Also, when I mentioned exhaustive extraction, Ian Hersey pointed out that in many cases the intermediate results of Inxight tagging and so on happen to be stored in an RDBMS.

Perhaps most important, I got a general feeling that Business Objects is serious about integrating Inxight into its general product offerings, which is not good news for independent text mining vendors such as Attensity or Temis (except insofar as it heats up the acquisition market for same). On the other hand, I’ve gotten nothing but confirmation of my view that Business Objects plans to remain a good OEM partner, even to competitors such as SAS.

This is my first post from the conference. There surely will be more soon on DBMS2 and the Monash Report.

Get great research about text mining, data warehouse appliances, and other hot analytics-related topics! Subscribe to our comprehensive (if not exhaustive) feed, by RSS/Atom or e-mail! We recommend taking the integrated feed for all our blogs, but blog-specific ones are also easily available.

Technorati Tags: Business Objects, Inxight, text analytics

 This could be interesting …

First, Ian points out that there are circumstances when, due to security and permissions, you can’t really index everything via one search engine. Specifically, he offers the government as an example. OK, I can see that in the government, with its classified and/or regulated silos. However, I have trouble thinking of many more examples. While there certainly are plenty of instances where a variety of organizations share information on a somewhat arms-length basis, it’s tough to think of such cases where federated text search would come into play.

Second, Ian in essence disputes my claim of inferior functionality. While implicitly conceding — as well he should! — that Inxight’s Awareness Server doesn’t do some things full-featured search engines do, he points out analytic features that may not be found in conventional search engine offering. The big one he calls out is faceted search — which of course was the core of Intelliseek, the acquisition Awareness Server came from. Hmm. Faceted search has a checkered history, with Excite and Northern Light being perhaps the most visible among many failures. On the other hand, it’s a great idea that keeps being tried, and some versions — notably Endeca’s — have turned out well.

I guess I’ll have to reserve judgment on that part until I look at Inxight’s product and see what they do and don’t actually have.

Well, the event-processing guys are active in that market too. At least StreamBase is. It was an obvious guess to ask if they were, and over the past few months I’ve gotten confirmation (including that they partner w/ Inxight just like almost everybody else does). Here, quoted with permission and lightly edited, is what StreamBase VP Marketing Bill Hobbib has to say on the subject

Regarding text filtering and processing, we’ve done work in financial services for a hedge fund and extensive work with the federal government and intelligence community. The existing StreamBase schema and message/field structure supports a wide array of message types, and text parsing can be done in either the SMTP adapter or the StreamBase engine, where the text processing occurs. Multiplexing onto different streams/schemas is supported.

In terms of text processing, StreamBase can process emails, documents, sentences, individual words or letters using StreamSQL’s existing capabilities, including a variety of built-in standard string operations, or user-defined functions, custom operators, and user-defined aggregates. We can also partner with text-mining companies.

Though you didn’t ask about processing media such as audio or video data, the new BLOB datatype is designed for this purpose. We partner with feature extraction vendors (e.g. speech to text) where necessary, as we don’t process the native audio or video data–just the metadata or the extracted features and converted files.

More on StreamBase can be found over on DBMS2, e.g. in this post or this one.

Keep getting great research about text analytics, data management and related technologies. Get a FREE subscription by RSS/Atom or e-mail!

Business Objects/Inxight have now reached that point. Even so, my briefing yesterday had some aspects worth writing up.

They are strong and convincing on the claim that Inxight’s OEM business will continue to be an area of emphasis, even when selling to BOBJ competitors. Specifically:

• When I pointed out that there had been some intemperate cocktail comments to the contrary, they winced.

• They pointed out, correctly, that Crystal Reports had been OEMed to various Business Objects direct competitors. (That said, Hyperion obviously drop Crystal after the Brio acquisition, and SAP has talked about replacing Crystal as well.) And in an Inxight-specific example, their federated search product Awareness Server is partnered with Oracle Enterprise Search, and that partnership is continuing for now.

• Inxight’s OEM sales are being folded into the highly successful Business Objects/Crystal Reports OEM channel. Frankly, I think this will go fine. While I wouldn’t necessarily look for much in the way of successful cross-selling between the two product lines, they probably also won’t screw a good thing up. That aspect is no harder than other mergers Business Objects has pulled off successfully.

Actually, there are a lot more than two product lines. E.g., there’s visualization technology from both sides of the merger. So some real synergies may actually exist. Also, there are some ISVs who OEM a full BI product suite, so to the extent general product line integration works in the enterprise market, it could work well in the indirect channel as well.

Their vision for text analytics integrated into business intelligence is airy and obvious, with lots of emphasis on the distinction between “structured” and “unstructured” data, and how great it will be to combine them. To their credit, they mercifully skipped the standard Gartner quote about 85% or so of data being unstructured, but otherwise I think they touched on most or all of the standard platitudes. (At least, they did in their slides. I asked for the slides in advance, and then strongly requested they NOT take me through the deck in the actual briefing. They obliged very nicely.)

In the early interest from existing BOBJ customers, there’s no particular pattern to the types of text analytics application or use envisioned.

Inxight’s classified Federal-business subsidiary will be left standalone, with the obvious intent of having it be affected as little as possible by this merger.

They seem serious about properly productizing Inxight’s visualization technology, which currently is a grab-bag of SDKs. This would include a set of core capabilities, database schemas that are straightforward to populate, and so on. And this would of course be packaged with other snazzy visualization technologies such as Crystal Excelsius.

Inxight seems to have had three primary visualization “products”, namely:

• Time Wall, which places events in time along a virtual “wall.” BOBJ says that this is something customers had actually been asking for, although on whiffed on asking which particular applications the customers had in mind. In Inxight’s case, unsurprisingly, the events were typically ones that were extracted from documents. However, one could also use this approach to show cases where, for example, various KPIs (Key Performance Indicators) first deviated from accepted bounds.

• Star Tree, which shows relationships, e.g. among people. This has been used by large enterprises to figure out how their own employees work together. It also has obvious potential national security applications.

• Table Lens, which displays information of high dimensionality. This may be the one that integrates most straightforwardly with conventional BI.

As a general rule – perhaps because of the programming required to implement them – these visualization products tend to be deployed for very specific applications. Naturally, it is BOBJ’s hope to get them used in broader enterprise deployments.

We also talked about Inxight’s federated search product Awareness Server. Frankly, that discussion was pretty confused. They asserted that this was an IDD (Information Discovery and Display – i.e., BI) product, while classic text analytic information extraction was more EIM (Enterprise Information and Management – i.e., ETL). I guess that’s because it fetches information and displays it directly, as a query tool does, while information extraction merely stages information into a database for future querying.

The problem with federated search as a product is that it’s directly competitive with what focused search engines do. Leading relational DBMS formally have federated search capabilities, but almost nobody ever uses them; instead, the data they index is the data they actually manage. Search engines, on the other hand, VERY commonly index documents they aren’t responsible for directly managing. Thus, Awareness Server competes directly with Google OneBox, FAST, et al. And while I forgot to probe for feature/function details, I’d be surprised to discover that Awareness Server is truly competitive with the much more popular and mature alternatives.

• Inxight has around 120 employees. (And while I haven’t doublechecked this, apparently Inxight has been disclosed to have $26 million revenue.)

• At least half of Inxight’s business is OEM. Only 10% or so is enterprise, with the balance being government.

• Until recently, Inxight OEMed only basic tokenization (e.g., stemming), reserving higher-level tokenization (e.g., entity extraction) for direct sales (primarily to government). Recently, however, most or all of Inxight’s tokenization has been opened up to the OEM channel.

• Opinions differ about the visualization tools. There have been a small number of large (even seven-figure) sales. There are several different tools. Some or all are Java, vs. Business Objects’ recent Flash/Flex focus. My tentative position is to be quite skeptical, but I guess – fairly literally, actually – that we’ll see.

• Federated search and categorization still sound to me more like fond hopes than big deals yet.

• Tea leaves at Business Objects are contradictory about how much interference there will be with the business of OEMing to BOBJ’s competitors. I stand by my prior prediction – Business Objects will look for ways of tightly integrating Inxight’s OEM business into the rest of BOBJ, but ultimately will decide not to kill the golden goose. Yes, I recognize that Inxight will be a much smaller fraction of BOBJ’s business than DataDirect has been at its two corporate parents (currently Progress Software). Still, I think the DataDirect analogy is a highly instructive one.

Basically, I still think what I thought before.

Want to continue getting great research about search, text mining, and other hot text technology topics? Then get a FREE subscription, by RSS/Atom or e-mail! We recommend taking the integrated feed for all our blogs, but blog-specific ones are also easily available.

Technorati Tags: Inxight, Business Objects, text mining

Want to continue getting great research about text mining, BI, and other subjects related to text analytics? Then get a FREE subscription to our research, by RSS/Atom or e-mail! We strongly recommend taking the integrated feed for all our blogs, but blog-specific ones are also easily available.

Technorati Tags: Business Objects, Inxight, Informatica, patent