Lexmark and Search
March 20, 2016
Short honk. Last year, Forrester, the mid tier consulting firm, released a magic square for enterprise search. I noted this morning that Lexmark was relying on TechRepublic to push this old wine in a somewhat new bottle. You can see the pitch at this link. What’s remarkable about this particular magic square thing is that Lexmark is flagged as a leader in enterprise search. Lexmark as you may know acquired the ISYS Search Software system and Brainware a couple of years ago. ISYS is interesting because its technology was crafted in the 1980s. Lexmark’s financial challenges are similar to those faced by other print centric companies trying to make the transition to the digital ecosystem. But a leader in a sector which has largely embraced open source search technology? Interesting.
Stephen E Arnold, March 20, 2016
Elasticsearch Case Example: Scrunch
March 19, 2016
If you are using or considering the use of Elasticsearch, you will want to read “Lessons Learned From A Year Of Elasticsearch In Production.” The write up contains five excellent tips.
I highlighted this statement as one which Elasticsearch users will want to keep in mind:
If you can afford SSDs, then buy them. Elasticsearch does a lot of reading from disk and fast disks equal fast queries.
Elasticsearch is one reason proprietary search vendors are gasping for air.
Stephen E Arnold, March 19, 2016
Microsoft Delve Described as Tainted
March 10, 2016
I read “Microsoft Delve Faces Challenges in Enterprise Search Role.” Seemed like old news to me. Fast Search never seemed to be in sync with what Fast marketers said the system could do.
In this write up, there is a darned remarkable statement. Here’s the quote that goes right into my “Did Someone Really Say This?” folder:
Delve is already a tainted product…
Gasp. Microsoft bought Fast Search & Transfer in 2008 for $1.2 billion. After the deal closed, the president of Fast Search found himself on the wrong end of Norwegian law. Microsoft killed the Unix version of Fast Search and seemed to be commited to making good on the promises Fast Search marketers offered. Check out the pre-sale presentation to CERN for the “future according to Fast Search.”
SharePoint search, the cloud thing, and Bing—Is Microsoft focused on enterprise search or any search application?
Any way that is quite a statement about Delve. Tainted ain’t a positive word.
Stephen E Arnold, March 10, 2016
Watson Weakly: Jargon and Resource Allocations
March 9, 2016
In case you missed the news, IBM seems to be trimming its workforce. Does anyone remember Robert X. Cringely’s “IBM Is So Screwed?” I do. I would wager that Mr. Cringely remembers IBM’s suggestion that Mr. Cringely was off base with his analysis.
Perhaps Mr. Cringely is vindicated. I read “IBM Job Cuts: US Tech Giant Begins Mass Firing One Third of Workforce.” Hmmm. One third of a workforce having an opportunity to find its future elsewhere? That sounds like a swell way to greet spring 2016. March in like a lion and march out like a lamb. Is the lamb heading to the local meat packers?
Against this cheerful seasonal background, I want to mention “Moving from Enterprise Search to Cognitive Exploration.” This is a recycling of an earlier white paper for which one must register in order to read or download the document. Please, note that you will have to jump through some hoops to get this March 2016 publication. Do not complain to me about the link, the involvement of a middleman, and the need to provide details about your interest in enterprise search. Take it up with IBM; that is, if someone will take your call or answer your email. Hey, good luck with that.
What’s notable about this white paper is this word pair: Cognitive Exploration. Original? Nah. The phrase turns up in the title of a collection of essays called Cognitive Exploratioin of Language and Linguistics in 1999. The phrase is some of the jingoism from the super reliable psychology linguistics disciplines. IBM has dallied with the phrase for a number of years but in the RA world, the phrase is getting a jump start. An example of IBM’s arguement is that no one no longer runs a search across a customer service database. Nope, one cognitively explores that customer database.
Cognitive Exploration. It flows trippingly on the tongue does it not. IBM does not fire people; IBM RA’s them. (RA. Resource allocation or termination or reduction in force.)
What is Cognitive Exploration? Well, it is Lucene search plus some home brew code and a dollop of acquired technology. IBM’s original commercial enterprise search system (STAIRS) is just not up to the task of cognitively exploring one’s information assets it seems.
The white paper is a tribute to the search buzzwords that have been used by marketers in the past. I just love Cognitive Exploration.
What is it? For the full answer, you will need to read the 13 pages of explanation. Here’s a sampling of the facts in the write up:
Analysts expect the total data created and copied to reach 44 ZB by the year 2020 (Analyst firm IDC). After all, there are more than 204,000,000 emails launched every minute every day (Mashable.com). How do you manage, search, and process that data and turn it into usable information?
Yep, that’s a lot of information. How is an organization going to deal with “all” those zeros and ones? I suppose I would begin by using a system designed to manipulate large data flows. How about Palantir, BAE Systems, Leidos for starters. What no IBM? Bummer.
The IBM argument advances:
To meet today’s expectations, a search system must be able to access all of your important data sources and filter results based on a user’s access permissions within the organization.
I love the “all”. IBM obviously has nailed video, audio, binaries of various types, disparate file types, and dynamic content flows from intercepts, social media, and interesting sources from the Dark Web. I love “all” type solutions. Too bad these are science fiction based on my experience.
The fix is Cognitive Exploration. Thank you, IBM. A new buzzword to explain what search and retrieval has flubbed for — what? — 50 years” IBM explains:
Cognitive exploration is the combination of search, content analytics, and cognitive computing. Not only can cognitive exploration accelerate the rate at which users can find and navigate information; by leveraging advanced technologies such as content analytics, machine learning, and reasoning it has the potential to augment human expertise.
I don’t want to be a party pooper, but this is perilously close to Palantir’s “augmented intelligence” jargon. Attivio, BA Insight, and even the French folks at Sinequa use similar lingo. Me-too’ism at its finest? Nah, this is IBM, the outfit taking Groupon (a discount coupong business) to court for allegedly infringing on Prodigy patents. Prodigy? Remember that online service?
After snoozing through the white paper’s three pillars of Cognitive Exploration, I raced to the the finish line.
Cognitive Exploration involves the i2 type of relationship analysis, some good old fashioned cuddling between search and cognitive computing (think Watson, gentle reader), and a unified view or what a popular novelist calls “God’s eye” view. Please note that IBM offers some examples, but get the numbering wrong. Where is number one? Watson, Watson, can you assist me? Guess not. IBM’s cognitive exploration essay begins counting with number 2. I am okay with zero. I am okay with one. But I am not okay with an enumerated list beginning with the number two. Careless typo? Indifference? Rushing to the RA meeting? Don’t know. Cognitive Watson counts two, three, four, not one, two, three.
At the end of this remarkable description of Cognitive Exploration I learned:
The cognitive capabilities that can be leveraged by Watson Explorer are provided by the IBM Watson platform.
Isn’t this a recycling of some of the early 1990s marketing material from i2 Group Limited, which IBM bought. Isn’t this lingo influenced by Palantir’s explanations of its Gotham platform?
Omitted from the “all” I assume is the seamless interchange of Gotham files with i2 Analyst Notebook and i2 Analyst Notebook with Gotham. The users and customers have to learn that “all,” like Mr. Clinton’s “is” may not be exactly congruent with one’s understanding of “federation” and “unified.”
Enough already. Go for the close:
IBM Watson Explorer unlocks the value within your data, utilizing that information to help employees make well-informed decisions, provide better support, and identify more customers and business opportunities. By reaching across multiple silos of information within your enterprise, search results will include information never previously integrated into single solutions. Users will benefit from search results from all the data in your company, structured and unstructured, and include data from outside as well. Rather than trying to make good decisions with limited insight, cognitive exploration users can now extract and understand all of the valuable information at their fingertips.
With such a wonderful tool at IBM’s disposal, why is IBM’s management unable to generate revenues? Perhaps the silliness of the marketing explanation of Cognitive Exploration does not deliver the results that obviously someone at IBM believes.
I am stuck on that error in numbering, the recycling of Palantir’s marketing lingo, and the somewhat silly phrase “Cognitive Exploration.”
I won’t sail my Nina, Pinta, and Santa Maria to that digital shore. I will use Google Earth and tools which I know sort of work.
Stephen E Arnold, March 9, 2016
Enterprise Search Morphs
March 9, 2016
I read “One Size Doesn’t Fit All with Enterprise Search.” The problem for me is that the article does not discuss enterprise search. Sure, there are buzzwords like knowledge discovery, but the focus is on a quite specific type of search and retrieval application: Customer service.
The idea behind search as a substitute for a human who knows a product is simple. Think money, headcount, and personnel hassles or churn in the parlance of the customer support world. Let software do a thankless job and move on with sales. That support thing? Hey, let the customer find the answer.
The focus of the write up is on what is called the “self service customer.” The person or persona in the write up has a couple of alter egos; namely, a call center agent and a call center analyst.
What this has to do with enterprise search baffles me. No wonder vendors of basic search and retrieval are struggling to close deals. Instead of describing a specific use case and what systems and methods are needed to deflect the customer yet keep ‘em buying, the once useful phrase “enterprise search” is further devalued.
Why not do what IBM has done and invent a new phrase for an enterprise solution which few love and many prefer to view as a utility and a commodity tool? Cognitive exploration, anyone?
Stephen E Arnold, March 9, 2016
Enterprise Search Revisionism: Can One Change What Happened
March 9, 2016
I read “The Search Continues: A History of Search’s Unsatisfactory Progress.” I noted some points which, in my opinion, underscore why enterprise search has been problematic and why the menagerie of experts and marketers have put search and retrieval on the path to enterprise irrelevance. The word that came to mind when I read the article was “revisionism” for the millennials among us.
The write up ignores the fact that enterprise search dates back to the early 1970s. One can argue that IBM’s Storage and Information Retrieval System (STAIRS) was the first significant enterprise search system. The point is that enterprise search as a productized service has a history of over promising and under delivering of more than 40 years.
Enterprise search with a touch of Stalinist revisionism.
Customers said they wanted to “find” information. What those individuals meant was have access to information that provided the relevant facts, documents, and data needed to deal with a problem.
Because providing on point information was and remains a very, very difficult problem, the vendors interpreted “find” to mean a list of indexed documents that contained the users’ search terms. But there was a problem. Users were not skilled in crafting queries which were essentially computer instructions between words the index actually contained.
After STAIRS came other systems, many other systems which have been documented reasonably well in Bourne and Bellardo-Hahn’s A History of Online information Services 1963-1976. (The period prior to 1970 describes for-fee research centric online systems. STAIRS was among the most well known early enterprise information retrieval system.) I provided some history in the first three editions of the Enterprise Search Report, published from 2003 to 2007. I have continued to document enterprise search in the Xenky profiles and in this blog.
The history makes painful reading for those who invested in many search and retrieval companies and for the executives who experienced the crushing of their dreams and sometimes career under the buzz saw of reality.
In a nutshell, enterprise search vendors heard what prospects, workers overwhelmed with digital and print information, and unhappy users of those early systems were saying.
The disconnect was that enterprise search vendors parroted back marketing pitches that assured enterprise procurement teams of these functions:
- Easy to use
- “All” information instantly available
- Answers to business questions
- Faster decision making
- Access to the organization’s knowledge.
The result was a steady stream of enterprise search product launches. Some of these were funded by US government money like Verity. Sure, the company struggled with the cost of infrastructure the Verity system required. The work arounds were okay as long as the infrastructure could keep pace with the new and changed word-centric documents. Toss in other types of digital information, make the system perform ever faster indexing, and keep the Verity system responding quickly was another kettle of fish.
Research oriented information retrieval experts looked at the Verity type system and concluded, “We can do more. We can use better algorithms. We can use smart software to eliminate some of the costs and indexing delays. We can [ fill in the blank ].
The cycle of describing what an enterprise search system could actually deliver was disconnected from the promises the vendors made. As one moves through the decades from 1973 to the present, the failures of search vendors made it clear that:
- Companies and government agencies would buy a system, discover it did not do the job users needed, and buy another system.
- New search vendors picked up the methods taught at Cornell, Stanford, and other search-centric research centers and wrap on additional functions like semantics. The core of most modern enterprise search systems is unchanged from what STAIRS implemented.
- Search vendors came like Convera, failed, and went away. Some hit revenue ceilings and sold to larger companies looking for a search utility. The acquisitions hit a high water mark with the sale of Autonomy (a 1990s system) to HP for $11 billion.
What about Oracle, as a representative outfit. Oracle database has included search as a core system function since the day Larry Ellison envisioned becoming a big dog in enterprise software. The search language was Oracle’s version of the structured query language. But people found that difficult to use. Oracle purchased Artificial Linguistics in order to make finding information more intuitive. Oracle continued to try to crack the find information problem through the acquisitions of Triple Hop, its in-house Secure Enterprise Search, and some other odds and ends until it bought in rapid succession InQuira (a company formed from the failure of two search vendors), RightNow (technology from a Dutch outfit RightNow acquired), and Endeca. Where is search at Oracle today? Essentially search is a utility and it is available in Oracle applications: customer support, ecommerce, and business intelligence. In short, search has shifted from the “solution” to a component used to get started with an application that allows the user to find the answer to business questions.
I mention the Oracle story because it illustrates the consistent pattern of companies which are actually trying to deliver information that the u9ser of a search system needs to answer a business or technical question.
I don’t want to highlight the inaccuracies of “The Search Continues.” Instead I want to point out the problem buzzwords create when trying to understand why search has consistently been a problem and why today’s most promising solutions may relegate search to a permanent role of necessary evil.
In the write up, the notion of answering questions, analytics, federation (that is, running a single query across multiple collections of content and file types), the cloud, and system performance are the conclusion of the write up.
Wrong.
The use of open source search systems means that good enough is the foundation of many modern systems. Palantir-type outfits, essential an enterprise search vendors describing themselves as “intelligence” providing systems,, uses open source technology in order to reduce costs, shift bug chasing to a community, The good enough core is wrapped with subsystems that deal with the pesky problems of video, audio, data streams from sensors or similar sources. Attivio, formed by professionals who worked at the infamous Fast Search & Transfer company, delivers active intelligence but uses open source to handle the STAIRS-type functions. These companies have figured out that open source search is a good foundation. Available resources can be invested in visualizations, generating reports instead of results lists, and graphical interfaces which involve the user in performing tasks smart software at this time cannot perform.
For a low cost enterprise search system, one can download Lucene, Solr, SphinxSearch, or any one of a number of open source systems. There are low cost (keep in mind that costs of search can be tricky to nail down) appliances from vendors like Maxxcat and Thunderstone. One can make do with the craziness of the search included with Microsoft SharePoint.
For a serious application, enterprises have many choices. Some of these are highly specialized like BAE NetReveal and Palantir Metropolitan. Others are more generic like the Elastic offering. Some are free like the Effective File Search system.
The point is that enterprise search is not what users wanted in the 1970s when IBM pitched the mainframe centric STAIRS system, in the 1980s when Verity pitched its system, in the 1990s when Excalibur (later Convera) sold its system, in the 2000s when Fast Search shifted from Web search to enterprise search and put the company on the road to improper financial behavior, and in the efflorescence of search sell offs (Dassault bought Exalead, IBM bought iPhrase and other search vendors), and Lexmark bought Brainware and ISYS Search Software.
Where are we today?
Users still want on point information. The solutions on offer today are application and use case centric, not the silly one-size-fits-all approach of the period from 2001 to 2011 when Autonomy sold to HP.
Open source search has helped create an opportunity for vendors to deliver information access in interesting ways. There are cloud solutions. There are open source solutions. There are small company solutions. There are more ways to find information than at any other time in the history of search as I know it.
Unfortunately, the same problems remain. These are:
- As the volume of digital information goes up, so does the cost of indexing and accessing the sources in the corpus
- Multimedia remains a significant challenge for which there is no particularly good solution
- Federation of content requires considerable investment in data grooming and normalizing
- Multi-lingual corpuses require humans to deal with certain synonyms and entity names
- Graphical interfaces still are stupid and need more intelligence behind the icons and links
- Visualizations have to be “accurate” because a bad decision can have significant real world consequences
- Intelligent systems are creeping forward but crazy Watson-like marketing raises expectations and exacerbates the credibility of enterprise search’s capabilities.
I am okay with history. I am not okay with analyses that ignore some very real and painful lessons. I sure would like some of the experts today to know a bit more about the facts behind the implosions of Convera, Delphis, Entopia, and many other companies.
I also would like investors in search start ups to know a bit more about the risks associated with search and content processing.
In short, for a history of search, one needs more than 900 words mixing up what happened with what is.
Stephen E Arnold, March 9, 2016
Attivio: Dines on Data Dexterity
March 7, 2016
Attivio was founded by some former Fast Search & Transfer executives. Attivio also had a brush with a board member who found himself in a sticky wicket. Quite a pedigree.
I read “Enterprise Search Takes Its Place at the Big Data Table.” The write up is built upon an interview with the chief executive officer of Attivio. Nice looking fellow who had a degree in music and marketing and an MBA from Wharton, the institution which helped educate Donald Trump.
What caught my attention were these points in the write up. My observations are in italics:
- Enterprise search has been around for two decades. [Nah, enterprise search is closing in on 50 years of fun and delight.]
- Enterprise search “finds unstructured content housed in file shares like SharePoint and other content management systems, in email archives, and in the content repositories of applications like customer relationship management. [Yep, and that is part of the problem with enterprise search. The bulk of the systems I have examined do not handle video, audio, binaries, and odd ball file types like those in ANB format very well or not at all. Plus users expect comprehensive results updated in near real time presented in a form which allows instant use.]
- Enterprise search does analytics and accelerated data discovery. [Yep, if the customer licenses a system like BAE NetReveal, the Palantir platform, or another industrial-strength fusion vendor.]
What I found interesting was the phrase “reducing the time to insight.” There is a suggestion from Attivio and from other vendors that their systems process digital content in a super fast mode.
In our testing, we have found that throughput for new content can require considerable investment in engineering and processing capability. Furthermore, dealing with flows from intercepts or other high volume content sources, most enterprise search systems cannot handle:
- Processing large flows of content in a matter of minutes. Hours or days is a more suitable time unit
- Updating the index or indexes
- Integrating real time data into search results, reports, and visualizations in a dynamic manner.
That’s why outfits who are emulating Palantir-style information access use open source search and then invest hundreds of millions in specialized engineering, interfaces, and fusion technologies.
Enterprise search vendors chasing Palantir-type systems are delivering what marketers find quite easy to describe. Here’s an example:
Not only that, but many enterprises can only “see” 10 percent of their data. The other ninety percent remains hidden—dark data. Data is often locked in silos, and it’s just too time-consuming to get it out. And making connections across structured, semi-structured, and unstructured information to serve to a BI tool is a completely manual, slow process – although highly valuable for developing strategic insights. Organizations that can cross this chasm will be poised to transform productivity, mitigate risks, and seize market opportunities.
The only hitch in the git along is that systems which handle “dark data” are available now. There are outfits able to handle “dark” data today. True, these are not based on enterprise search concepts because the core of a utility function is not a solid foundation for next generation information access. There are platforms which deliver actionable outputs. Even more interesting is that the US government is funding research to develop next generation systems designed to leap frog Palantir, i2, DCGS-A, and many other solutions.
Why?
Marketing is one thing. Delivering a system which works reliably, exhibits consistency, and integrates with work flows is a work in progress.
The notion that a Fast-type system can deliver what a Palantir-type system does is something I believe is wordsmithing. Watson does wordsmithing; others deliver next generation information access. Has Attivio hit a home run with its new positioning? Is the Attivio solution a starter for the Hickory Crawdads? My hunch the folks investing $70 million in Attivio want to start for the Boston Red Sox this year. Play ball.
Stephen E Arnold, March 7, 2016
Venture Backed Search Vendors Face Exciting 2016
February 12, 2016
I read “The State of Venture Capital.” I thought, “Oh, ho, here comes the tightening of the thumbscrews. The idea is simple. Insert fingers and turn the crank. My hunch is that the device will focus the attention of person whose fingers are in the business end of the gizmo.
In the write up, I learned that in the next two years, folks should expect:
- Increased loss ratios
- Most flat rounds
- More down rounds
- More structured rounds
- Relatively harder to raise capital
- VCs marking-to-market showing some movements south
I like the reference to the movement south.
How does this relate to the search and content processing outfits which have sucked in tens of millions in venture funding? Three items for which I will be watching:
- More market repositioning. Think predictive analytics, data lakes, cloud solutions, and artificial intelligence. Talk is cheap. If talk generates a license deal, that’s the upside.
- Downsizing. I know that growth is all the rage, but I think that some vendors will have no choice except cutting back on expenses. Full time hires become contract workers. Trade show participation becomes a webinar which is archived and the promoted as a resource.
- Dance card shuffling. In an effort to generate leads and from the leads some real license deals, companies will join up. Others will departner and find another entity with which to dance.
Which search vendors will survive? The last big shake out winnowed the likes of Convera, Delphes, Entopia, and Siderean. The acquisition boomlet moved Autonomy, Exalead, ISYS Search, and Vivisimo into the safe havens of larger organization. Who will buy today’s market leaders? Other vendors will have no choice but go quiet. The last time I checked Dieselpoint it was still in business. Sophia Search? Intrafind? X1?
Which company is the next Autonomy? Elastic, Recommind, IBM Watson?
My view is that 2016 will be exciting for some folks.
Stephen E Arnold, February 12, 2016
Google Search Appliance: Like Glass It Broke
February 8, 2016
I read “So Long Google Search Appliance.” Farewell, happy yellow and blue boxes. So long integrators who have been supporting these wildebeests for a decade. Au revoir easy-as-pie search.
According to the write up:
The tech giant told its reseller and consulting partners the news via email on Thursday, noting that they can continue to sell one-year license renewals for existing hardware customers through 2017, but that they will be unable to sell new hardware. Renewals will end in 2018.
I recall writing about the Google Search Appliance when I was reporting about enterprise search for specialist publications. I was the first or one of the first to run down the pricing for the wonky boxes. I pointed out that a redundant multi million document system would ring the Google cash register in the high six figures with seven figures not out of sight. I thought I mentioned that the number of engineeers supporting the GSA had dwindled to a couple of folks. I thought I pointed out that the assumption a Web search system would work like a champ on corporate content was a wild and crazy notion.l
Like so many others who assumed enterprise search was not a tough problem, the Alphabet Google thing has bailed. Google essentially failed to revolutionize enterprise search. Cheaper and more usable appliances are available, including products from Maxxcat and Thunderstone. There are reasonable cloud solutions. And there is a cornucopia of outfits offering repackaged open source systems. Heck, if one pokes around long enough, a bold enterprise can license a system from companies with proprietary information access systems; 3RDi, Fabasoft, Lexmark, etc.
What will organizations do without the Google Search Appliance? Yard sale, Goodwill?
Stephen E Arnold, February 8, 2016
3RDi for Enterprise Search
February 5, 2016
Health and medical search need an upgrade? T/DG 3RDi might be just what the doctor ordered. You search blues will disappear when you have natural language processing, semantic search, search relevancy, search analytics, research tools, and data integration. Very comprehensive it seems.
T/DG offers 3RDi. Now try to search for these entities. To locate the services firm offering the 3RDi system, one has to figure out how to make Bing, Google, and Yandex point to the correct entities.
Naming products and companies is tricky. Let me save you the hassle of wading through false drops.
- T/DG means “The Digital Group,” an outfit founded in 1999 and operating from New Jersey.
- 3RDi means “relevant, deep insights.” (I don’t know what the 3 means.)
The search system appears to be a “platform” based on open source technology. Here’s a block diagram of 3RDi:
Source: The Digital Group, 2015
The company’s most recent push is health care. The search system performs the type of functions which I associate with a system like the ones Autonomy and Fast Search & Transfer described in the late 1990s. There is also a hefty dose of “platformitis.” The idea is that a licensee can use the system to meet the needs of users. The support for controlled vocabularies is helpful in domain specific deployments, but these have to be maintained, which can be a financial and resource burden for some licensees.
3RDi embraces the semantic marketing jargon enthusiastically; for example, this diagram shows how “knowledge” and “semantics” make the “experience” work for licensees:
Source: The Digital Group, 2015
Users of the system do not have to deal with results lists. The system presents information in a visual manner; for example:
Source: The Digital Group, 2015
In short, 3RDi appears to deliver the type of utility I associate with systems from outfits like BAE Systems and Palantir.
If your organization wants an open source system with the bells and whistles found in seven figure platforms, you may want to explore 3RDi.
The urls you need are:
I assume that the company will make the “3” clearer going forward. There is a live demo available. You will need to register. The system balks at non commercial domains like my Yahoo account.
The recent marketing push given 3RDi signals that the enterprise search sector is alive and well. As the company says, “Start experiencing.” I wonder what the “3” means.
Stephen E Arnold, February 5, 2016
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