FeaturedEnterprise Search: Essentially Marginalized to Good Enough
I use Google Trends to see what’s hot and what’s not in the world of information retrieval. If you want to use the free version of Google Trends, navigate to http://www.google.com/trends/ and explore. That’s some of what Google does to make decisions about how much of Larry Page’s “wood” to put behind the Google Search Appliance eight ball.
I plugged in “enterprise search.” When one allows Google to output its version of the popularity of the term, you get this graph. It shows a downward trend but the graph is without much context. The pale lettering does not help. Obviously Googlers do not view the world through trifocals with 70 year old eyes. Here’s the Trends’ output for “enterprise search”:
Now let’s add some context. From the “enterprise search” Trends’ output, click the pale blue plus and add this with quotes: “big data.” Here’s the output for this two factor analysis:
One does not have to be an Ivy League data scientist to see the difference between the hackneyed “enterprise search” and more zippy but meaningless “Big Data.” I am not saying Big Data solutions actually work. What’s clear is that pushing enterprise search is not particularly helpful when the Trends’ reveal a flat line for years, not hours, not days, not months–years.
I think it is pretty clear why I can assert with confidence that “enterprise search” appears to be a non starter. I know why search vendors persist in telling me what “enterprise search” is. The vendors are desperate to find the grip that a Tupinambis lizard possesses. Instead of clinging to a wall in the sun at 317 R. Dr. Emílio Ribas (Cambui) (where I used to live in Campinas, SP), the search vendors are clinging to chimera. The goal is to make sales, but if the Google data are even sort of correct, enterprise search is flat lining.
Little wonder that consultant reports like those from the mid tier crowd try to come up with verbiage that will create sales leads for the research sponsors; case in point, knowledge quotient. See Meme of the Moment for a fun look at IDC’s and search “expert” Dave Schubmehl’s most recent attempt to pump up the music.
The question is, “What is generating revenue?” In a sense, excitement surrounds vendors who deliver solutions. These include search, increasingly supplied by open source software. Elasticsearch is zipping along, but search is not the main dish. Search is more like broccoli or carrots.
The good news is that there is a group of companies, numbering about 30, which have approached search differently. As a result, many of these companies are growing and charting what I call “next generation search.”
Want to know more? Well, that’s good. Watch for my coverage of this sector in the weeks and months ahead. I will toss a small part of our research into my November Information Today column. A tiny chunk. Keep that in mind.
In the meantime, think critically about the craziness flowing from many mid tier or azure chip consulting firms. Those “outputs” are marketing, self aggrandizing, and, for me, downright silly. What’s that term for doing trivial actions again and again?
Stephen E Arnold, November 9, 2014
InterviewsElasticsearch: A Platform for Third Party Revenue
Making money from search and content processing is difficult. One company has made a breakthrough. You can learn how Mark Brandon, one of the founders of QBox, is using the darling of the open source search world to craft a robust findability business.
I interviewed Mr. Brandon, a graduate of the University of Texas as Austin, shortly after my return from a short trip to Europe. Compared with the state of European search businesses, Elasticsearch and QBox are on to what diamond miners call a “pipe.”
In the interview, which is part of the Search Wizards Speak series, Mr. Brandon said:
We offer solutions that work and deliver the benefits of open source technology in a cost-effective way. Customers are looking for search solutions that actually work.
Simple enough, but I have ample evidence that dozens and dozens of search and content processing vendors are unable to generate sufficient revenue to stay in business. Many well known firms would go belly up without continual infusions of cash from addled folks with little knowledge of search’s history and a severe case of spreadsheet fever.
Qbox’s approach pivots on Elasticsearch. Mr. Brandon said:
When our previous search product proved to be too cumbersome, we looked for an alternative to our initial system. We tested Elasticsearch and built a cluster of Elasticsearch servers. We could tell immediately that the Elasticsearch system was fast, stable, and customizable. But we love the technology because of its built-in distributed nature, and we felt like there was room for a hosted provider, just as Cloudant is for CouchDB, Mongolab and MongoHQ are for MongoDB, Redis Labs is for Redis, and so on. Qbox is a strong advocate for Elasticsearch because we can tailor the system to customer requirements, confident the system makes information more findable for users.
When I asked where Mr. Brandon’s vision for functional findablity came from, he told me about an experience he had at Oracle. Oracle owns numerous search systems, ranging from the late 1980s Artificial Linguistics’ system to somewhat newer systems like the late 1990s Endeca system, and the newer technologies from Triple Hop. Combine these with the SES technology and the hybrid InQuira formed from two faltering NLP systems, and Oracle has some hefty investments.
Here’s Mr. Brandon’s moment of insight:
During my first week at Oracle, I asked one of my colleagues if they could share with me the names of the middleware buyer contacts at my 50 or so named accounts. One colleague said, “certainly”, and moments later an Excel spreadsheet popped into my inbox. I was stunned. I asked him if he was aware that “Excel is a Microsoft technology and we are Oracle.” He said, “Yes, of course.” I responded, “Why don’t you just share it with me in the CRM System?” (the CRM was, of course, Siebel, an Oracle product). He chortled and said, “Nobody uses the CRM here.” My head exploded. I gathered my wits to reply back, “Let me get this straight. We make the CRM software and we sell it to others. Are you telling me we don’t use it in-house?” He shot back, “It’s slow and unusable, so nobody uses it.” As it turned out, with around 10 million corporate clients and about 50 million individual names, if I had to filter for “just middleware buyers”, “just at my accounts”, “in the Northeast”, I could literally go get a cup of coffee and come back before the query was finished. If I added a fourth facet, forget it. The CRM system would crash. If it is that bad at the one of the world’s biggest software companies, how bad is it throughout the enterprise?
Stephen E Arnold, July 2, 2014
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