Natural Language Processing: Tomorrow and Yesterday
October 31, 2017
I read “Will Natural Language Processing Change Search as We Know It?” The write up is by a search specialist who, I believe, worked at Convera. The Search Technologies’ Web site asserts:
He was the architect and inventor of RetrievalWare, a ground-breaking natural-language based statistical text search engine which he started in 1989 and grew to $50 million in annual sales worldwide. RetrievalWare is now owned by Microsoft Corporation.
I think Fast Search acquired a portion of Convera. When Microsoft purchased Fast Search, the Convera technology was part of the deal. When Convera faded, one rumor I captured in 2007 was that some of the Convera technology was used by Ntent, formed as the result of a merger between Convera Corporation and Firstlight ERA. If accurate, the history of Convera is fascinating with Excalibur, ConQuest, and Allen & Co. in the mix.
In the “Will Natural Language Processing Change Search As We Know It” blog post, I noted these points:
- Intranets incorporating NLP, semantic search and AI can fuel chatbots as well as end-to-end question-answering systems that live on top of search. It is a truly semantic extension to the search box with far-reaching implications for all types of search.
- With NLP, enterprise knowledge contained in paper documentation can be encoded in a machine-readable format so the machine can read, process and understand it enough to formulate an intelligent response.
- it’s good to know about established tool sets and methodologies for developing and creating effective solutions for use cases like technical support. But like all development projects, take care to create the tools based on mimicking the responses of actual human domain experts. Otherwise, you may run into the proverbial development problem of “garbage in, garbage out” which has plagued many such expert system initiatives.
Mr. Nelson is painting a reasonable picture about the narrow use of widely touted technologies. In fact, the promise of NLP has been part of enterprise search marketing for decades.
What I found interesting was the Convera document called “Accurate Search: What a Concept, published by Convera in 2002. I noted this passage on page 4 of the document:
Concept Search capitalizes on the richness of language, with its multiple term meanings, and transforms it from a problem into an advantage. RetrievalWare performs natural language processing and search term expansion to paraphrase queries, enabling retrieval of documents that contain the specific concepts requested rather than just the words typed during the query while also taking advantage of its semantic richness to rank documents in results lists. RetrievalWare’s powerful pattern search abilities overcome common errors in both content and queries, resulting in greater recall and user satisfaction.
I find the shift from a broad solution to a more narrow solution interesting. In the span of 15 years, the technology of search seems to be struggling to deliver.
Perhaps consulting and engineering services are needed to make search “work”? Contrast search with mobile phone technology. Progress has been evident. For search, success narrows to improving “documentation” and “customer support.”
Has anyone tried to reach PayPal’s customer support or United Airlines’ customer support? Try it. United was at one time a “customer” of Convera’s. From my point of view, United Airlines’ customer service has remained about the same over the last decade or two.
Enterprise search, broad or narrow, remains a challenge for marketers and users in my opinion. NLP, I assume, has arrived after a long journey. For a free profile of Convera, check out this link.
Stephen E Arnold, October 31, 2017
Google: What For-Fee Thought Leader Love? And for Money? Yep
July 13, 2017
Talk about disinformation. Alphabet Google finds itself in the spotlight for normal consulting service purchases. How many of those nifty Harvard Business Review articles, essays in Strategy & Business (the money loser published by the former Booz, Allen & Hamilton), or white papers generated by experts like me are labors of thought leader love.
Why not ask a person like me, an individual who has written a white paper for an interesting company in Spain? You won’t. Well, let me interview myself:
Question: Why did you write the white paper about multi-language text analysis?
Answer: I did a consulting job and was asked to provide a report about the who, what, why, etc. of the company’s technology.
Question: Is the white paper objective and factual?
Answer: Yes, I used information from my book research, a piece of published material from the “old” Autonomy Software, and the information gathered at the company’s headquarters in Madrid by one of my colleagues from the engineers. I had a couple of other researchers chase down information about the company, its products, customers, and founder. I then worked through the information about text analysis in my archive. I think I did a good job of presenting the technology and why it is important.
Question: Were you paid?
Answer: Yes, I retired in 2013, and I don’t write for third parties unless those third parties pony up cash.
Question: Do you flatter the company or distort the company’s technology, its applications, or its benefits?
Answer: I try to work through the explanation in order to inform. I offer my opinion at the end of the write up. In this particular case, the technology is pretty good. I state that.
Question: Would another expert agree with you?
Answer: Some would and some would not. When figuring out with a complex multi-lingual platform when processing text in 50 languages, there is room for differences of opinion with regard to such factors as [a] text through put on a particular application, [b] corpus collection and preparation, [c] system tuning for a particular application such as a chatbot, and other factors.
Question: Have you written similar papers for money over the years?
Answer: Yes, I started doing this type of writing in 1972 when I left the PhD program at the University of Illinois to join Halliburton Nuclear in Washington, DC.
Question: Do people know you write white papers or thought leader articles for money?
Answer: Anyone who knows me is aware of my policy of charging money for knowledge work. I worked at Booz, Allen & Hamilton and a number of other equally prestigious firms. To my knowledge, I have never been confused with Mother Teresa.
| Mother Theresa | A Person Who Works for Money |
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I offer this information as my reaction to the Wall Street Journal’s write up “Google Pays Scholars to Influence Policy.” You will have to pay to read the original article because Mr. Murdoch is not into free information.The original appeared in my dead tree edition of the WSJ on July 12, 2017 on the first page with a jump to a beefy travelogue of Google’s pay-for-praise and pay-for-influence activities. A correction to the original story appears on Fox News. Gasp. Find that item here.
Google, it seems, is now finding itself in the spotlight for search results, presenting products to consumers, and its public relations/lobbying activities.
My view is that Google does not deserve this type of criticism. I would prefer that real journalists tackle such subjects as [a] the Loon balloon patent issue, [2] Google’s somewhat desperate attempts to discover the next inspiration like Yahoo’s online advertising approach, and [3] solving death’s progress.
Getting excited about white papers which have limited impact probably makes a real journalist experience a thrill. For me, the article triggers a “What’s new?”
But I am not Mother Teresa, who would have written for Google for nothing. Nah, not a chance.
Stephen E Arnold, July 14, 2017
Booz Boo Boo: Blue Chip? Maybe Not
June 1, 2017
I read “Booz Allen, NGA Probe Intel Leak.” Let’s assume that the information in the write up is “sort of” accurate. I suggest this because the article invokes the name of “Edward Snowden” and the name of “Hal Martin.” Both of these individuals allegedly behaved with a bit of professional “looseness.”
But the write up does more than remind me that the once highly regarded blue chip management consulting firm has become an example of how not to manage its own employees and contractors.
Too bad. I worked at Booz, Allen & Hamilton when the firm’s reputation was reasonably well regarded. Today I am not so sure I would place the Booz Allen outfit identified in the FCW article in my “I want to work their” Top 10.
The main point of the write up seems to me to be:
Edward Snowden, Hal Martin and now another Booz Allen Hamilton employee could be involved in the leak of sensitive intelligence data — though in the latest case, it appears it could be accidental.
The information, according the FCW, was sensitive. The error was a result of a misconfiguration error.
Nevertheless, a company charged with working within the constraints set forth by the client should have management procedures in place to prevent alleged security issues.
Booz, Allen & Hamilton once kept a low profile. Now the firm finds itself making headlines.
FCW is not the grocery store tabloid-type of “real news” outfit, of course. However, I ask myself, “Management or mismanagement?”
And from an outfit which once provided management consulting services to the world’s leading organizations.
Interesting.
Stephen E Arnold, June 1, 2017
Forrester: Enterprise Content Management Misstep
April 14, 2017
I have stated in the past that mid tier consulting firms—that is, outfits without the intellectual horsepower of a McKinsey, Bain, or BCG—generate work that is often amusing, sometimes silly, and once in a while just stupid. I noted an error which is certainly embarrassing to someone, maybe even a top notch expert at mid tier Forrester. The idea for a consulting firm is to be “right” and to keep the customer (in this case Hyland) happy. Also, it is generally good to deliver on what one promises. You know, the old under promise, over deliver method.
How about being wrong, failing, and not delivering at all? Read on about Forrester and content management.
Context
I noted the flurry of news announcements about Forrester, a bigly azure-chip consulting firm. A representative example of these marketing news things is “Microsoft, OpenText, IBM Lead Forrester’s ECM Wave in Evolving Market.” The write up explains that the wizards at Forrester have figured out the winners and losers in enterprise content management. As it turns out, the experts at Forrester do a much better job of explaining their “perception” of content management that implementing content management.
How can this be? Paid experts who cannot implement content management for reports about content management? Some less generous people might find this a minor glitch. I think that consultants are pretty good at cooking up reports and selling them. I am not too confident that mid tier consulting firms and even outfits like Booz, Allen has dotted their “i’s” and crossed their “t’s.”
Let me walk you through this apparent failure of Forrester to make their reports available to a person interested in a report. This example concerns a Forrester reviewed company called Hyland and its OnBase enterprise content management system.
The deal is that Hyland allows a prospect to download a copy of the Forrester report in exchange for providing contact information. Once the contact information is accepted, the potential buyer of OnBase is supposed to be able to download a copy of the Forrester report. This is trivial stuff, and we are able to implement the function when I sell my studies. Believe me. If we can allow registered people to download a PDF, so can you.
The Failure
I wanted a copy of “The Forrester Wave: ECM Business Content Services.” May I illustrate how Forrester’s enterprise content management system fails its paying customers and those who register to download these high value, completely wonderful documents.
Step 1: Navigate to this link for OnBase by Hyland, one of the vendors profiled in the allegedly accurate, totally object Forrester report
Step 2: Fill out the form so Hyland’s sales professionals can contact you in hopes of selling you the product which Forrester finds exceptional
Note the big orange “Download Now” button. I like the “now” part because it means that with one click I get the high-value, super accurate report.
Step 3: Click on one of these two big green boxes:
I tested both, and both return the same high value, super accurate, technically wonderful reports—sort of.
You Do Not Search. You Insight.
April 12, 2017
I am delighted, thrilled. I read “Coveo, Microsoft, Sinequa Lead Insight Engine Market.” What a transformation is captured in what looks to me like a content marketing write up. Key word search morphs into “insight.” For folks who do not follow the history of enterprise search with the fanaticism of those involved in baseball statistics, the use of the word “insight” to describe locating a document is irrelevant. Do you search or insight?
For me, hunkered down in rural Kentucky, with my monitors flickering in the intellectual darkness of Kentucky, the use of the word “insight” is a linguistic singularity. Maybe not on the scale of an earthquake in Italy or a banker leaping from his apartment to the Manhattan asphalt, but a historical moment nevertheless.
Let me recap some of my perceptions of the three companies mentioned in the headline to this tsunami of jargon in the Datanami story:
- Coveo is a company which developed a search and retrieval system focused on Windows. With some marketing magic, the company explained keyword search as customer support, then Big data, and now this new thing, “insight”. For those who track vendor history, the roots of Coveo reach back to a consumer interface which was designed to make search easy. Remember Copernic. Yep, Coveo has been around a long while.
- Sinequa also was a search vendor. Like Exalead and Polyspot and other French search vendors, the company wanted manage data, provide federation, and enable workflows. After a president change and some executive shuffling, Sinequa emerged as a Big Data outfit with a core competency in analytics. Quite a change. How similar is Sinequa to enterprise search? Pretty similar.
- Microsoft. I enjoyed the “saved by the bell” deal in 2008 which delivered the “work in progress” Fast Search & Transfer enterprise search system to Redmond. Fast Search was one of the first search vendors to combine fast-flying jargon with a bit of sales magic. Despite the financial meltdown and an investigation of the Fast Search financials, Microsoft ponied up $1.2 billion and reinvented SharePoint search. Well, not exactly reinvented, but SharePoint is a giant hairball of content management, collaboration, business “intelligence” and, of course, search. Here’s a user friendly chart to help you grasp SharePoint search.
Flash forward to this Datanami article and what do I learn? Here’s a paragraph I noted with a smiley face and an exclamation point:
Among the areas where natural language processing is making inroads is so-called “insight engines” that are projected to account for half of analytic queries by 2019. Indeed, enterprise search is being supplanted by voice and automated voice commands, according to Gartner Inc. The market analyst released it latest “Magic Quadrant” rankings in late March that include a trio of “market leaders” along with a growing list of challengers that includes established vendors moving into the nascent market along with a batch of dedicated startups.
There you go. A trio like ZZTop with number one hits? Hardly. A consulting firm’s “magic” plucks these three companies from a chicken farm and gives each a blue ribbon. Even though we have chickens in our backyard, I cannot tell one from another. Subjectivity, not objectivity, applies to picking good chickens, and it seems to be what New York consulting firms do too.
Are the “scores” for the objective evaluations based on company revenue? No.
Return on investment? No.
Patents? No.
IRR? No. No. No.
Number of flagship customers like Amazon, Apple, and Google type companies? No.
The ranking is based on “vision.” And another key factor is “the ability to execute its “strategy.” There you go. A vision is what I want to help me make my way through Kabul. I need a strategy beyond stay alive.
What would I do if I have to index content in an enterprise? My answer may surprise you. I would take out my check book and license these systems.
- Palantir Technologies or Centrifuge Systems
- Bitext’s Deep Linguistic Analysis platform
- Recorded Future.
With these three systems I would have:
- The ability to locate an entity, concept, event, or document
- The capability to process content in more than 40 languages, perform subject verb object parsing and entity extraction in near real time
- Point-and-click predictive analytics
- Point-and-click visualization for financial, business, and military warfighting actions
- Numerous programming hooks for integrating other nifty things that I need to achieve an objective such as IBM’s Cybertap capability.
Why is there a logical and factual disconnect between what I would do to deliver real world, high value outputs to my employees and what the New York-Datanami folks recommend?
Well, “disconnect” may not be the right word. Have some search vendors and third party experts embraced the concept of “fake news” or embraced the know how explained in Propaganda, Father Ellul’s important book? Is the idea something along the lines of “we just say anything and people will believe our software will work this way”?
Many vendors stick reasonably close to the factual performance of their software and systems. Let me highlight three examples.
First, Darktrace, a company crafted by Dr. Michael Lynch, is a stickler for explaining what the smart software does. In a recent exchange with Darktrace, I learned that Darktrace’s senior staff bristle when a descriptive write up strays from the actual, verified technical functions of the software system. Anyone who has worked with Dr. Lynch and his senior managers knows that these people can be very persuasive. But when it comes to Darktrace, it is “facts R us”, thank you.
Second, Recorded Future takes a similar hard stand when explaining what the Recorded Future system can and cannot do. Anyone who suggests that Recorded Future predictive analytics can identify the winner of the Kentucky Derby a day before the race will be disabused of that notion by Recorded Future’s engineers. Accuracy is the name of the game at Recorded Future, but accuracy relates to the use of numerical recipes to identify likely events and assign a probability to some events. Even though the company deals with statistical probabilities, adding marketing spice to the predictive system’s capabilities is a no-go zone.
Third, Bitext, the company that offers a Deep Linguistics Analysis platform to improve the performance of a range of artificial intelligence functions, is anchored in facts. On a recent trip to Spain, we interviewed a number of the senior developers at this company and learned that Bitext software works. Furthermore, the professionals are enthusiastic about working for this linguistics-centric outfit because it avoid marketing hyperbole. “Our system works,” said one computational linguist. This person added, “We do magic with computational linguistics and deep linguistic analysis.” I like that—magic. Oh, Bitext does sales too with the likes of Porsche, Volkswagen, and the world’s leading vendor of mobile systems and services, among others. And from Madrid, Spain, no less. And without marketing hyperbole.
Why then are companies based on keyword indexing with a sprinkle of semantics and basic math repositioning themselves by chasing each new spun sugar-encrusted trend?
I have given a tiny bit of thought to this question.
In my monograph “The New Landscape of Search” I made the point that search had become devalued, a free download in open source repositories, and a utility like cat or dir. Most enterprise search systems have failed to deliver results painted in Technicolor in sales presentations and marketing collateral.
Today, if I want search and retrieval, I just use Lucene. In fact, Lucene is more than good enough; it is comparable to most proprietary enterprise search systems. If I need support, I can ring up Elastic or one of many vendors eager to gild the open source lily.
The extreme value and reliability of open source search and retrieval software has, in my opinion, gutted the market for proprietary search and retrieval software. The financial follies of Fast Search & Transfer reminded some investors of the costly failures of Convera, Delphes, Entopia, among others I documented on my Xenky.com site at this link.
Recently most of the news I see on my coal fired computer in Harrod’s Creek about enterprise search has been about repositioning, not innovation. What’s up?
The answer seems to be that the myth cherished by was that enterprise search was the one, true way make sense of digital information. What many organizations learned was that good enough search does the basic blocking and tackling of finding a document but precious little else without massive infusions of time, effort, and resources.
But do enterprise search systems–no matter how many sparkly buzzwords–work? Not too many, no matter what publicly traded consulting firms tell me to believe.
Snake oil? I don’t know. I just know my own experience, and after 45 years of trying to make digital information findable, I avoid fast talkers with covered wagons adorned with slogans.
What happens when an enterprise search system is fed videos, podcasts, telephone intercepts, flows of GPS data, and a couple of proprietary file formats?
Answer: Not much.
The search system has to be equipped with extra cost connectors, assorted oddments, and shimware to deal with a recorded webinar and a companion deck of PowerPoint slides used by the corporate speaker.
What happens when the content stream includes email and documents in six, 12, or 24 different languages?
Answer: Mad scrambling until the proud licensee of an enterprise search system can locate a vendor able to support multiple language inputs. The real life needs of an enterprise are often different from what the proprietary enterprise search system can deal with.
That’s why I find the repositioning of enterprise search technology a bit like a clown with a sad face. The clown is no longer funny. The unconvincing efforts to become something else clash with the sad face, the red nose, and worn shoes still popular in Harrod’s Creek, Kentucky.
When it comes to enterprise search, my litmus test is simple: If a system is keyword centric, it isn’t going to work for some of the real world applications I have encountered.
Oh, and don’t believe me, please.
Find a US special operations professional who relies on Palantir Gotham or IBM Analyst’s Notebook to determine a route through a hostile area. Ask whether a keyword search system or Palantir is more useful. Listen carefully to the answer.
No matter what keyword enthusiasts and quasi-slick New York consultants assert, enterprise search systems are not well suited for a great many real world applications. Heck, enterprise search often has trouble displaying documents which match the user’s query.
And why? Sluggish index updating, lousy indexing, wonky metadata, flawed set up, updates that kill a system, or interfaces that baffle users.
Personally I love to browse results lists. I like old fashioned high school type research too. I like to open documents and Easter egg hunt my way to a document that answers my question. But I am in the minority. Most users expect their finding systems to work without the query-read-click-scan-read-scan-read-scan Sisyphus-emulating slog.
Ah, you are thinking I have offered no court admissible evidence to support my argument, right? Well, just license a proprietary enterprise search system and let me know how your career is progressing. Remember when you look for a new job. You won’t search; you will insight.
Stephen E Arnold, April 12, 2017
The Uncertainty for Beltway Bandits: Billions at Stake
January 17, 2017
I don’t find CNBC a source of useful information. I did notice a write up with a title which caught my attention; specifically “Trump’s Rift with Intelligence Community Is Spooking US Spy Agency Contractors.” The business of some intelligence agencies boils down to information access, search, and content processing. With digital content readily available, the Beltway Bandits (contractors, consulting outfits, and body shops which provide “services” to the US government have been, are, and should be in hog heaven. Successful Beltway Bandits wallow in money, not mud, I wish to point out.
The CNBC story asserts:
The changing political landscape in Washington and friction between President-elect Donald Trump and the U.S. intelligence community could have major implications not only for the spy agencies but for the shadow private contractors such as Booz Allen Hamilton that support them.
Yikes. The Boozer!
The idea is that
Booz Allen, which gets 97 percent of it revenue from U.S. government agencies, provides everything from cyber and IT services to work designed to enhance the nation’s intelligence capabilities.
CNBC notes:
Overall, the U.S. budget for the national intelligence program was $53 billion in fiscal 2016 and another $17.7 billion for the military intelligence program.
My view from rural Kentucky is that the “total” is probably different from what CNBC reports. One example: What about the budget for projects for the White House, what about entities with one innocuous name which perform “interesting” work. Are these figures tallied?
CNBC notes that despite the uncertainty which accompanies any new president taking office, spending for information and intelligence is likely to go up.
My thought is that Booz, Allen and similar firms are going to chug along. Information access is a tough problem. Who is the president and his appointees going to rely upon? A Yandex query? Experts in Cairo, Illinois? Nope. The Beltway crowd, a tradition for decades.
Stephen E Arnold, January 17, 2017
Gartner Wants to Change Its Tint: From Azure to Blue
January 7, 2017
Is it possible for a mid tier consulting firm to change into a blue chip firm with a splurge of money, stock, and PR?
The idea is that there is a hierarchy of consulting firms. At the top are outfits like McKinsey, Bain, BCG, SRI, and a handful of others are blue chip outfits. These outfits deliver the blue ribbon winning bacon to their clients. Then at the bottom of the hierarchy are the drab gray chips held by former middle school teachers and unemployed journalists who embrace freelance consulting. You can find some of these folks at search engine optimization conferences or via gig Web sites. In the middle are consulting firms which are generating revenue and have some clients. These outfits either try to move up to the blue chip sector and compete head to head with the blue chip folks. or they are drifting down to Fiverr.com territory where “services” begin at $5 per job. In the middle are the azure chip outfits. Many of these firms purveying expertise embrace LinkedIn and do their best to become the talk of the town. The talking heads on many TV news programs come from the azure chip brigade.
Why are the color thing and the consulting hierarchy relevant?
Gartner Group, if the information in “IT Research Firm Gartner Is Buying CEB for $2.6 Billion” is on the money, is making a beeline to the paint store. From azure to blue chip with a bit of cash and Moxie.
The write up points out that Gartner is paying $2.6 billion for a services firm. I learned:
Gartner is offering $54 in cash and 0.2284 of its shares for each CEB share. The deal represents a premium of about 25 percent to CEB’s Wednesday close. CEB’s shares were up 16.4 percent at $72.05 in premarket trading, below the implied offer price of $77.25 per share. Gartner’s shares, which closed at $101.79 on Wednesday, were untraded.
Well, that’s a bit underwhelming for shareholders. “Untraded.” Hmmm.
The Washington Post reported that one CEB executive was “excited” by the deal. The CEB top dog is heading for the kennel. The Post noted:
CEB has grown more slowly than Gartner recently, making some investors worry whether the combined company can maintain the double-digit revenue growth rates Gartner has boasted in recent years.
What happens if more of the CEB professionals check out?
Will the respray deliver the growth and revenue Gartner desires? I have no crystal ball, but if there are some show dogs at CEB, why not see if the McKinsey- or Booz Allen-type outfits are hiring. More money and maybe more prestige?
The big question for me is the new blue chip paint going to hold up in the tough business climate?
Stephen E Arnold, January 7, 2017
Study of Search: Weird Results Plus Bonus Errors
December 30, 2016
I was able to snag a copy of “Indexing and Search: A Peek into What Real Users Think.” The study appeared in October 2016, and it appears to be the work of IT Central Station, which is an outfit described as a source of “unbiased reviews from the tech community.” I thought, “Oh, oh, “real users.” A survey. An IDC type or Gartner type sample which although suspicious to me seems to convey some useful information when the moon is huge. Nope. Nope.Unbiased. Nope.
Note that the report is free. One can argue that free does not translate to accurate, high value, somewhat useful information. I support this argument.
The report, like many of the “real” reports I have reviewed over the decades is relatively harmless. In terms of today’s content payloads, the study fires blanks. Let’s take a look at some of the results, and you can work through the 16 pages to double check my critique.
First, who are the “top” vendors? This list reads quite a bit about the basic flaw in the “peek.” The table below presents the list of “top” vendors along with my comment about each vendor. Companies with open source Lucene/Solr based systems are in dark red. Companies or brands which have retired from the playing field in professional search are in bold gray.
| Vendor | Comment |
| Apache | This is not a search system. It is an open source umbrella for projects of which Lucene and Solr are two projects among many. |
| Attivio | Based on Lucene/Solr open source search software; positioned as a business intelligence vendor |
| Copernic | A desktop search and research system based on proprietary technology from the outfit known as Coveo |
| Coveo | A vendor of proprietary search technology now chasing Big Data and customer support |
| Dassault Systèmes | Owns Exalead which is now downgraded to a utility with Dassault’s PLM software |
| Data Design, now Ryft.com | Pitches search without indexing via propriety “circuit module” method |
| Data Gravity | Search is a utility in a storage centric system |
| DieselPoint | Company has been “quiet” for a number of years |
| Expert System | Publicly traded and revenue challenged vendor of a metadata utility, not a search system |
| Fabasoft | Mindbreeze is a proprietary replacement for SharePoint search |
| Discontinued the Google Search Appliance and exited enterprise search | |
| Hewlett Packard Enterprise | Sold its search technology to Micro Focus; legal dispute in progress over alleged fraud |
| IBM Ominifind | Lucene and proprietary scripts plus acquired technology |
| IBM StoredIQ | Like DB2 search, a proprietary utility |
| ISYS Search Software | Now owned by Lexmark and marginalized due to alleged revenue shortfalls |
| Lookeen | Lucene based desktop and Outlook search |
| Lucidworks | Solr add ons with floundering to be more than enterprise search |
| MAANA | Proprietary search optimized for Big Data |
| Microsoft | Offers multiple search solutions. The most notorious are Bing and Fast Search & Transfer proprietary solutions |
| Oracle | Full text search is a utility for Oracle licenses; owns Artificial Linguistics, Triple Hop, Endeca, RightNow, InQuira, and the marginalized Secure Enterprise Search. Oh, don’t forget command line querying via PL/SQL |
| Polyspot, now CustomerMatrix | Now a customer service vendor |
| Siderean Software | Went out of business in 2008; a semantic search outfit |
| Sinequa | Now a Big Data outfit with hopes of becoming the “next big thing” in whatever sells |
| X1 Search | An eternal start up pitching eDiscovery and desktop search with a wild and crazy interface |
What’s the table tell us about “top” systems? First, the list includes vendors not directly in the search and retrieval business. There is no differentiation among the vendors repackaging and reselling open source Lucene/Solr solutions. The listing is a fruit cake of desktop, database, and unstructured search systems. In short, the word “top” does not do the trick for me. I prefer “a list of eclectic and mostly unknown systems which include a search function.”
The report presents 10 bar charts which tell me absolutely nothing about search and retrieval. The bars appear to be a popularity content based on visits to the author’s Web site. Only two of the search systems listed in the bar chart have “reviews.” Autonomy IDOL garnered three reviews and Lookeen one review. The other eight vendors’ products were not reviewed. Autonomy and Lookeen could not be more different in purpose, design, and features.
The report then tackles the “top five” search systems in terms of clicks on the author’s Web site. Yep, clicks. That’s a heck of a yardstick because what percentage of clicks were humans and what percentage was bot driven? No answer, of course.
The most popular “solutions” illustrate the weirdness of the sample. The number one solution is DataGravity, which is a data management system with various features and utilities. The next four “top” solutions are:
- Oracle Endeca – eCommerce and business intelligence and whatever Oracle can use the ageing system for
- The Google Search Appliance – discontinued with a cloud solution coming down the pike, sort of
- Lucene – open source, the engine behind Elasticsearch, which is quite remarkably not on the list of vendors
- Microsoft Fast Search – included in SharePoint to the delight of the integrators who charge to make the dog heel once in a while.
I find it fascinating that DataGravity (1,273) garnered almost 4X the “votes” as Microsoft Fast Search (404). I think there are more than 200 million plus SharePoint licensees. Many of these outfits have many questions about Fast Search. I would hazard a guess that DataGravity has a tiny fraction of the SharePoint installed base and its brand identity and company name recognition are a fraction of Microsoft’s. Weird data or meaningless.
The bulk of the report are comparison of various search engines. I could not figure out the logic of the comparisons. What, for example, do Lookeen and IBM StoredIQ have in common? Answer: Zero.
The search report strikes me as a bit of silliness. The report may be an anti sales document. But your mileage will differ. If it does, good luck to you.
Stephen E Arnold, December 30, 2016
Cacaphones: A Chapbook for the Cursory Consultant
December 16, 2016
I came across a post consisting of images from a mid tier consulting firm. You know. Mid tier, an azure chip consulting firm. This type of firm is distinct from blue-chip consulting firms like McKinsey, BCG, the “old”, pre spin out Snowden Booz, Allen & Hamilton. Those folks. Another generation’s Google.
You can find (for now) the collection of images at this link. The person posting this link will probably not get hired at the azure chip, mid tier outfit who cooked up the images in “Every Gartner Hype Cycle for Emerging Technologies Since 2000.” That works out to 16 years of “cacaphones”; that is, words which are an emission of jargon, buzzwords, and argot designed to help sell consulting work that benefits consultants.
The blue chip outfits mostly stick with the crazy lingo of MBAs, lawyers, accountants, and engineers who know who Milton and Whitman are.
Here’s a run down by year of the cacaphones. How many of these do you use? How many of these can you define even if you bandy the cacaphones around in meetings, at conferences, or at your favorite Starbuck’s?
Year 2000 Cacaphones (n=20 spoor)
3-D Web
Active Server Pages
Audio mining
Biometrics
Bluetooth
DSL/Cable modems
Digital ink
Enterprise portals
Java language
Jini
Micropayments
Quantum computing
Smart cards
Speech recognition
Synthetic characters
Voice over IP
Voice portals
WAP/Wireless Web
Webtops
XML
Year 2001 Cacaphones (n=19 spoor)
Active server pages
B2B e markets
B2C e business
Bluetooth
Digital signatures
Enterprise instant messaging
Enterprise portals
Head mounted displays
M commerce
PDA phones
Peer to peer
Personal fuel cells
Semantic Web
Synthetic characters
Voice over IP
Web services
Wireless LANs/802.11
Wireless Web/WAP
e payments
Year 2002 Cacaphones (n=21 spoor)
Biometrics
Bluetooth
E payments
E tags
Grid computing
Identity services
Location sensing
Nanocomputing
Natural language search
Peer to peer computing
Personal digital assistant phones
Personal fuel cells
Public key infrastructure
Speech recognition in call centers
Speech recognition on desktops
Text to speech
Virtual private networks
Voice over IP
WAP/Wireless Web
Web services
Wireless LANs/802.11
Year 2003 Cacaphones (n=24 spoor): The Year of the Portal
Advanced Web services in portals
Advanced integration in portals
Basic Web services support in portals
Basic search
Business process fusion
Contextual personalization
Federated portals across vendor families
Federated portals within vendor families
Integrated collaboration
Integrated content management
JSR170
Mobile access to portals
Open source portals
Personal work portals
Portal fabric
Portal ubiquity
Portlets
Process portals
Roll based personalization
SES (possibly the Korean girl musical group)
Virtual content repositories
WSRP and JSR 168
XML based multichannel output and interaction
Year 2004 Cacaphones (n=32 spoor): Revenge of the Portal
Advanced Web services in portals
Advanced integration in portals
Application platform suites
Basic Web services support in portals
Basic search
Business process fusion
Contextual personalization
Desktop portals
Federated portals across vendor families
Federated portals within vendor families
Hosted portals
Integrated collaboration
Integrated content management
Integrated open source content management
JSR168 (a portlet catalog)
JSR170 (content repository)
Micro portals
Mobile access to portals
Offline portals
Open source higher education portals
Open source horizontal portals
Portal fabric
Portal ubiquity
Portlets
Process portals
Rich client portals
Role based personalization
Smart enterpriser suites (maybe the 2003 SES?)
Syndication
Virtual content repositories
Web services for remote portals
XML based multichannel output and interaction
Year 2005 Cacaphones (n=41 spoor): A Bountiful Year of Caca
4G
902.16 2004 Worldwide inter operability for microwave access
Augmented reality
Biometric identity documents
Biometric user identification
Business process management suites
Business process networks
Business rule engines
Carbon nanotubes
Corporate Semantic Web
Corporate blogging
DNA logic
Desktop search (what?)
Electronic ink/digital paper
Handwriting recognition
Inkjet manufacturing
Internal Web services
Internet micropayments
Linux on desktop for mainstream business users
Location aware applications
Mesh networks Senor
Micro fuel cells (no longer personal)
Model drive approaches
Networked collective intelligence
Organic light emitting devices
Peer to peer VoIP
Podcasting
Prediction markets
Quantum computing
RFID (passive)
Really simple syndication
Services oriented architecture
Software as a Service
Speech recognition for telephony and call centers
Tablet PC
Text mining
Text to speech speech synthesis
Trusted computing group
Videoconferencing
VoIP (listed twice in the 2005 hype cycle)
XBRL
Year 2006 Cacaphones (n=32 spoor): A Year for Remembering Quantum Computing
Augmented reality
Biometric payments
Collective intelligence
Corporate blogging
Corporate Semantic Web
DNA logic
Digital paper/e paper
Enterprise instant messaging
Event driven architecture
Folksonomies
IPv6
Internal Web servicers
Location aware applications
Location aware technology
Mashup
Mesh networks: sensor
Model driven architectures
Offline Ajax
Prediction markets
Quantum computing
RFID
RSS enterprise
Smartphone
Social network analysis
Speech recognition for mobile devices
Speech to speech translation
Tablet PC Mobile phone payments
Telepresence
Tera-architectures
VoIP
Web 2.0
Wikis
Year 2007 Cacaphones (n=34 spoor): VoIP and Digital Fiesta
Bluetooth in automobiles
Broadband video on demand
Consumer telematics
Digital TV (cable and satellite)
Digital terrestrial TV
Digital video recorders
Digital video broadcasting–handheld
Fixed mobile converged voice service
HD Radio
HD optical disc players
HDTV displays
Household Wi-Fi
IPTV
Interactive TV
Legal file sharing / legitimate P2P
Micro projectors
Media distribution via game consoles
Mobile TV broadcasting
Mobile TV streaming
Mobile video on demand
Network DVR
Next generation satellite
OLED TVs
Online game consoles
PC based media center
Portable media players
Portable personality
Residential VoIP
Ultra mobile devices
Video on demand
Video chat over IP
Wire line home networking (coaxial and power line)
Widgets
Wire line home networking / dedicated Ethernet wiring
Year 2008 Cacaphones (n=27 spoor): The Hardware Influence
3D printing
Augmented reality
Basic Web services (Yep, basic)
Behavioral economics
Cloud computing
Context delivery architecture
Corporate blogging
Electronic paper
Erasable paper printing systems (Huh?)
Green IT
Idea management
Location aware applications
Micro blogging
Mobile robots
Public virtual worlds (Oh, boy)
RFID (case/pallet)
Service oriented architecture
Service oriented business applications
Social computing platforms
Social network analysis
Solid state drives
Surface computers (A mid tier person talked to Microsoft)
Tablet PC
Video telepresence
Virtual assistants
Web 2.0
Wikis
Year 2009 Cacaphones (n=35 spoor): Some Weird Stuff
3-D flat panel displays
3-D printing
Augmented reality
Behavioral economics (Someone took a night school course)
Cloud computing
Context delivery architecture
Corporate blogging
Developed markets (What?)
E book readers
Electronic paper
Green IT
Home health monitoring
Human augmentation
Idea management (What?)
Internet TV
Location aware applications
Mesh networks: sensor
Micro blogging
Mobile robots
Online video
Over the air mobile phone payment systems
Public virtual worlds
Quantum computing (Yippy. Back on the list)
RFID (case/pallet)
Services oriented architecture
Social network analysis
Social software suites (Huh?)
Speech recognition
Surface computers (Go, Microsoft)
Tablet PC
Video search (Discovering YouTube and Google Video search perchance)
Video telepresence
Web 2.0
Wikis
Wireless power
Year 2010 Cacaphones (n=32 spoor):The Début of Extreme
3D flat panel TVs and displays
3D printing Speech to speech translation
4G standard
Activity streams
Augmented reality
Autonomous vehicles
Biometric authentication methods
Broadband over power lines
Cloud computing
Cloud/Web platforms
Computer brain interface
Consumer generated media
Context delivery architecture
E book readers
Extreme transaction processing
Gesture recognition
Human augmentations
Idea management (round up those puppies, partner)
Interactive TV
Internet TV
Internet micropayment systems
Location aware applications
Media tablet
Mesh networks sensor
Micro blogging
Mobile application store
Mobile robots
Pen centric tablet PCs
Predictive analytics
Private cloud computing
Public virtual worlds
Social analytics
Speech recognition
Tangible user interfaces
Terahertz waves
Video search (again!)
Video telepresence
Virtual assistants
Wireless power
Year 2011 Cacaphones (n=41 spoor): A Year in Recycling
3D bio printing
3D printing
Activity streams
Augmented reality
Big Data and extreme processing and management
Biometric authentication methods
Cloud / Web platforms
Cloud computing
Computer brain interface
Context enriched services
E book readers (hello, Kindle)
Gamification
Gesture recognition
Group buying
Hosted virtual desktops
Human augmentation
Idea management
Image recognition
In memory database management systems
Internet TV
Internet of things
Location aware applications
Machine to machine communication services (ah, ha, a network)
Media table
Mesh networks sensor
Mobile application stores
Mobile robots
NFC payment
Natural language question answering
Predictive analytics
Private cloud computing
QR /color code consumerization
Quantum computing (it’s back again)
Social TV
Social analytics
Speech recognition
Speech to speech translation
Video analytics for customer services
Virtual assistants
Virtual worlds
Wireless power
Year 2012 Cacaphones (n=44 spoor): The Kitchen Sink Era
3D bio printing
3D printing
3D scanners
Activity streams
Application stores
Audio mining / speech analytics
Augmented reality
Automatic content recognition (Huh?)
Autonomous vehicles
Big Data (at last!)
Biometric authentication methods
Bring your own device
Cloud computing
Complex event processing
Consumer telematics
Consumerization
Crowdsourcing
Gamification
Gesture control
HTML5
Home health monitoring
Hosted virtual desktops
Human augmentation
Hybrid cloud computing
Idea management
In memory analytics
In memory database management systems
Internet of things
Machine to machine communication services
Media tablets
Mobile over the air payments
Mobile robots
NFC payment
Natural language question answering
Predictive analytics
Private cloud computing
Quantum computing (a familiar emerging technology)
Silicon anode batteries
Social analytics
Speech recognition
Speech to speech translation
Text analytics
Virtual worlds
Volumetric and holographic displays
Wireless power
Year 2013 Cacaphones (n=43 spoor): Losing the Familiar
3D bio printing
3D scanners
Activity streams
Affective computing
Augmented reality
Autonomous vehicles
Big Data
Bio acoustic sensing
Bio metric authentication methods
Bio chips
Brain computer interface
Cloud computing
Consumer 3D printing
Consumer telematics
Complex event processing
Content analytics
Electro vibration
Enterprise 3D printing
Gamification
Gesture control
Human augmentation
In memory analytics
In memory database management systems
Internet of things
Location intelligence
Machine to machine communication services
Mesh networks sensor
Mobile health monitoring
Mobile robots
Natural Language question answering
Neuro business (huh?)
Near field communication
Predictive analytics (a perennial favorite)
Prescriptive analytics
Quantified self (huh?)
Quantum computing (still an innovation trigger)
Smart dust
Speech recognition
Speech to speech translation
Virtual assistants
Virtual reality
Volumetric and holographic displays
Wearable user interfaces
Year 2014 Cacaphones (n=43 spoor):Time for Affective Computing
3D bio printing systems
3D scanners
Activity streams
Affective computing
Augmented reality
Autonomous vehicles
Big Data
Bio acoustic sensing
Biochips
Brain computer interface
Cloud computing
Complex event processing
Connected home
Consumer 3D printing
Consumer telematics
Content analytics (new jargon for the old jargon text analytics?)
Crypto currencies (the consultants discover Bitcoin)
Data science
Digital security (at last, security)
Enterprise 3D printing
Gamification
Gesture control
Human augmentation
Hybrid cloud computing
In memory analytics
In memory database management systems
Internet of things
Machine to machine communication services
Mobile health monitoring
Natural language question answering
Near field communications
Neuro business
Prescriptive analytics (do what the math says, Mary)
Quantum computing (still an innovation trigger)
Smart advisors
Smart robots (mobile robots have disappeared it seems)
Software defined anything (anything?)
Speech recognition
Speech to speech translation
Virtual personal assistants
Virtual reality
Volumetric and holographic displays
Wearable user interfaces
Year 2015 Cacaphones (n=37 spoor): Not Much Neuro Creativity Evident
3D bio printing systems for organ transplant
Advanced analytics with self service delivery
Affective computing
Augmented reality
Autonomous field vehicles (Isn’t this autonomous vehicles?)
Autonomous vehicles
Bio acoustic sensing
Biochips
Brain computer interface
Citizen data science
Connected home
Consumer 3D printing
Crypto currencies
Crypto currency exchange
Digital dexterity
Digital security
Enterprise 3D printing
Gesture control
Human augmentation
Hybrid cloud computing
Internet of Things
Internet of things platform
Machine learning (finally!)
Micro data centers
Natural language question answering
Neuro business
People literate technology (A first timer)
Quantum computing (still with us)
Smart advisors (who wants a stupid advisor?)
Smart dust
Smart robots
Software defined security (a variation on software defined anything)
Speech to speech translation
Virtual personal assistants
Virtual reality
Volumetric displays
Wearable
Year 2016 Cacaphones (n=33 spoor): Lots of “Smart”
4D printing (another dimension?)
802.11ax
Affective computing (More emotion in that silicon)
Augmented reality (Remember Google Glass)
Autonomous vehicles
Blockchain (A first timer)
Brain computer interface
Cognitive expert advisors
Commercial UAV drones (Go, Amazon)
Connected home
Context brokering (love that context word)
Conversational user interfaces
Data broker Platform as a Service or dbrPssS
Enterprise taxonomy and ontology management (Huh?)
General purpose machine intelligence (Wow!)
Gesture control devices
Internet of Things platform
Machine learning
Micro data centers
Nanotube electronics
Natural language question answering
Neuro morphic hardware (Huh?)
Personal analytics
Quantum computing (Plugging along)
Smart data discovery (Opposite of stupid data discovery?)
Smart dust
Smart robots
Smart workspace
Software defined security
Software defined anything, now SDx
Virtual personal assistants
Virtual reality
Volumetric displays.
Here’s a list of the cacaphones, deduplicated, in alphabetical order:
3-D Web
3-D flat panel displays
3-D printing
3D bio printing
3D flat panel TVs and displays
3D scanners
4D printing (another dimension?)
4G
4G standard
802.11ax
902.16
Active server pages
Activity streams
Advanced Web services in portals
Advanced analytics with self service delivery
Advanced integration in portals
Affective computing
Application platform suites
Application stores
Audio mining
Augmented reality
Automatic content recognition (Huh?)
Autonomous field vehicles
Autonomous vehicles
B2B e markets
B2C e business
Basic Web services
Basic Web services support in portals
Basic search
Behavioral economics
Big Data
Bio acoustic sensing
Biochips
Bio metric authentication methods
Bio metric identity documents
Bio metric payments
Bio metric user identification
Bio metrics
Blockchain (A first timer)
Bluetooth
Bluetooth in automobiles
Brain computer interface
Bring your own device. BYOB
Broadband over power lines
Broadband video on demand
Business process fusion
Business process management suites
Business process networks
Business rule engines
Carbon nanotubes
Citizen data science
Cloud / Web platforms
Cloud computing
Cloud/Web platforms
Cognitive expert advisers
Collective intelligence
Commercial UAV drones (Go, Amazon)
Complex event processing
Computer brain interface
Connected home
Consumer 3D printing
Consumer generated media
Consumer telematics
Consumerization
Content analytics
Context brokering
Context delivery architecture
Context enriched services
Contextual personalization
Conversational user interfaces
Corporate Semantic Web
Corporate blogging
Crowdsourcing
Crypto currencies
DNA logic
DSL/Cable modems
Data broker Platform as a Service or dbrPssS
Data science
Desktop portals
Desktop search
Developed markets
Digital TV (cable and satellite)
Digital dexterity
Digital ink
Digital paper
Digital security
Digital signatures
Digital terrestrial TV
Digital video recorders
Digital video broadcasting–handheld
E book readers
E payments
E tags
Electronic ink
Electronic paper
Electro vibration
Enterprise 3D printing
Enterprise instant messaging
Enterprise portals
Enterprise taxonomy and ontology management
Erasable paper printing systems
Event driven architecture
Extreme processing
Extreme transaction processing
Federated portals across vendor families
Fixed mobile converged voice service
Folksonomies
Gamification
General purpose machine intelligence (Wow!)
Gesture control devices
Gesture recognition
Green IT
Grid computing
Group buying
HD Radio
HD optical disc players
HDTV displays
HTML5
Handwriting recognition
Head mounted displays
Home health monitoring
Hosted portals
Hosted virtual desktops
Household Wi-Fi
Human augmentation
Hybrid cloud computing
IPTV
IPv6
Idea management
Identity survives
Image recognition
In memory analytics
In memory database management systems
Ink jet manufacturing
Integrated collaboration
Integrated content management
Integrated open source content management
Interactive TV
Internal Web services
Internet TV
Internet micro payment systems
Internet micro payments
Internet of Things
Internet of Things platform
JSR168 (a portlet catalog)
JSR170 (content repository)
Java language
Jini
Legal file sharing / legitimate P2P
Linux on desktop for mainstream business users
Location aware applications
Location intelligence
Location sensing
M commerce
Machine learning
Machine to machine communication services
Mash up
Media distribution via game consoles
Media tablets
Mesh networks sensor
Micro data centers
Micro fuel cells
Micro portals
Micro blogging
Micro payments
Micro projectors
Mobile TV broadcasting
Mobile TV streaming
Mobile access to portals
Mobile application store
Bio metric authentication methods
Mobile application stores
Mobile health monitoring
Mobile over the air payments
Mobile robots
Mobile video on demand
Model drive approaches
Model driven architectures
NFC payment
Nanocomputing
Nanotube electronics
Natural language question answering
Natural language search
Near field communications
Network DVR
Networked collective intelligence
Neuro business
Neuro morphic hardware (Huh?)
Neuro business (huh?)
Next generation satellite
OLED TVs
Offline Ajax
Offline portals
Online game consoles
Online video
Open source higher education portals
Open source horizontal portals
Open source portals
Organic light emitting devices
Over the air mobile phone payment systems
PC based media center
PDA phones
Peer to peer
Peer to peer VoIP
Peer to peer computing
Pen centric tablet PCs
People literate technology (A first timer)
Personal analytics
Personal digital assistant phones
Personal fuel cells
Personal work portals
Podcasting
Portable media players
Portable personality
Portal fabric
Portal ubiquity
Portlets
Prediction markets
Predictive analytics
Prescriptive analytics
Private cloud computing
Process portals
Public key infrastructure
Public virtual worlds
QR /color code consumerization
Quantified self (huh?)
Quantum computing
RFID
RFID (case/pallet)
RFID (passive)
RSS enterprise
Really simple syndication
Residential VoIP
Rich client portals
Role based personalization
SES (possibly the Korean girl musical group)
Semantic Web
Service oriented architecture
Service oriented business applications
Services oriented architecture
Silicon anode batteries
Smart advisers
Smart cards
Smart data discovery
Smart dust
Smart enterprise suites (maybe the 2003 SES?)
Smart robots
Smart workspace
Smart phone
Social TV
Social analytics
Social computing platforms
Social network analysis
Social software suites (Huh?)
Software defined security
Software as a Service
Software defined anything, now SDx
Software defined security (a variation on software defined anything)
Solid state drives
Speech analytics
Speech recognition
Speech recognition for mobile devices
Speech recognition for telephony and call centers
Speech recognition in call centers
Speech recognition on desktops
Speech to speech translation
Speech to speech translation
Speech to speech translation
Surface computers
Syndication
Synthetic characters
Tablet PC
Tablet PC Mobile phone payments
Tangible user interfaces
Telepresence
Tera-architectures
Tera hertz waves
Text analytics
Text mining
Text to speech
Text to speech speech synthesis
Trusted computing group
Ultra mobile devices
Video analytics for customer services
Video chat over IP
Video on demand
Video search
Video telepresence
Videoconferencing
Virtual assistants
Virtual content repositories
Virtual personal assistants
Virtual private networks
Virtual reality
Virtual worlds
VoIP
Voice over IP
Voice portals
Volumetric and holographic displays
Volumetric displays
WAP/Wireless Web
WSRP and JSR 168
Wearable
Wearable user interfaces
Web 2.0
Web services
Web services for remote portals
Webtops
Widgets
Wikis
Wireless LANs/802.11
Wireless Web/WAP
Wireless power
Wire line home networking (coaxial and power line)
Wire line home networking / dedicated Ethernet wiring
Worldwide inter operability for microwave access (Yes!)
XBRL
XML
XML based multichannel output and interaction
Observations
- Each annual list is what appears to be a subjective round up of jargon. Unlike Google Trends, the lists and their relative placement on the hype graph seem subjective.
- Some drums are beaten loudly and for years; examples include portal (20 mentions). Other inclusions are pretty darned weird or incomprehensible; for instance, digital dexterity, quantified self, synthetic characters, electro vibration, and behavioral economics.
- The lists with their suggestion of what’s coming, what’s here, and what’s going out of style is obviously a marketing exercise. The give away is that collective cacaphones skew to business processes, hot hardware (real or imagined), and network services. My hypothesis is that the mid tier outfit wants to sell bread-and-butter advice along with speculation about the world of Star Wars and Star Trek.
- One would expect an entry to appear each year with its location adjusted to reflect the market grip of the “innovation.” That’s not the case. Items appear once like behavior economics and then disappear. I asked myself, “is this annual cacaphone graph prepared over kale and sushi in a brainstorming session with participants Googling for ideas?”
You will be able to divine the future by contemplating these alphabetical lists and doing some poetical extrapolation. Security appears in four different forms, but lags behind the burning hot subject of portlet. Apply your efforts to “neuro business” and thrive or not. By the way, I have absolutely zero idea what to do with my “quantified self” when I use “neuro morphic hardware.” Stupid, right?
Stephen E Arnold, December 16, 2016
Big Data Is So Big
November 4, 2016
I love simplifications. I love simplifications even more when they arrive with nary a footnote, explanation of sources, or comments about methodology. Ta da. Let me point you to an IDC chart at this location. If the link does not resolve, contact IDC. I bet you can buy this picture.
My copy arrived via a tweet. More fascinating that the weird collection of circles is that the work comes from the same outfit which tried to sell my research on Amazon. The tweet with the wonky chart was free, but IDC slapped a $3,500 price tag on eight pages of information with my name but without my permission for its Amazon venture. At least my research team used footnotes. Ah, IDC, home of the “how much time you waste looking for information” craziness. A wonderful resource because — you know, like, really — Big Data are so big.
Stephen E Arnold, November 4, 2016
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