Cautious Words on Microsoft Delve
October 22, 2014
Much buzz has been collecting around Microsoft’s Delve (formerly known as Oslo), the new search-and-discovery component of Office 365. ComputerWorldUK, however, raises some questions in, “Delve, Office Graph Must Transcend Office 365 to be Revolutionary.” The application is designed to tap into the company’s Office Graph machine-learning engine, but apparently has a way to go before fulfilling its creators’ goals. Reporter Juan Carlos Perez writes:
“If Microsoft realizes its Office Graph vision — and it may take years to materialize — then the way information workers interact with business software today and the way they find digital information will seem ancient and grossly inefficient. And Microsoft might fly past competitors in the enterprise with a technology that creates a sort of cockpit that automates and simplifies for employees the use of their Microsoft and non-Microsoft software.”
Delve began gradually rolling out to Office users in September, with the process to be completed sometime next year. The tool can be used as a conventional search engine, but it is designed to do much more. The article supplies this example:
“Delve knows that ‘Joe’ has a meeting in an hour, what its topic is and who will be in attendance. So, Delve proactively fetches relevant documents, files and information about the topic and the participants, and displays them on its dashboard, so Joe can be prepared for the meeting. Joe didn’t have to spend 30 minutes compiling all this data manually, assuming that he even would have had the time to do it, and if he did, that he would have been able to find the information, a big challenge for employees of all stripes everywhere.”
Sounds great! However, Perez notes that some open questions stand between here and the realization of Delve’s potential. Perhaps most obviously, being able to comb only Office applications for data is limiting; most of us don’t limit ourselves to Microsoft products (as much as the company might like us to.) There are considerable technical challenges there. Then there’s the privacy issue—will users find it’s “stealthy technology” creepy, and possibly be worried about nosy supervisors? Apparently, some more end-user controls are planned, but they may not address that concern. See the article for more thorough discussion of these issues. Will Delve overcome these obstacles?
Cynthia Murrell, October 22, 2014
Sponsored by ArnoldIT.com, developer of Augmentext
SLI Systems: Stunning Factoid
October 21, 2014
SLI Systems reported its financial results in mid October 2014. The numbers were interesting. The company reported revenue of $22.1 million, which is good for search software. However, the company said that it lost $5.9 million. See “SLI Systems Poised for Continued Growth in Rapidly Expanding E-Commerce Industry.”
In the write up was a remarkable factoid; to wit:
More than 500 e-commerce businesses are using SLI’s solutions, which can service more than a billion queries in a single month,” said SLI CEO Shaun Ryan. “That’s ten percent of the volume that Google reportedly serves in North America in the same time frame. And with continued growth, we expect to continue adding scale to our high-margin business.”
From my point of view, this is an intriguing number. In order to break even, SLI Systems needed almost $30 million in 2013-2014. Based on the information I have gathered over the years, search vendors dependent on venture funding find themselves in an SLI Systems boat frequently.
Keep in mind that the cost of maintaining a search system is often higher than revenues can support; therefore, search vendors face red ink each time the accountant tallies up the numbers.
Why not get more customers? Well, that costs money.
Why not charge more? Well, savvy customers may look at open source options like Magento.
Well, why not come out with a killer product? Most search vendors believe they have killer products.
Convincing analysts and prospects is a different type of pizza. But if the factoid is correct, SLI Systems is generating hefty traffic when aggregated. Is it time for a revised business model?
Stephen E Arnold, October 22, 2014
LucidWorks and Its Clueless Graphic
October 21, 2014
I noted a link to a LucidWorks presentation in a tweet. I navigated to the presentation on Slideshare. The approach in the presentation was trendy. My approach to presentations is untrendy, so I am no judge.
I found one slide particularly suggestive of the company’s approach to marketing. On slide 20 I saw this:
I am not exactly certain what vowel the asterisk represents. The slides strikes me as possibly offensive. But I live in rural Kentucky. What do I know? I assume the message is clear.
Perhaps this type of marketing messaging is one of the reasons ElasticSearch appears to have more momentum in the commercialized open source search sector?
Here’s a representative ElasticSearch slide from “A Gentle Introduction to ElasticSearch.”
Which company’s presentation resonates with you? Cluelessness or clues?
Stephen E Arnold, October 22, 2014
Watson Analytic Example
October 21, 2014
Navigate to Thinglink. At this location is an example of the type of graphic that can be generated with output from Watson, IBM’s next big thing. A graphic artist has taken the data and created an eye snapping infographic. How many other systems can generate this type of output? Quite a few if the information in my analytics files are representative. Is it necessary to use IBM Watson when Microsoft Excel and an open source tool like Tableau are available? IBM Watson analyzed 135 million tweets from 10 countries in Central and South America. Brazil was excluded.
Twitter said in 2013:
Brazil is one of our largest markets with a strong user base. Twitter has already become an important part of our lives in Brazil and, by strengthening our local presence, we plan to continue delighting our users as well as creating new opportunities for marketers who want to connect with them.
Perhaps I overlooked Brazil. No big deal.
Stephen E Arnold, October 22, 2014
ElasticSearch How To: A Useful Case Example
October 21, 2014
If you want to avoid the hassle of some proprietary search engines, you may want to take a look at this case study about ElasticSearch. Navigate to “Building Scalable Search from Scratch with ElasticSearch.” The author works through his process for putting ElasticSearch to work in content space with a variety of information; for example, products, text collections, and user information.
What makes this write up useful is the logical layout of the article and the inclusion of a requirements summary, block diagrams, and code snippets.
This type of solid user support is one reason ElasticSearch is outpacing some open source search competitors like LucidWorks and Nutch.
Highly recommended. (As far as I can tell, no mid tier consulting firms has surfed on this content. Dave Schubmehl, this may be an opportunity.)
Stephen E Arnold, October 21, 2014
Big Data Defined 43 Ways
October 21, 2014
A happy quack to the reader who alerted us to “”What Is Big Data?” The write up consists of 43 definitions provided by luminaries in a variety of fields. If you are in search of enlightenment with regard to Big Data, navigate to the story and dig in.
I found a couple of definitions interesting. Let me highlight Daniel Gillick’s and Hal Varian’s. Both are hooked up with Google, one of the big time big data outfits.
Mr. Gillick says:
Historically, most decisions — political, military, business, and personal — have been made by brains [that] have unpredictable logic and operate on subjective experiential evidence. “Big data” represents a cultural shift in which more and more decisions are made by algorithms with transparent logic, operating on documented immutable evidence. I think “big” refers more to the pervasive nature of this change than to any particular amount of data.
Mr. Varian says:
Big data means data that cannot fit easily into a standard relational database.
There you have it: A cultural shift and anything that won’t fit in a Codd-style data management system. Are the other 41 definitions superfluous?
Stephen E Arnold, October 21, 2014
Xanalys: Sidelight on the Name Watson
October 21, 2014
I read a thought provoking post on the Xanalys blog. The write up is “Watson a Name?”
The article states:
long before IBM began using the name Watson for its artificially intelligent computer system – the system designed to play the TV game show Jeopardy – the name was used by Xanalys for its industry leading investigation management software.
The write up continues:
Xanalys’ Watson™ software was born out of Cambridge, England technology company Harlequin in the late 1980s. The programs in the Watson suite include Elementary Watson, Watson Mapping, Watson Pro, Watson PowerCase and Watson CaseCall. The foundation of the suite, though, was always Watson. Watson, a name still trademarked by Xanalys, is a powerful visual analysis tool for operational intelligence that enables investigators to rapidly import, track and then interpret data from a wide range of sources. Watson provides a powerful querying facility to support the effective analysis of that data that can actually identify links between contacts and reveal associations among activities that are not immediately apparent to an investigator or analyst.
Xanalys does not seem overly troubled by this “coincidence.” My thought is that IBM may have been somewhat casual in its branding of its search system. Another possibility is that IBM was just doing what large companies do.
For more information about Xanalys, navigate to www.xanalys.com.
Stephen E Arnold, October 21, 2014
Autonomy: 33 APIs
October 21, 2014
Curious about Hewlett Packard’s Autonomy APIs? You can see the list of 33 at IdolOnDemand.com. If you are curious about Autonomy’s Big Data capabilities, you may be puzzled about the lack of explicit analytics application programming interfaces. Don’t be. The savvy developer selects operations, takes outputs, and pumps the data into a search based application, third party number crunching system, a data management system, or plain old Excel. What’s interesting is that the naming of the APIs makes clear the search-centric nature of Autonomy. The marketing of IDOL as a service or a cloud solution shifts attention away from search in my view.
Stephen E Arnold, October 21, 2014
Report Predicts Big Data Growth
October 21, 2014
Here’s another prediction on the future of Big Data. WhaTech calls our attention to a recent report from ReportsnReports in, “Explore Global Big Data Market that Will Grow at a CAGR of 34.17% by 2018.” Those on the hook to venture firms looking for Big Data payoffs hope the estimate is on the low side. Keep in mind, though, that this figure comes from a wild and crazy consulting firm report. The press release tells us:
“Global Big Data Market 2014-2018, has been prepared based on an in-depth market analysis with inputs from industry experts. The report covers the Americas, and the EMEA and APAC regions; it also covers the Global Big Data market landscape and its growth prospects in the coming years. The report also includes a discussion of the key vendors operating in this market.”
See the write-up for a list of vendors mentioned in the report; that we can get for free. The post goes on to list the “key questions” addressed by the $2500 report:
“What will the market size be in 2018 and what will the growth rate be?
What are the key market trends?
What is driving this market?
What are the challenges to market growth?
Who are the key vendors in this market space?
What are the market opportunities and threats faced by the key vendors?
What are the strengths and weaknesses of the key vendors?”
Good questions, all.
Cynthia Murrell, October 21, 2014
Sponsored by ArnoldIT.com, developer of Augmentext
Coveo Pivots to Federated Search
October 21, 2014
Through a post at their blog Coveo Insights, enterprise-search firm Coveo urges, “Power Your Customer Service with Unified Search Driven Knowledge.” The write-up gives a few reasons why such “omni-channel” (federated) search functionality is a wise choice for customer service. Writer and Coveo marketing director Tucker Hall explains:
“Customers … engage with companies across a growing number of channels — from self-service portals and contact centers, to social media and field service engagements. Today’s savvy customer expects (and deserves) a seamless and consistent service experience across all of these channels. Omni-channel customer service has now become essential for companies hoping to maximize customer engagement, satisfaction, and retention.
“Successful omni-channel customer service can prove difficult regardless of the specific technologies and systems an organization has in place. That’s because success demands that customers and support personnel alike have swift, intuitive access to the case-resolving knowledge and expertise they need, when and how they need it.”
Hall asserts that many companies are missing out because they “fail to appreciate” the reasons to choose federated search: data and expertise are located in many systems, crowd-sourcing is a thing, and analytics must be actionable. But you, dear reader, already knew those, didn’t you? More on these points can be found in Coveo’s solution brief on the subject (registration required).
It is interesting to note that, while Coveo and others focus on federated search, Microsoft is more into the search-without-searching method called Delve. Let many flowers bloom!
Coveo serves organizations large, medium, and small with solutions that aim to be agile and easy to use yet scalable, fast, and efficient. The company was founded in 2005 by members of the team which developed Copernic Desktop Search. Coveo maintains offices in the U.S., Netherlands, and Quebec.
Cynthia Murrell, October 21, 2014
Sponsored by ArnoldIT.com, developer of Augmentext
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