Global Enterprise Search Market Survey Released
July 30, 2013
Industry experts have performed an in-depth market analysis to define the global enterprise search market landscape. It is an enterprise “state of the union” if you will. Read all about it in the SBWire press release, “Industrial Survey: Global Enterprise Search Market 2012-2016.”
The article explains the scope of the report and the general state of the enterprise search market:
“Global Enterprise Search market to grow at a CAGR of 12.98 percent over the period 2012-2016. One of the key factors contributing to this market growth is the increased demand for rapid and easy data access. The Global Enterprise Search market has also been witnessing the emergence of software-as-a-service based solutions. However, the high cost of implementation could pose a challenge to the growth of this market.”
The full report can be purchased and downloaded through ResearchMoz.
It does seem valid that some organizations are concerned about the cost of implementing software as a service (SaaS). However, there are many affordable and intuitive solutions that are meeting the needs of even small organizations through their usage of open source infrastructure. For instance, LucidWorks offers both LucidWorks Big Data and LucidWorks Search, which are each flexible enough to be both affordable and highly effective.
Emily Rae Aldridge, July 30, 2013
Sponsored by ArnoldIT.com, developer of Beyond Search
Search Factoid from Research Moz
July 29, 2013
I saw “Global Enterprise Search Market to 2016: Latest Industry Analysis, Strategies, Survey, Size, Share, Growth Trends, and Forecast Research Report Available at Research Moz.” The news release explains that Research Moz has completed a study of the enterprise search market, making an effort to cover every possible angle. The report, unlike other analyses, purposes to cover the Middle East and what I used to think of as the Pacific Rim.
I navigated to Research Moz and learned that the report is 58 pages in length. The most fascinating item in the news release, in my view, was:
Global Enterprise Search market to grow at a CAGR of 12.98 percent over the period 2012-2016.
If the robust growth rate is accurate, the search and content processing firms working hard to cover their payroll can look forward to a brighter future. The information available to me suggests that search is fracturing, making growth estimates difficult. The fastest growing sectors like military intelligence are less than forthcoming about the size of the contracts awarded by various nation states. In addition, the sharp uptake of open source search solutions continues to have an impact of some commercial vendors. Companies which sell services to support information retrieval are, in my view, consulting and engineering firms, not vendors of search solutions.
Research Moz also offers reports on other global markets; for example, pet food.
More information is available at http://www.researchmoz.us/global-enterprise-search-market-2012-2016-report.html. Pricing information was not available.
Stephen E Arnold, July 29, 2013
Sponsored by Xenky
Snowden Controversy Will Mean More Big Data Transparency
July 29, 2013
With the recent news of the NSA’s phone records requests and deep use of data mining, we are on the cusp of a new frontier for big data and its relationship to the government. However, a little digging shows this fascinating time capsule from 2007, “Lost in the Cloud: Google in the US Government.”
According to this whitepaper:
“Consumer Watchdog investigation has found. One of the most visible signs of Google’s clout is the hangars at the National Aeronautics and Space Administration’s Moffett Air0ield, near Google’s world headquarters, where a 0leet of jets and helicopters stands ready to ferry the company’s top executives near or far, for business or pleasure. When a deal between NASA and top Google executives to use the base was 0irst disclosed in 2007, it called for only four jets to use the base.”
Not a stunner, really. The government has long been a supporter of big data and data mining technology that is sweeping the private sector these days. But, honestly, did anyone think Uncle Sam was sinking money into this field to help refine the census? We are not political one way or the other, but what we do love is transparency in big data and we suspect that’s what’s on the horizon after this affair.
Patrick Roland, July 29, 2013
Sponsored by ArnoldIT.com, developer of Beyond Search
Database Indexing Explained
July 29, 2013
Finally, everything you need to explain database indexing to your mom over breakfast. Stack Overflow hosts the discussion, “How Does Database Indexing Work?” The original question, posed by a user going by Zenph Yan, asks for an answer at a “database agnostic level.” The lead answer, also submitted by Zenph Yan, makes for a respectable article all by itself. (Asked and answered by the same user? Odd, perhaps, but that is actively encouraged at Stack Overflow.)
Yan clearly defines the subject at hand:
“Indexing is a way of sorting a number of records on multiple fields. Creating an index on a field in a table creates another data structure which holds the field value, and pointer to the record it relates to. This index structure is then sorted, allowing Binary Searches to be performed on it.
“The downside to indexing is that these indexes require additional space on the disk, since the indexes are stored together in a table using the MyISAM engine, this file can quickly reach the size limits of the underlying file system if many fields within the same table are indexed.”
Yan’s explanation also describes why indexing is needed, how it works (with examples), and when it is called for. It is worth checking out for those pondering his question. A couple other users contributed links to helpful resources. Der U suggests another Stack Overflow discussion, “What do Clustered and Non Clustered Index Actually Mean?“, while one, dohaivu, recommends the site, Use the Index, Luke.
Cynthia Murrell, July 29, 2013
Sponsored by ArnoldIT.com, developer of Augmentext
Selfless Analytic Partnerships Score Big
July 29, 2013
One would think the big data analytics field would be cutthroat and bloody with competition. Oddly, though, it is actually a mostly friendly affair. It seems like we hear more and more about disparate firms partnering up to give customers a better product. Such was the case with this recent Business Wire story, “JackBe Unveils Presto Real-Time Analytics Add On with Terracotta Big Memory.”
According to the story:
“JackBe®, the leading provider of Real-Time Actionable Intelligence software, today released its Presto Real-Time Analytics Add-On With Terracotta BigMemory (RTA Add-On), which bundles Terracotta’s enterprise-grade BigMemory in-memory data management platform for seamless high performance in-memory analytics. This supercharged combination of in-memory and analytics allows Presto to mash Big Data with live and transactional enterprise data into actionable dashboards in a fraction of the time required by traditional methods, putting real-time Big Data analytics at the fingertips of decision-makers.”
We like the way these two companies are playing to their strengths. When selfless analytics minds do that, the customers score big. It is reminiscent of the IBM big data partnership. In these cases we are seeing savvy companies partnering to do something extraordinary.
Patrick Roland, July 29, 2013
Sponsored by ArnoldIT.com, developer of Beyond Search
CIO Top 10 Big Data Startups
July 29, 2013
CIO.com has finalized their list of the top ten big data startups to watch. The results have been released. Read more in their article, “10 Top Big Data Startups to Watch–Final Rankings.”
The article states the criteria:
“After more than 4,000 votes were cast, the final Big Data startup rankings are in. Keep in mind that while voting was weighted heavily, it was not the be-all-and-end-all consideration. Other criteria included big-name end users, VC funding, the pedigree of the management team and market positioning.”
So after such thorough analysis, we were pleased to see a few familiar names on the list. Several good companies that are delivering quality products, LucidWorks among them:
“LucidWorks did well in the voting, has solid funding ($16 million) and is uniquely positioned in this roundup with their focus on Big Data search. However, they’ll need to get more on-the-record customers on the books to climb higher than this.”
LucidWorks Big Data will continue to do well among its existing customer base and expand into further markets. Their open source platform brings the strength of Apache Lucene Solr to an intuitive solution that is ready out-of-the-box.
Emily Rae Aldridge, July 29, 2013
Sponsored by ArnoldIT.com, developer of Beyond Search
Marketers! OdinText Can Help You
July 28, 2013
I saw a flurry of links to a news release titled “New Patented Text Analytics Analytics Approach [sic]” about a text analytics package. The company receiving the patent is OdinText / Anderson Analytics. The company asserts that it provides a text analytics system for market research professionals. I was intrigued by an “analytics analytics approach.”
The news story describes US 8,475,498, “Natural Language Text Analytics.” The abstract states:
A method of text analytics includes filtering a plurality of unfiltered records having unstructured data into at least a first group and a second group. The first group and said second group each include at least two records and the first group is different than the second group. The method includes determining a first proportion of occurrence for a term by comparing a first number of records having at least one occurrence of the term in the first group to a first total number of records in the first group, determining a second proportion of occurrence for the term by comparing a second number of records having at least one occurrence of the term in said second group to a second total number of records in the second group, and comparing the first proportion of occurrence to the second proportion of occurrence to yield a resultant comparison occurrence.
Anderson Analytics’ Web site says:
We Focus on Getting Accurate and Relevant Data. Quality research starts with quality data, and the best answers come from well thought out questions. Whether we are working with internal business data or gathering primary research, we make sure that projects are of correct and sufficient scope to accurately address the business need.
I scanned the document and thought about Ramanathan Guha’s programmable search engine and context server invention; for example, US 8,316,040 and its related inventions from 2007 forward. The Guha system and method are quite different from the Odin/Anderson system and method.
If you are an NLP savvy marketer, you may want to take a closer look at OdinText. The system “overcomes, alleviates, and/or mitigates one or more of the aforementioned [references a list of known NLP search problems] and other deleterious effects of prior art.
Google and Dr. Guha, you may have some work to do.
Stephen E Arnold, July 28, 2013
Sponsored by Xenky
Is Duck Duck Go a No Go?
July 28, 2013
I’m sorry to say that I agree with Brian Mayer wholeheartedly when he explains, “I Used DuckDuckGo for a Week and Had to Switch Back. Here’s Why.” In his blog, Notes, the busy entrepreneur says he was prompted to give the Google alternative another try upon recent revelations about government snooping, since DuckDuckGo famously does not track users’ search terms. The exercise just reinforced for the blogger just how much better Google is at delivering relevant results. He writes:
“Now, I love that DuckDuckGo doesn’t track searches. In terms of their commitment to privacy and their users, I don’t think there’s a better option. And I love that there’s an alternative for people concerned about their data being collected. But it took me only a week using DuckDuckGo to appreciate the little things that Google does that still make it a far superior product.”
Mayer lists some of those “little” things: Google is faster; it keeps up with current events (returning more timely results); it refuses to index sites containing code errors (!); and it knows which Wikipedia articles are worth pulling up. He concludes:
“I tried, and for the things that matter to me, it seems that Google is just a better experience. I hope DuckDuckGo improves the product, because eventually I would love to switch back. But philosophical alignment isn’t enough to get me to use an inferior product.”
I can corroborate Mayer’s account; I have had a similarly fraught relationship with this water fowl. I still use it if I’m looking up something sensitive, like health or money stuff. For the most part, though, I am also waiting for the duck to improve. At least I know I’m not waiting alone.
Cynthia Murrell, July 28, 2013
Sponsored by ArnoldIT.com, developer of Augmentext
Big O Explained: Why Systems Are Alike?
July 27, 2013
In several of my recent lectures, I pointed out that most end users cannot differentiate among search systems. The comment made about these systems is often, “Why can’t these systems be like Google?” I concluded that the similarity of requests suggests that systems are essentially identical.
One reason is that training in university and the “use what works” approach in the real world produces search, content processing, and analytics systems that are pretty much indistinguishable. There are differences, but these can be appreciated only when a person takes the systems apart. Even then, differences are difficult to explain; for example, why a threshold value in System A is 15 percent lower than in System B. When dealing with sketchy data, the difference is usually irrelevant.
Another reason is that today’s systems are struggling to cope with operations that stretch the capabilities of even the most robust systems. Developers have to balance what the engineering plan wants to do with what can be done in a reasonable amount of time on an existing system.
Enter Big O.
You may want to take a look at “Big O Notation Explained by a Self-Taught Programmer.” I found the write up interesting and clear. The main point in my opinion is:
Consider this function:
def all_combinations(the_list): results = [] for item in the_list: for inner_item in the_list: results.append((item, inner_item)) return resultsThis matches every item in the list with every other item in the list. If we gave it an array
[1,2,3], we’d get back[(1,1) (1,2), (1,3), (2, 1), (2, 2), (2, 3), (3, 1), (3, 2), (3, 3)]. This is part of the field of combinatorics(warning: scary math terms!), which is the mathematical field which studies combinations of things. This function (or algorithm, if you want to sound fancy) is consideredO(n^2). This is because for every item in the list (akanfor the input size), we have to donmore operations. Son * n == n^2.Below is a comparison of each of these graphs, for reference. You can see that an
O(n^2)function will get slow very quickly where as something that operates in constant time will be much better.
Net net: Developers have to do what works. Search and related content processes are complex. In order to get the work done, search systems have embraced “what works.” Over time, we get undifferentiable systems.
Disagree? Use the comments section to explain.
Stephen E Arnold, July 27, 2013
Sponsored by Xenky
OpenText Releases Web Experience Management Solution
July 27, 2013
From OpenText we read an interesting article called “Next Generation Web Experience Management.” The majority of the article discusses the context in which Web Experience Management (WEM) is needed. We also learned that OpenText has released a WEM solution.
According to Aberdeen Group research, leading organizations are delivering consistent and relevant messages. Not only are they doing that, but they also send these messages across multiple platforms.
The article states:
“The right technologies are required to deliver brand experiences in an efficient, pleasing, and consistent manner to the consumer at every touch point. For experiences to be satisfying (and build brand equity in your products and services), they should be rich, consistent, and personalized. Today’s consumer expects highly tailored, adaptable, and even predictable digital experiences. Web Experience Management (WEM) facilitates the management and optimization of experience across a variety of channels and platforms to create compelling customer experiences, promote consistent omni-channel brand experiences, and improve engagement with responsive design.”
Technology as a vessel to deliver the brand experience is not a novel concept, but the extent to which more doors are opening in this area — such as web experience management — is noteworthy indeed.
Megan Feil, July 27, 2013
Sponsored by ArnoldIT.com, developer of Beyond Search
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