Lexmark Upgrades Its Enterprise Search
September 30, 2016
Enterprise search has taken a back a back seat to search news regarding Google’s next endeavor and what the next big thing is in big data. Enterprise search may have taken a back seat in my news feed, but it is still a major component in enterprise systems. You can even speculate that without a search function, enterprise systems are useless.
Lexmark, one of the largest suppliers of printers and business solutions in the country, understand the importance of enterprise search. This is why they recently updated the description of its Perceptive Enterprise Search in its system’s technical specifications:
Perceptive Enterprise Search is a suite of enterprise applications that offer a choice of options for high performance search and mobile information access. The technical specifications in this document are specific to Perceptive Enterprise Search version 10.6…
A required amount of memory and disk space is provided. You must meet these requirements to support your Perceptive Enterprise Search system. These requirements specifically list the needs of Perceptive Enterprise Search and do not include any amount of memory or disk space you require for the operating system, environment, or other software that runs on the same machine.
Some technical specifications also provide recommendations. While requirements define the minimum system required to run Perceptive Enterprise Search, the recommended specifications serve as suggestions to improve the performance of your system. For maximum performance, review your specific environment, network, and platform capabilities and analyze your planned business usage of the system. Your specific system may require additional resources above these recommendations.”
It is pretty standard fare when it comes to technical specifications, in other words, not that interesting but necessary to make the enterprise system work correctly.
Whitney Grace, September 30, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
VirtualWorks Purchases Natural Language Processing Firm
July 8, 2016
Another day, another merger. PR Newswire released a story, VirtualWorks and Language Tools Announce Merger, which covers Virtual Works’ purchase of Language Tools. In Language Tools, they will inherit computational linguistics and natural language processing technologies. Virtual Works is an enterprise search firm. Erik Baklid, Chief Executive Officer of VirtualWorks is quoted in the article,
“We are incredibly excited about what this combined merger means to the future of our business. The potential to analyze and make sense of the vast unstructured data that exists for enterprises, both internally and externally, cannot be understated. Our underlying technology offers a sophisticated solution to extract meaning from text in a systematic way without the shortcomings of machine learning. We are well positioned to bring to market applications that provide insight, never before possible, into the vast majority of data that is out there.”
This is another case of a company positioning themselves as a leader in enterprise search. Are they anything special? Well, the news release mentions several core technologies will be bolstered due to the merger: text analytics, data management, and discovery techniques. We will have to wait and see what their future holds in regards to the enterprise search and business intelligence sector they seek to be a leader in.
Megan Feil, July 8, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Enterprise Search Is Stuck in the Past
July 4, 2016
Enterprise search is one of the driving forces behind an enterprise system because the entire purpose of the system is to encourage collaboration and quickly find information. While enterprise search is an essential tool, according to Computer Weekly’s article. “Beyond Keywords: Bringing Initiative To Enterprise Search” the feature is stuck in the past.
Enterprise search is due for an upgrade. The amount of enterprise data has increased, but the underlying information management system remains the same. Structured data is easy to make comply with the standard information management system, however, it is the unstructured data that holds the most valuable information. Unstructured information is hard to categorize, but natural language processing is being used to add context. Ontotext combined natural language processing with a graph database, allowing the content indexing to make more nuanced decisions.
We need to level up the basic keyword searching to something more in-depth:
“Search for most organisations is limited: enterprises are forced to play ‘keyword bingo’, rephrasing their question multiple times until they land on what gets them to their answer. The technologies we’ve been exploring can alleviate this problem by not stopping at capturing the keywords, but by capturing the meaning behind the keywords, labeling the keywords into different categories, entities or types, and linking them together and inferring new relationships.”
In other words, enterprise search needs the addition of semantic search in order to add context to the keywords. A basic keyword search returns every result that matches the keyword phrase, but a context-driven search actually adds intuition behind the keyword phrases. This is really not anything new when it comes to enterprise or any kind of search. Semantic search is context-driven search.
Whitney Grace, July 4, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Enterprise Search Vendor Sinequa Partners with MapR
June 8, 2016
In the world of enterprise search and analytics, everyone wants in on the clients who have flocked to Hadoop for data storage. Virtual Strategy shared an article announcing Sinequa Collaborates With MapR to Power Real-Time Big Data Search and Analytics on Hadoop. A firm specializing in big data, Sinequa, has become certified with the MapR Converged Data Platform. The interoperation of Sinequa’s solutions with MapR will enable actionable information to be gleaned from data stored in Hadoop. We learned,
“By leveraging advanced natural language processing along with universal structured and unstructured data indexing, Sinequa’s platform enables customers to embark on ambitious Big Data projects, achieve critical in-depth content analytics and establish an extremely agile development environment for Search Based Applications (SBA). Global enterprises, including Airbus, AstraZeneca, Atos, Biogen, ENGIE, Total and Siemens have all trusted Sinequa for the guidance and collaboration to harness Big Data to find relevant insight to move business forward.”
Beyond all the enterprise search jargon in this article, the collaboration between Sinequa and MapR appears to offer an upgraded service to customers. As we all know at this point, unstructured data indexing is key to data intake. However, when it comes to output, technological solutions that can support informed business decisions will be unparalleled.
Megan Feil, June 8, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
RAVN ACE Can Help Financial Institutions with Regulatory Compliance
March 31, 2016
Increased regulations in the financial field call for tools that can gather certain information faster and more thoroughly. Bobsguide points to a solution in, “RAVN Systems Releases RAVN ACE for Automated Data Extraction of ISDA Documents Using Artificial Intelligence.” For those who are unaware, ISDA stands for International Swaps and Derivatives Association, and a CSA is a Credit Support Annex. The press release informs us:
“RAVN’s ground-breaking technology, RAVN ACE, joins elements of Artificial Intelligence and information processing to deliver a platform that can read, interpret, extract and summarise content held within ISDA CSAs and other legal documents. It converts unstructured data into structured output, in a fraction of the time it takes a human – and with a higher degree of accuracy. RAVN ACE can extract the structure of the agreement, the clauses and sub-clauses, which can be very useful for subsequent re-negotiation purposes. It then further extracts the key definitions from the contract, including collateral data from tabular formats within the credit support annexes. All this data is made available for input to contract or collateral management and margining systems or can simply be provided as an Excel or XML output for analysis. AVN ACE also provides an in-context review and preview of the extracted terms to allow reviewing teams to further validate the data in the context of the original agreement.”
The write-up tells us the platform can identify high-credit-risk relationships and detail the work required to repaper those accounts (that is, to re-draft, re-sign, and re-process paperwork). It also notes that even organizations that have a handle on their contracts can benefit, because the platform can compare terms in actual documents with those in that have been manually abstracted.
Based in London, enterprise search firm RAVN tailors its solutions to the needs of each industry it serves. The company was founded in 2011.
Cynthia Murrell, March 31, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
A Hefty Guide to Setting up SharePoint 2013 Enterprise Search Center
March 8, 2016
The how-to guide titled Customizing SharePoint 2013 Search Center on Code Project provides a lengthy, detailed explanation (with pictures) of the new features of SharePoint 2013, an integration of the 2010 version and Microsoft FAST search. The article offers insights into certain concepts of the program such as crawled properties and managed properties before introducing step-by-step navigation for customizing the result page and Display template, as well as other areas of Sharepoint. The article includes such tips as this,
“Query rules allow you to modify the users keyword search based on a condition. Let’s say when the user types Developer, we want to retrieve only the books which have BookCategory as Developer and if they type ‘IT Pro’, we only want to retrieve the Administrator related books.”
Nine steps later, you have a neat little result block with the matching items. The article outlines similar processes for Customizing the Search Center, Modifying the Search Center, Adding the Results Page to the Navigation, and Creating the Result Source. This leads us to ask, Shouldn’t this be easier by now? Customizing a program so that it looks and acts the way we expect seems like pretty basic setup, so why does it take 100+ steps to tailor SharePoint 2013?
Chelsea Kerwin, March 8, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Braiding Big Data
October 26, 2015
An apt metaphor to explain big data is the act of braiding. Braiding requires person to take three or more locks of hair and alternating weaving them together. The end result is clean, pretty hairstyle that keeps a person’s hair in place and off the face. Big data is like braiding, because specially tailored software takes an unruly mess of data, including the combed and uncombed strands, and organizes them into a legible format. Perhaps this is why TopQuadrant named its popular big data software TopBraid, read more about its software upgrade in “TopQuadrant Launches TopBraid 5.0.”
TopBraid Suite is an enterprise Web-based solution set that simplifies the development and management of standards-based, model driven solutions focused on taxonomy, ontology, metadata management, reference data governance, and data virtualization. The newest upgrade for TopBraid builds on the current enterprise information management solutions and adds new options:
“ ‘It continues to be our goal to improve ways for users to harness the full potential of their data,’ said Irene Polikoff, CEO and co-founder of TopQuadrant. ‘This latest release of 5.0 includes an exciting new feature, AutoClassifier. While our TopBraid Enterprise Vocabulary Net (EVN) Tagger has let users manually tag content with concepts from their vocabularies for several years, AutoClassifier completely automates that process.’ “
The AutoClassifer makes it easier to add and edit tags before making them a part of the production tag set. Other new features are for TopBraid Enterprise Vocabulary Net (TopBraid EVN), TopBraid Reference Data Manager (RDM), TopBraid Insight, and the TopBraid platform, including improvements in internationalization and a new component for increasing system availability in enterprise environments, TopBraid DataCache.
TopBraid might be the solution an enterprise system needs to braid its data into style.
Whitney Grace, October 26, 2015
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Attivio Does Data Dexterity
October 9, 2015
Enterprise search company Attivio has an interesting post in their Data Dexterity Blog titled “3 Questions for the CEO.” We tend to keep a close eye on industry leader Attivio, and for good reason. In this post, the company’s senior director of product marketing Jane Zupan posed a few questions to her CEO, Stephen Baker, about their role in the enterprise search market. Her first question has Baker explaining his vision for the field’s future, “search-based data discovery”; he states:
“With search-based data discovery, you would simply type a question in your natural language like you do when you perform a search in Google and get an answer. This type of search doesn’t require a visualization tool. So, for example, you could ask a question like ‘tell me what type of weather conditions which exist most of the time when I see a reduction in productivity in my oil wells.’ The answer that comes back, such as ‘snow,’ or ‘sleet,’ gives you insights into how weather patterns affect productivity. Right now, search can’t infer what a question means. They match the words in a query, or keywords, with words in a document. But [research firm] Gartner says that there is an increasing importance for an interface in BI tools that extend BI content creation, analysis and data discovery to non-skilled users. You don’t need to be familiar with the data or be a business analyst or data scientist. You can be anyone and simply ask a question in your words and have the search engine deliver the relevant set of documents.”
Yes, many of us are looking forward to that day. Will Attivio be the first to deliver? The interview goes on to discuss the meaning of the company’s slogan, “the data dexterity company.” Part of the answer involves gaining access to “dark data” buried within organizations’ data silos. Finally, Zupan asks what “sets Attivio apart?” Baker’s answers: the ability to quickly access data from more sources; deriving structure from and analyzing unstructured data; and friendliness to “non-technical” users.
Launched in 2008, Attivio is headquartered in Newton, Massachusetts. Their team includes folks with an advantageous combination of backgrounds: in search, database, and business intelligence companies.
Cynthia Murrell, October 9, 2015
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Where’s the Finish Line Enterprise Search?
September 16, 2015
What never ceases to amaze me is that people are always perplexed when goals for technology change. It always comes with a big hullabaloo and rather than complaining about the changes, time would be better spent learning ways to adapt and learn from the changes. Enterprise search is one of those technology topics that sees slow growth, but when changes occur they are huge. Digital Workplace Group tracks the newest changes in enterprise search, explains why they happened, and how to adapt: “7 Ways The Goal Posts On Enterprise Search Have Moved.”
After spending an inordinate amount of explaining how the author arrived at the seven ways enterprise search has changed, we are finally treated to the bulk of the article. Among the seven reasons are obvious insights that have been discussed in prior articles on Beyond Search, but there are new ideas to ruminate about. Among the obvious are that users want direct answers, they expect search to do more than find information, and understanding a user’s intent. While the obvious insights are already implemented in search engines, enterprise search lags behind.
Enterprise search should work on a more personalized level due it being part of a closed network and how people rely on it to fulfill an immediate need. A social filter could be applied to display a user’s personal data in search results and also users rely on the search filter as a quick shortcut feature. Enterprise search is way behind in taking advantage of search analytics and how users consume and manipulate data.
“To summarize everything above: Search isn’t about search; it’s about finding, connecting, answers, behaviors and productivity. Some of the above changes are already here within enterprises. Some are still just being tested in the consumer space. But all of them point to a new phase in the life of the Internet, intranets, computer technology and the experience of modern, digital work.”
As always there is a lot of room for enterprise search improvement, but these changes need to made for an updated and better work experience.
Whitney Grace, September 16, 2015
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Coveo: A Real Life Search Implementation Success
September 11, 2015
If we detect some serious Coveo cheerleading in this recent article found on RT Insights, that might be because the story originated at that company. Still, “How Real-Time Enterprise Search Helps Seal Financial Deals” does illustrate the advantages of consolidating data resources into a more easily-used system.
The write-up describes challenges faced by London investment firm 3i Group. The global company had been collecting an abundance of data about its clients’ deals, but was spending many worker hours retrieving that information from scattered repositories. Coveo Enterprise Search to the rescue! The platform implementation included a user-friendly UI, actionable analytics, and security measures. The article continues:
“As a result of the implementation, 3i Group reports 90 percent faster access to deal-related intelligence as well as a 20 percent reduction in staff and resources required to respond to compliance requests. 3i Group’s staff members use the platform to search across 3.66 million file share documents, 6.39 million Exchange emails, 897,000 SharePoint documents, and 107 million Enterprise Vault records. For the first time, 3i Group staff members are able to perform a single search across all of the company’s knowledge repositories by using either a browser-based interface or an integrated search interface within SharePoint. 3i Group’s compliance team was provided with a dashboard that enabled them to search and correlate content from across 3i Group’s entire data set, and quickly evaluate permissions and user access rights for every 3i Group record or knowledge asset.”
Founded in 2005, Coveo maintains offices in California and the Netherlands, with its R&D headquarters in Quebec. (The company is also hiring as of this writing.)There is no doubt that being able to reach and analyze all data from one dashboard can be a huge time-saver, especially for a large organization. Just remember that Coveo is but one of several strong options; some are even open source.
Cynthia Murrell, September 11, 2015
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
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