November 26, 2014
Enterprise Apps Today has an article called “Attensity Boosts Ability To Discover ‘Unknown’ Trends In Data,” discussing how Attensity was updated with new features to detect themes in real-time social data, catch spam, and make it easier to compose/filter queries. Before Attensity’s new software updates, social analytics tools use mentions to measure interest in products. The “mentions” are not the most quantifiable way to see if a product is successful.
The new Attensity Q tracks themes, trends, anomalies, and events around a product in the context of online conversations. This makes it easier to create new vocabularies and brand-unique terms into queries.
” ‘Social analytics has largely been limited up to this point by forming hypotheses and testing them – the hunting and pecking for insights that traditional search requires you to do,” [Senior Project Manager and NLP Strategist Katherine] Matsumoto said. “But there is a growing need for our customers to be presented with findings that they didn’t know to look for. These findings may be within their search topic, adjacent to it or many degrees removed through nested relationships.’ “
Attensity Q has more applications than retail. It can be used for legal departments to detect fraudulent activities and by HR departments to target area for improvement. It could even be used with healthcare patient data to track unusual patterns and offer a better diagnosis.
Rather than bragging about big data’s possibilities, Attensity is describing some practical applications and their uses.
November 24, 2014
Data is messy and needs to be kept clean. Data on a large, enterprise scale is a nightmare to neat freaks, because without an organizational hierarchy it would take years to sift through. Wand Inc.’s corporate blog posted some exciting news, “Expert System And WAND Partner For A More Effective Management Of Enterprise Information.” WAND is known throughout big data as the leader in enterprise taxonomies, while Expert Systems is renowned for its semantic technology.
The goal of the partnership is to help enterprise systems make their data more findable, manage better client relationships, and decrease operational risks. While the partnership will affect enterprise systems overall, there are three main factors that will overhaul the enterprise content management process:
1 “Taxonomy selection: WAND offers the biggest library of out-of-the-box taxonomies available on the market today. By selecting one of the available sector specific taxonomies, customers can speed up significantly their implementation time without compromising their specific classification requirements.
2 Automatic Classification based on the selected taxonomy: once the customer chooses the taxonomy, Expert System makes a full set of tools available to define the semantic based categorization rules and the engine that enables the automatic categorization of all the enterprise content.
3 Native integration with the most common document and collaboration systems, including Microsoft SharePoint.”
WAND and Expert Systems’ combined forces will allow enterprise systems to make their data more findable. While the partnership is beneficial, it reads like most big data relationships. What makes it different, however, are the names attached.
November 21, 2014
SemanticWeb.com posted an article called “Retrieving And Using Taxonomy Data From DBpedia” with an interesting introduction. It explains that DBpedia is a crowd-sourced Internet community whose entire goal is to extract structured information from Wikipedia and share it. The introduction continues that DBpedia already has over three billion facts W3C standard RDF data model ready for application use.
The W3C standards are already written using the SKOS vocabulary, primarily used by the New York Times, the Library of Congress, and other organizations for their own taxonomies and subject headers. Users can extrapolate the data and implement it in their own RDF applications with the goal of giving your data more value.
DBpedia is doing a wonderful service for users so they do not have to rely on proprietary software to deliver them rich taxonomies. The taxonomies can be retrieved under the open source community bylaws and gain instant improvement for content. There is one caveat:
“Remember that, for better or worse, the data is based on Wikipedia data. If you extend the structure of the query above to retrieve lower, more specific levels of horror film categories, you’d probably find the work of film scholars who’ve done serious research as well as the work of nutty people who are a little too into their favorite subgenres.”
Remember Wikipedia is a good reference tool to gain an understanding of a topic, but you still need to check more verifiable resources for hard facts.
November 18, 2014
The article on CNN Money titled Varonis Announces Metadata Framework Version 6, Including New Functionality For Four Varonis Solutions explores the new features of Version 6. Varonis, the leading software provider, focuses on human-generated data that is unstructured and might include anything from spreadsheets to emails to text messages. They can boast over 3,000 customers in fields as varied as healthcare, media and financial services. The Varonis MetaData Framework has been perfected over the last decade. The article describes it this way,
“ [It is ] a single platform on a unifying code base, purpose-built to tackle the many challenges and use cases that arise from the massive volumes of unstructured data files created and stored by organizations of all sizes. Currently powering five distinct Varonis products, the Varonis Metadata Framework intelligently extracts and analyzes metadata from customers’ vast, distributed unstructured data stores, and enables a variety of uses cases, including data governance, data security, archiving, file synchronization, enhanced mobile data accessibility, search, and business collaboration.”
Exciting new features in Version 6 include a search API for DatAnswers, “bi-directional permissions visibility” for DatAdvantage to reduce operational overhead, and reduced risk through DatAlert with the information of malware location and timing.
Chelsea Kerwin, November 18, 2014
November 12, 2014
The article titled The Five Rules for Data Discovery on Computerworld discusses Enterprise Data Discovery. In the pursuit of fast-paced, accurate data analytics, Enterprise Data Discovery is touted in this article as a ramped up tool for accessing relevant information quickly. The first capability is “governed self-service discovery” which enables users to reformulate their data search on their own. This also allows for the blending of data types including social media and unstructured data. The article also emphasizes the importance of having a dialogue with the data,
“You also discovered that the spike in sales occurred in the middle of the media campaign and during the time of the spike, there was a major sporting event. This new clue prompts a new question – what could a sporting event have to do with the spike? Again, the data reveals its value by providing a new answer – one of the advertisements from the campaign got additional play at the event. Now, you have something solid to work on.”
According to the article, Enterprise Data Discovery offers a view of the road less travelled, enabling users to approach their discovery with new questions. Of course, the question that arises while reading this article is, who has time for this? The emphasis on self-service is interesting, but it also suggests that users will be spending a good chunk of time manipulating the data on their own.
Chelsea Kerwin, November 12, 2014
November 10, 2014
Depending on one’s field, it may seem like every bit of information in existence is now just an Internet search away. However, as researchers well know, there is a wealth of potentially crucial information that is still difficult to access. In fact, GCN tells us that marketing firm IDC estimates up to 90 percent of “big data” falls into this category. GCN also turns our attention to a potential solution in, “Brown Dog Digs Into the Deep, Dark Web.”
Brown Dog is a project out of the National Center for Supercomputing Application [NCSA] at the University of Illinois at Urbana-Champaign. In 2013, the team received a $10 million, five-year award from the National Science Foundation for the project. Already, they have developed two services that facilitate access to uncurated data collections. The write-up reports:
“The first, called Data Access Proxy (DAP), transforms unreadable files into readable ones by linking together a series of computing and translational operations behind the scenes. Similar to an Internet gateway, the configuration of the DAP would be entered into a user’s machine settings. Thereafter, data requests over HTTP would first be examined by the proxy to determine if the native file format is readable on the client device.
“The second tool, the Data Tilling Service (DTS), lets individuals search collections of data, using an existing file to discover similar files in the data. For example, while browsing an online image collection, a user could drop an image of three people into the search field, and the DTS would return images in the collection that also contain three people. If the DTS encounters a file format it is unable to parse, it would use the Data Access Proxy to make the file accessible. It also indexes the data and extracts and appends metadata to files to give users a sense of the type of data they are encountering.”
The article notes that Brown Dog’s makers are building on previous software development, and that they hope to “bring together every possible source of automated help already in existence.” That’s some goal! Not surprisingly, the prospective tools have been likened to a time machine of sorts. Kenton McHenry, one of the project’s leaders, reminds us that the world’s first web browser, Mosaic, was also developed at NCSA; his team hopes to leave a similarly significant legacy.
Cynthia Murrell, November 10, 2014
November 5, 2014
Well, this is interesting. The Inquirer reports that the Germans are taking a stand against Google’s practice of consolidating users’ Web-wide data in, “Germany Tells Google to Pause for Permission Before Profiling People.” The Hamburg Data Protection Authority has a particular problem with Google’s one-privacy-policy-fits-all-countries stance. For its part, Google continues to assert that the “simpler, more effective services” it can provide by pulling the threads of our online presences are worth the privacy tradeoff. I’m sure the increased ad revenue is just a nice side-effect.
Reporter Dave Neal quotes Johannes Caspar, the Hamburg commissioner of data protection and freedom:
“On the substantial issue of combining user data across services, Google has not been willing to abide to the legally binding rules and refused to substantially improve the user’s controls. So we had to compel Google to do so by an administrative order. Our requirements aim at a fair balance between the concerns of the company and its users. The issue is up to Google now. The company must treat the data of its millions of users in a way that respects their privacy adequately while they use the various services of the company.”
I suppose we’ll see about that. What will be the next step in the struggle between Google and the world’s privacy advocates?
Cynthia Murrell, November 05, 2014
October 31, 2014
The article on Fortune titled The Company Was In a Death Spiral. She Brought It Back From the Brink lauds the work of Penny Herscher at data analytics firm FirstRain. Herscher took over the company in 2004 after successful work at Cadence Design Systems, Simplex and Texas Instruments. FirstRain was a bankrupt company with a great prototype but no product. Herscher embraced the challenges posed by FirstRain and began her overhaul with a move from New York to California. The article goes on,
“She raised $20 million from new investors and hired a trusted team, including chief operating officer Y.Y. Lee, a mathematician and software engineer… Today, more than 50% of FirstRain’s senior leadership is women. The fledgling company had barely started developing a product when storms began brewing on the horizon. It was 2008. The global economy was beginning to collapse. “The wheels came off the bus,” Herscher says with lament. To survive, the company had to completely change course again…It pulled through.”
But only after major lay-offs and changes in the structure. Today FirstRain customers include IBM and Cisco, and it is only continuing to grow, with new offices in San Mateo. Herscher’s story of success is one of commitment and creative problem-solving.
Chelsea Kerwin, October 31, 2014
October 30, 2014
The information page titled What You Can Do With: Presto on Software AG Products provides an overview of the data-combining software formerly known as JackBe until its acquisition by Software AG. JackBe is now Presto! (Exclamation point optional.) Information flow since March 2014 has been modest. The article offers an overview and some of the capabilities of the software, such as in-memory analytics and visualization and data mashing. The article states,
“Presto combines data from any source for data visualizations. Accessing the original data—directly from data warehouses, news feeds, social media, existing BI systems, streaming big data, even Excel spreadsheets—lets business users respond to changing conditions as they happen. Presto’s “point-click-connect” assembly tool, Wires, makes it easy to bring together and manipulate data from multiple existing systems into meaningful data visualizations. Simple, powerful data mashing means IT and power users can create new apps and dashboards in hours—even minutes…”
Software AG began in 1969 in Germany and in 2013 acquired JackBe. According to the Company History page, the deal was actually awarded the title of Strategic M&A deal of the Year by the Association for Corporate Growth. Other acquisitions include Apama Complex Event Processing Platform, alfabet AG, and Longjump.
Chelsea Kerwin, October 30, 2014
October 28, 2014
Partnerships offer companies ways to improve their product quality and create new ones. Semantic Web reports that “Expert System And WAND Partner For A More Effective Management Of Enterprise Information.” Expert System is a leading semantic technology company and WAND is known for its enterprise taxonomies. Their new partnership will allow businesses to have a better and more accurate way to organize data.
Each company brings unique features to the partnership:
“The combination of the strengths of each company, on one side WAND’s unique expertise in the development of enterprise taxonomies and Expert System’s Cogito on the other side with its unique capability to analyze written text based on the comprehension of the meaning of each word, not only ensures the highest quality possible, but also opens up the opportunity to tackle the complexity of enterprise information management. With this new joint offer, companies will finally have full support for a faster and flexible information management process and immediate access to strategic information.”
Enterprise management teams are going to get excited about how Expert System and WAND will improve taxonomy selection and have more native integration with in-place data systems. One of the ways the two will combine their strengths is with the new automatic classification: when a WAND taxonomy is selecting, Expert System brings in its semantic based categorization rules and an engine for automatic categorization.