How Data Science Pervades
May 2, 2017
We think Information Management may be overstating a bit with the headline, “Data Science Underlies Everything the Enterprise Now Does.” While perhaps not underpinning quite “everything,” the use of data analysis has indeed spread throughout many companies (especially larger ones).
Writer Michael O’Connell cites a few key developments over the last year alone, including the rise of representative data, a wider adoption of predictive analysis, and the refinement of customer analytics. He predicts, even more, changes in the coming year, then uses a hypothetical telecom company for a series of examples. He concludes:
You’ll note that this model represents a significant broadening beyond traditional big data/analytics functions. Such task alignment and comprehensive integration of analytics functions into specific business operations enable high-value digital applications ranging far beyond our sample Telco’s churn mitigation — cross-selling, predictive and condition-based maintenance, fraud detection, price optimization, and logistics management are just a few areas where data science is making a huge difference to the bottom line.
See the article for more on the process of turning data into action, as illustrated with the tale of that imaginary telecom’s data-wrangling adventure.
Cynthia Murrell, May 2, 2017
Enterprise Search and a Chimera: Analytical Engines
May 1, 2017
I put on my steam punk outfit before reading “Leading Analytical Engines for Enterprise Search.” Now there was one small factual error; specifically, the Google Search Appliance is a goner. When it was alive and tended to by authorized partners, it was not particularly adept at doing “analytical engine” type things.
What about the rest of the article? Well, I found it amusing.
Let me get to the good stuff and then deal with the nasty reality which confronts the folks who continue to pump money into enterprise search.
What companies does this “real journalism” out identify as purveyors of high top shoes for search. Yikes, sorry. I meant to say enterprise search systems which do analytical engine things.
Here’s the line up:
The Google Search Appliance. As noted, this is a goner. Yep, the Google threw in the towel. Lots of reasons, but my sources say, cost of sales was a consideration. Oh, and there were a couple of Google FTEs plus assorted costs for dealing with those annoyed with the product’s performance, relevance, customization, etc. Anyway. Museum piece.
Microsoft SharePoint. I find this a side splitter. Microsoft SharePoint is many things. In fact, armed with Visual Studio one can actually make the system work in a useful manner. Don’t tell the HR folks who wonder why certified SharePoint experts chew up a chunk of the budget and “fast.” Insider joke. Yeah, Excel is the go to analysis tool no matter what others may say. The challenge is to get the Excel thing to interact in a speedy, useful way with whatever the SharePoint administrator has managed to get working in a reliable way. Nuff said.
Coveo. Interesting addition to the list because Coveo is doing the free search thing, the Salesforce thing, the enterprise search thing, the customer support thing, and I think a bunch of other things. The Canadian outfit wants to do more than surf on government inducements, investors’ trust and money, and a key word based system. So it’s analytical engine time. I am not sure how the wrappers required to make key word search do analytics help out performance, but the company says it is an “analytical engine.” So be it.
Attivio. This is an interesting addition. The company emerged from some “fast” movers and shakers. The baseball data demo was nifty about six years ago. Now the company does search, publishing, analytics, etc. The shift from search to analytical engine is somewhat credible. The challenge the company faces is closing deals and generating sustainable revenue. There is that thing called “open source”. A clever programmer can integrate Lucene (Elasticsearch), use its open source components, and maybe dabble with Ikanow. The result? Perhaps an Attivio killer? Who knows.
Lucidworks (Really?). Yep, this is the Avis to the Hertz in the open source commercial sector. Lucidworks (Really?) is now just about everything sort of associated with Big Data, search, smart software, etc. The clear Lucid problem is Shay Bannon and Elastic. Not only does Elastic have more venture money, Elastic has more deployments and, based on information available to me, more revenue, partners, and clout in the open source world. Lucidworks (Really?) has a track record of executive and founder turnover and the thrill of watching Amazon benefit from a former Lucid employee’s inputs. Exciting. Really?
So what do I think of this article in CIO Review? Two things:
- It is not too helpful to me and those looking for search solutions in Harrod’s Creek, Kentucky. The reason? The GSA error and gasping effort to make key word search into something hot and cool. “Analytical engines” does not rev my motor. In fact, it does not turn over.
- CIO Review does not want me to copy a quote from the write up. Tip to CIO Review. Anyone can copy wildly crazy analytical engines article by viewing source and copying the somewhat uninteresting content.
Stephen E Arnold, May 1, 2017
Semantic Platform Aggregates Scientific Information
May 1, 2017
A new scientific repository is now available from a prominent publisher, we learn from “GraphDB, Leading Semantic Database from Ontotext, Powers Springer Nature’s New Linked Open Data Platform” at PRWeb. (We note the word “leading” in the title; who verifies this assertion? Just curious.) The platform, dubbed SciGraph, aggregates data from Springer Nature and its academic partners. The press release specifies:
Thanks to semantic technologies, Linked Open Data and the GraphDB semantic database, all these data are connected in a way which semantically describes and visualizes how the information is interlinked. GraphDB’s capability to seamlessly integrate disparate data silos allows Springer Nature SciGraph to comprise metadata from journals and articles, books and chapters, organizations, institutions, funders, research grants, patents, clinical trials, substances, conference series, events, citations and reference networks, Altmetrics, and links to research datasets.
The dataset is released under a certain international creative commons license, and can be downloaded (by someone with the appropriate technical knowledge) here.
An early explorer of semantic technology, Ontotext was founded in 2000. Based in Bulgaria, the company keeps their North American office in New Jersey. Ontotext’s client roster includes big names in publishing, government agencies, and cultural institutions.
Cynthia Murrell, May 1, 2017
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