Need Data Integration? Think of Cisco. Well, Okay

November 25, 2016

Data integration is more difficult than some of the text analytics’ wizards state. Software sucks in disparate data and “real time” analytics systems present actionable results to marketers, sales professionals, and chief strategy officers. Well, that’s not exactly accurate.

Industrial strength data integration demands a company which has bought a company which acquired a technology which performs data integration. Cisco offers a system that appears to combine the functions of Kapow with the capabilities of Palantir Technologies’ Gotham and tosses in the self service business information which Microsoft touts.

Cisco acquired Composite Information in 2013. Cisco now offers the Composite system as the Cisco Information Server. Here’s what the block diagram of the federating behemoth looks like. You can get a PDF version at this link.


The system is easy to use. “The graphical development and management environments are easy to learn and intuitive to use,” says the Cisco Teradata information sheet. For some tips about the easy to use system check out the Data Virtualization Cisco Information Server blog. A tutorial, although dated is, at this link. Note that the block diagram between 2011 and the one presented above has not significantly changed. I assume there is not much work required to ingest and make sense of the Twitter stream or other social media content.
The blog has one post and was last updated in 2011. But there is a YouTube video at this link.

The system includes a remarkable range of features; for example:

  • Modeling which means import and transform what Cisco calls “introspect”, create a model and figure out how to make it run at an acceptable level of performance, and expose the data to other services. (Does this sound like iPhrase’s and Teratext’s method? It does to me.)
  • Search
  • Transformation
  • Version control and governance
  • Data quality control and assurance
  • Outputs
  • Security
  • Administrative controls.

The time required to create this system is, according to Cisco Teradata, is “over 300 man years.”

The licensee can plug the system into an IBM DB2 running on a z/OS8 “handheld”. You will need a large hand by the way. No small hands need apply.

Stephen E Arnold, November 25, 2016

Genetics Are Biased

November 4, 2016

DNA does not lie. DNA does not lie if conducted accurately and by an experienced geneticist.  Right now it is popular for people to get their DNA tested to discover where their ancestors came from.  Many testers are surprised when they receive their results, because they learn their ancestors came from unexpected places.  Black Americans are eager to learn about the genetics, due to their slave ancestry and lack of familial records.  For many Black Americans, DNA is the only way they can learn where their roots originated, but Africa is not entirely cataloged.

According to Science Daily’s article “Major Racial Bias Found In Leading Genomics Database,” if you have African ancestry and get a DNA test it will be difficult to pinpoint your results.  The two largest genomics databases that geneticists refer to contain a measurable bias to European genes.  From a logical standpoint, this is understandable as Africa has the largest genetic diversity and remains a developing continent without the best access to scientific advances.  These provide challenges for geneticists as they try to solve the African genetic puzzle.

It also weighs heavily on black Americans, because they are missing a significant component in their genetic make-up they can reveal vital health information.  Most black Americans today contain a percentage of European ancestry.  While the European side of their DNA can be traced, their African heritage is more likely to yield clouded results.  On a financial scale, it is more expensive to test black Americans genetics due to the lack of information and the results are still not going to be as accurate as a European genome.

This groundbreaking research by Dr. O’Connor and his team clearly underscores the need for greater diversity in today’s genomic databases,’ says UM SOM Dean E. Albert Reece, MD, PhD, MBA, who is also Vice President of Medical Affairs at the University of Maryland and the John Z. and Akiko Bowers Distinguished Professor at UM SOM. ‘By applying the genetic ancestry data of all major racial backgrounds, we can perform more precise and cost-effective clinical diagnoses that benefit patients and physicians alike.

While Africa is a large continent, the Human Genome Project and other genetic organizations should apply for grants that would fund a trip to Africa.  Geneticists and biologists would then canvas Africa, collect cheek swabs from willing populations, return with the DNA to sequence, and add to the database.  Would it be expensive?  Yes, but it would advance medical knowledge and reveal more information about human history.  After all, we all originate from Mother Africa.

Whitney Grace, November 4, 2016
Sponsored by, publisher of the CyberOSINT monograph

NTechLab as David to the Google Goliath of Facial Recognition

October 27, 2016

The article titled A Russian Startup is Beating Google with Eerily Accurate Facial Recognition Technology on Business Insider positions NTechLab as the company leading the industry in facial recognition technology. In 2015, the startup beat Google to win the “MegaFace” competition. The article explains,

NTechLab sets itself apart from its competitors with its high level of accuracy and its ability to search an extensive database of photographs. At the MegaFace Championship, NTechLab achieved a 73 percent accuracy with a database of 1 million pictures. When the number dropped to 10,000 images, the system achieved a jaw-dropping accuracy of 95 percent. “We are the first to learn how to efficiently handle large picture databases,” said NTechLab founder Artem Kukharenko to Intel iQ.

The startup based its technology in deep learning and a neural network. The company has held several public demonstrations at festivals and amusement parks. Attendees share selfies with the system, then receive pictures of themselves when the system “found” them in the crowd. Kukharenko touts the “real-word” problem-solving capabilities of his system. While there isn’t a great deal of substantive backup to his claims, the company is certainly worth keeping an eye on.

Chelsea Kerwin, October 27, 2016
Sponsored by, publisher of the CyberOSINT monograph

Data Silos: Here to Stay

October 20, 2016

Data silos have become a permanent part of the landscape. Even if data reside in a cloud, some data are okay for certain people to access. Other data are off limits. Whether the data silo is a result of access controls or because an enthusiastic marketer has a one off storage device in his or her cubbies’ desk drawer, we have silos.

I read “Battling Data Silos: 3 Tips to Finance and Operations Integration.” This is a very good example of providing advice which is impossible to implement. If I were to use the three precepts in an engagement, I have a hunch that a barrel of tar and some goose feathers will be next to my horse and buggy.

What are the “tips”? Here you go.

  1. Conduct a data discovery audit.
  2. Develop a plan
  3. And my fave “Realize the value of the cloud for high performance and scalability.”

Here we go, gentle reader.

The cost of a data discovery audit can be high. The cost of the time, effort, and lost productivity mean that most data audits are limp wash rags. Few folks in an organization know what data are where, who manages those data, and the limits placed on the data. Figuring out the answers to these questions in a company with 25 people is tough. Try to do it for a government agency with dozens of locations and hundreds of staff and contractors. Automated audits can be a help, but there may be unforeseen consequences of sniffing who has what. The likelihood of a high value data discovery audit without considerable preparation, budgeting, and planning is zero. Most data audits like software audits never reach the finish line without a trip to the emergency room.

The notion of a plan for consolidating data is okay. Folks love meetings with coffee and food. A plan allows a professional to demonstrate that work has been accomplished. The challenge, of course, is to implement the plan. That’s another kettle of fish entirely. MBA think does not deliver much progress toward eliminating silos which proliferate like tweets about zombies.

The third point is value. Yep, value. What is value? I don’t know. Cloud value can be demonstrated for specific situations. But the thought of migrating data to a cloud and then making sure that no regulatory, legal, or common sense problems have been avoided is a work in progress. Data management, content controls, and security tasks nudge cloud functions toward one approach: Yet another data silo.

Yep, YADS. Three breezy notions crater due to the gravitational pull of segmented content repositories under the control of folks who absolutely love silos.

Stephen E Arnold, October 20, 2016

Recent Developments in Deep Learning Architecture from AlexNet to ResNet

September 27, 2016

The article on GitHub titled The 9 Deep Learning Papers You Need To Know About (Understanding CNNs Part 3) is not an article about the global media giant but rather the advancements in computer vision and convolutional neural networks (CNNs). The article frames its discussion around the ImageNet Large-Scale Recognition Challenges (ILSVRC), what it terms the “annual Olympics of computer vision…where teams compete to see who has the best computer vision model for tasks such as classification, localization, detection and more.” The article explains that the 2012 winners and their network (AlexNet) revolutionized the field.

This was the first time a model performed so well on a historically difficult ImageNet dataset. Utilizing techniques that are still used today, such as data augmentation and dropout, this paper really illustrated the benefits of CNNs and backed them up with record breaking performance in the competition.

In 2013, CNNs flooded in, and ZF Net was the winner with an error rate of 11.2% (down from AlexNet’s 15.4%.) Prior to AlexNet though, the lowest error rate was 26.2%. The article also discusses other progress in general network architecture including VGG Net, which emphasized depth and simplicity of CNNs necessary to hierarchical data representation, and GoogLeNet, which tossed the deep and simple rule out of the window and paved the way for future creative structuring using the Inception model.

Chelsea Kerwin, September 27, 2016
Sponsored by, publisher of the CyberOSINT monograph
There is a Louisville, Kentucky Hidden Web/Dark Web meet up on September 27, 2016.
Information is at this link:

In-Q-Tel Wants Less Latency, Fewer Humans, and Smarter Dashboards

September 15, 2016

I read “The CIA Just Invested in a Hot Startup That Makes Sense of Big Data.” I love the “just.” In-Q-Tel investments are not like bumping into a friend in Penn Station. Zoomdata, founded in 2012, has been making calls, raising venture funding (more than $45 million in four rounds from 21 investors), and staffing up to about 100 full time equivalents. With its headquarters in Reston, Virginia, the company is not exactly operating from a log cabin west of Paducah, Kentucky.

The write up explains:

Zoom Data uses something called Data Sharpening technology to deliver visual analytics from real-time or historical data. Instead of a user searching through an Excel file or creating a pivot table, Zoom Data puts what’s important into a custom dashboard so users can see what they need to know immediately.

What Zoomdata does is offer hope to its customers for less human fiddling with data and faster outputs of actionable intelligence. If you recall how IBM i2 and Palantir Gotham work, humans are needed. IBM even snagged Palantir’s jargon of AI for “augmented intelligence.”

In-Q-Tel wants more smart software with less dependence on expensive, hard to train, and often careless humans. When incoming rounds hit near a mobile operations center, it is possible to lose one’s train of thought.

Zoomdata has some Booz, Allen DNA, some MIT RNA, and protein from other essential chemicals.

The write up mentions Palantir, but does not make explicit the need to reduce t6o some degree the human-centric approaches which are part of the major systems’ core architecture. You have nifty cloud stuff, but you have less nifty humans in most mission critical work processes.

To speed up the outputs, software should be the answer. An investment in Zoomdata delivers three messages to me here in rural Kentucky:

  1. In-Q-Tel continues to look for ways to move along the “less wait and less weight” requirement of those involved in operations. “Weight” refers to heavy, old-fashioned system. “Wait” refers to the latency imposed by manual processes.
  2. Zoomdata and other investments whips to the flanks of the BAE Systems, IBMs, and Palantirs chasing government contracts. The investment focuses attention not on scope changes but on figuring out how to deal with the unacceptable complexity and latency of many existing systems.
  3. In-Q-Tel has upped the value of Zoomdata. With consolidation in the commercial intelligence business rolling along at NASCAR speeds, it won’t take long before Zoomdata finds itself going to big company meetings to learn what the true costs of being acquired are.

For more information about Zoomdata, check out the paid-for reports at this link.

Stephen E Arnold, September 15, 2016

SAP In Memory: Conflicts of Opinion

September 13, 2016

I was surprised by the information presented in “SAP Hana Implementation Pattern Research Yields Contradictory Results.” My goodness, I thought, an online publication actually presents some ideas that a high profile system may not be a cat fully dressed in pajamas.

The SAP Hana system is a database. The difference between Hana and the dozens of other allegedly next generation data management solutions is its “in memory, columnar database platform.” If you are not hip to the lingo of the database administrators who clutch many organizations by the throat, an in memory approach is faster than trucking back to a storage device. Think back to the 1990s and Eric Brewer or the teens who rolled out Pinpoint.

The columnar angle is that data is presented in stacks with each item written on a note card. The mapping of the data is different from a row type system. The primary key in a columnar structure is the data, which maps back to the the row identification.

The aforementioned article points to a mid tier consulting firm report. That report by an outfit called Nucleus Research. Nucleus, according to the article, “revealed that 60 percent of SAP reference customers – mostly in the US – would not buy SAP technology again.” I understand that SAP engenders some excitement among its customers, but a mid tier consulting firm seems to be demonstrating considerable bravery if the data are accurate. Many mid tier consulting firms sand the rough edges off their reports.

The article then jumps to a report paid for by an SAP reseller, which obviously has a dog in the Nucleus fight. Another mid tier research outfit called Coleman Parks was hired to do another study. The research focused on 250 Hana license holders.

The results are interesting. I learned from the write up:

When asked what claims for Hana were credible, 92% of respondents said it reduced IT infrastructure costs, a further 87% stated it saved business costs. Some 98% of Hana projects came in on-budget, and 65% yet to roll out were confident of hitting budget.

Yep, happy campers who are using the system for online transactional processing and online analytical processing. No at home chefs tucking away their favorite recipes in Hana I surmise.

However, the report allegedly determined what I have known for more than a decade:

SAP technology is often deemed too complex, and its CEO Bill McDermott has been waging a public war against this complexity for the past few years, using the mantra Run Simple.

The rebuttal study identified another plus for Hana:

“We were surprised how satisfied the Hana license holders were. SAP has done a good job in making sure these projects work, and rate at which has got Hana out is amazing for such a large organization,” said Centiq director of technology and services Robin Webster. “We had heard a lot about Hana as shelfware, so we were surprised at the number saying they were live.”

From our Hana free environment in rural Kentucky, we think:

  1. Mid tier consulting firms often output contradictory findings when reviewing products or conducting research. If there is bias in algorithms, imagine what might luck in the research team members’ approaches
  2. High profile outfits like SAP can convince some of the folks with dogs in the fight to get involved in proving that good things come to those who have more research conducted
  3. Open source data management systems are plentiful. Big outfits like Hewlett Packard, IBM, and Oracle find themselves trying to generate the type of revenue associated with proprietary, closed data management products at a time when fresh faced computer science graduates just love free in memory solutions like Memsql and similar solutions.

SAP mounted an open source initiative which I learned about in “SAP Embraces Open Source Sort Of.” But the real message for me is that one can get mid tier research firms to do reports. Then one can pick the one that best presents a happy face to potential licensees.

Here in Harrod’s Creek, the high tech crowd tests software before writing checks. No consultants required.

Stephen E Arnold, September 13, 2016

The Decline of Free Software As a Failure of Leadership and Relevance

August 18, 2016

The article on Datamation titled 7 Reasons Why Free Software Is Losing Influence investigates some of the causes for the major slowdown in FOSS (free and open software software). The article lays much of the blame at the feet of the leader of the Free Software Foundation (FSF), Richard Stallman. In spite of his major contributions to the free software movement, he is prickly and occasionally drops Joe Biden-esque gaffes detrimental to his cause. He also has an issue when it comes to sticking to his message and making his cause relevant. The article explains,

“Over the last few years, Richard Stallman has denounced cloud computinge-bookscell phones in general, and Android in particular. In each case, Stallman has raised issues of privacy and consumer rights that others all too often fail to mention. The trouble is, going on to ignore these new technologies solves nothing, and makes the free software movement more irrelevant in people’s lives. Many people are attracted to new technologies, and others are forced to use them because others are.”

In addition to Stallman’s difficult personality, which only accounts for a small part of the decline in the FSF’s influence, the article also has other suggestions. Perhaps most importantly, the FSF is a tiny company without the resources to achieve its numerous goals like sponsoring the GNU Project, promoting social activism, and running campaigns against DRM and Windows.

Chelsea Kerwin, August 18, 2016

Sponsored by, publisher of the CyberOSINT monograph

There is a Louisville, Kentucky Hidden /Dark Web meet up on August 23, 2016.
Information is at this link:


Salesforce Blackout

July 27, 2016 is a cloud computing company with the majority of its profits coming from customer relationship management and acquiring commercial social networking apps.  According to PC World, Salesforce recently had a blackout and the details were told in: “Salesforce Outage Continues In Some Parts Of The US.”  In early May, Salesforce was down for over twelve hours due to a file integrity issue in the NA14 database.

The outage occurred in the morning with limited services restored later in the evening. Salesforce divides its customers into instances.  The NA14 instance is located in North America as many of the customers who complained via Twitter are located in the US.

The exact details were:

“The database failure happened after “a successful site switch” of the NA14 instance “to resolve a service disruption that occurred between 00:47 to 02:39 UTC on May 10, 2016 due to a failure in the power distribution in the primary data center,” the company said.  Later on Tuesday, Salesforce continued to report that users were still unable to access the service. It said it did not believe “at this point” that it would be able to repair the file integrity issue. Instead, it had shifted its focus to recovering from a prior backup, which had not been affected by the file integrity issues.”

It is to be expected that power outages like this would happen and they will reoccur in the future.  Technology is only as reliable as the best circuit breaker and electricity flows.  This is why it is recommended to back up your files in more than one place.


Whitney Grace, July 27, 2016
Sponsored by, publisher of the CyberOSINT monograph

Meet the Company Selling Our Medical Data

July 22, 2016

A company with a long history is getting fresh scrutiny. An article at Fortune reports, “This Little-Known Firm Is Getting Rich Off Your Medical Data.” Writer Adam Tanner informs us:

“A global company based in Danbury, Connecticut, IMS  buys bulk data from pharmacy chains such as CVS , doctor’s electronic record systems such as Allscripts, claims from insurers such as Blue Cross Blue Shield and from others who handle your health information. The data is anonymized—stripped from the identifiers that identify individuals. In turn, IMS sells insights from its more than half a billion patient dossiers mainly to drug companies.

“So-called health care data mining is a growing market—and one largely dominated by IMS. Last week, the company reported 2015 net income of $417 million on revenue of $2.9 billion, compared with a loss of $189 million in 2014 (an acquisition also boosted revenue over the year). ‘The outlook for this business remains strong,’ CEO Ari Bousbib said in announcing the earnings.”

IMS Health dates back to the 1950s, when a medical ad man sought to make a buck on drug-sales marketing reports. In the 1980s and ‘90s, the company thrived selling profiles of specific doctors’ proscribing patterns to pharmaceutical marketing folks. Later, they moved into aggregating information on individual patients—anonymized, of course, in accordance with HIPAA rules.

Despite those rules, some are concerned about patient privacy. IMS does not disclose how it compiles their patient dossiers, and it may be possible that records could, somehow someday, become identifiable. One solution would be to allow patients to opt out of contributing their records to the collection, anonymized or not, as marketing data firm Acxiom began doing in 2013.

Of course, it isn’t quite so simple for the consumer. Each health record system makes its own decisions about data sharing, so opting out could require changing doctors. On the other hand, many of us have little choice in our insurance provider, and a lot of those firms also share patient information. Will IMS move toward transparency, or continue to keep patients in the dark about the paths of their own medical data?


Cynthia Murrell, July 22, 2016

Sponsored by, publisher of the CyberOSINT monograph

There is a Louisville, Kentucky Hidden Web/Dark
Web meet up on July 26, 2016.
Information is at this link:

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