The Pros and Cons of Data Silos When It Comes to Data Analysis and Management
February 22, 2016
The article on Informatica Blog titled Data Silos Are the Death of Analytics. Here’s the Fix explores the often overlooked need for a thorough data management vision and strategy at any competitive business. The article is plugging for an eBook guide to data analytics, but it does go into some detail on the early stages of streamlining the data management approach, summarized by the advice to avoid data silos. The article explains,
“It’s vital to pursue a data management architecture that works across any type of data, BI tool, or storage technology. If the move to add Hadoop or NoSQL demands entirely different tools to manage the data, you’re at risk of creating another silo…When you’ve got different tools for your traditional data warehouse versus your cloud setup, and therefore different skill sets to hire for, train for, and maintain, you’re looking at a real mess.”
The suggestions for streamlined processes and analysis certainly make sense, but the article does not defend the reasonable purposes of data silos, such as power, control, and secrecy. Nor do they consider that in some cases a firm is required to create data silos to comply with a government contract. But it is a nice thought: one big collection of data, one comprehensive data strategy. Maybe.
Chelsea Kerwin, February 22, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Big Data Myths Debunked
December 4, 2015
An abundance of data is not particularly valuable without the ability to draw conclusions from it. Forbes recognizes the value of data analysis in, “Text Analytics Gurus Debunk Four Big Data Myths.” Contributor Barbara Thau observes:
“And while retailers have hailed big data as the key to everything from delivering shoppers personalized merchandise offers to real-time metrics on product performance, the industry is mostly scratching its head on how to monetize all the data that’s being generated in the digital era. One point of departure: Over 80% of all information comes in text format, Tom H.C. Anderson, CEO of, which markets its text analytics software to clients such as Coca-Cola KO +0.00% told Forbes. So if retailers, for one, ‘aren’t using text analytics in their customer listening, whether they know it or not, they’re not doing too much listening at all,’ he said.”
Anderson and his CTO Chris Lehew went on to outline four data myths they’ve identified; mistakes, really: a misplaced trust in survey scores; putting more weight on social media data than direct contact from customers; valuing data from new sources over the customer-service department’s records, and refusing to keep an eye on what the competition is doing. See the article for the reasons these pros disagree with each of these myths.
Text analytics firm OdinText promises to draw a more accurate understanding from their clients’ data collections, whatever industry they are in. The company received their OdenText patent in 2013, and was incorporated earlier this year.
Cynthia Murrell, December 4, 2015
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Data Analytics Is More Than Simple Emotion
November 6, 2015
Hopes and Fears posted the article, “Are You Happy Now? The Uncertain Future Of Emotion Analytics” discusses the possible implications of technology capable of reading emotions. The article opens with a scenario from David Collingridge explaining that the only way to truly gauge technology’s impact is when it has become so ingrained into society that it would be hard to change. Many computing labs are designing software capable of reading emotions using an array of different sensors.
The biggest problem ahead is not how to integrate emotion reading technology into our lives, but what are the ethical concerns associated with it?
Emotion reading technology is also known as affective computing and the possible ethical concerns are more than likely to come from corporation to consumer relationships over consumer-to-consumer relationships. Companies are already able to track a consumer’s spending habits by reading their Internet data and credit cards, then sending targeted ads.
Consumers should be given the option to have their emotions read:
“Affective computing has the potential to intimately affect the inner workings of society and shape individual lives. Access, an international digital rights organization, emphasizes the need for informed consent, and the right for users to choose not to have their data collected. ‘All users should be fully informed about what information a company seeks to collect,’ says Drew Mitnick, Policy Counsel with Access, ‘The invasive nature of emotion analysis means that users should have as much information as possible before being asked to subject [themselves] to it.’”
While the article’s topic touches on fear, it ends on a high note that we should not be afraid of the future of technology. It is important to discuss ethical issues right now, so groundwork will already be in place to handle affective computing.
Whitney Grace, November 6, 2015
NSA Blanket Data Collection Preventing Accurate Surveillance
June 4, 2015
The article on ZDNet titled NSA Is So Overwhelmed with Data, It’s No Longer Effective, Says Whistleblower examines the concept of “bulk data failure” by the NSA and other agencies. William Binney, a whistleblower who has been out of the NSA for over a decade, says that the sheer amount of data the NSA collects leads to oversights and ineffective surveillance. The article states,
“Binney said he estimated that a “maximum” of 72 companies were participating in the bulk records collection program — including Verizon, but said it was a drop in the ocean. He also called PRISM, the clandestine surveillance program that grabs data from nine named Silicon Valley giants, including Apple, Google, Facebook, and Microsoft, just a “minor part” of the data collection process. “The Upstream program is where the vast bulk of the information was being collected,” said Binney.”
It appears that big data presents challenges even when storage, servers, and money are available. Binney blames the data overload for bungles that have led to the Boston bombing and Paris shooting. He believes the NSA had the information needed to prevent the attacks, but couldn’t see the trees for the forest. Smart data collection, rather than mass data collection, is his suggestion to fix this information overload.
Chelsea Kerwin, June 4, 2014
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
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