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Bold idea for 'big data': Researchers take aim at data glut with customized optical network

Bold idea for 'big data': Researchers take aim at data glut with customized optical network | Data Nerd's Corner | Scoop.it
Computer networking researchers at Rice University have a new idea for how to handle the mountains of data piling up in the labs of their fellow scientists around campus: Create a customized, energy-efficient optical network that can feed rivers of...
Carla Gentry CSPO's insight:

Rice's Ken Kennedy Institute for Information Technology helped facilitate the BOLD collaboration as part of its efforts to address ongoing challenges in computational science. Rice Information Technology's Networking, Telecommunications and Data Center group and the Rice IT Research Computing Support Group will help develop and support the BOLD network

Read more at: http://phys.org/news/2013-09-bold-idea-big-aim-glut.html#jCp

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Big Data, IOT and Security - OH MY!

Big Data, IOT and Security - OH MY! | Data Nerd's Corner | Scoop.it
Why should I – as a data scientist or analyst be worried about security, that’s not really part of my job is it? Well if you are a consultant or own your own business it is! Say, you download secure data from your clients and then YOU get hacked, guess who is liable if sensitive information is leaked or gets into the wrong hands? What if you develop a platform where the client’s customers can log in and check their accounts, credit card info and purchase histories are stored on this system, if stolen, it can set you up for a lawsuit. If you are a corporation, you are protected in some extents but what if you operate as a sole proprietor – you could lose your home, company and reputation. Still think security when dealing with big data isn’t important?
Carla Gentry CSPO's insight:
Organizations need to get better at protecting themselves and discovering that they’ve been breached plus we, the consultants, need to do a better job of protecting our own data and that means you can’t use password as a password! Let’s not make it easy for the hackers and let’s be sure that when we collect sensitive data and yes, even the data collected from cool technology toys connected to the internet, that we are security minded, meaning check your statements, logs and security messages - verify everything! When building your database, use all the security features available (masking, obfuscation, encryption) so that if someone does gain access, what they steal is NOT usable!
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Obama Tours Boise State University - 3D Printing Industry

President Barack Obama’s been doing some traveling, as presidents are wont to do. Before heading to more exotic or turbulent locales, President Obama hit up the quaint town of Boise, Idaho, taking a trip to Boise State University’s College of Engineering, where the school has recently opened its Product Development Lab. And what’s key to product development these days? You guessed it! 3D printing!
Carla Gentry CSPO's insight:

As a joint effort between the University’s College of Engineering and College of Business and Economics, the new lab pairs student employees with local members of industry to co-develop a wide range of designs and products. In this process, mechanical engineering students are able to use 3D printing technologies to prototype and produce items, many of which will actually head to market.

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Can virtual reality revolutionise market research?

Can virtual reality revolutionise market research? | Data Nerd's Corner | Scoop.it
Last year Facebook purchased Oculus Rift for a reported $2 billion - before the product had even gone to market - signalling the excitement virtual reality headsets are generating. Yet beyond gaming, market research is also set for a technological overhaul - with virtual worlds helping researchers overcome many of the pitfalls of traditional, survey-based analysis.
Carla Gentry CSPO's insight:

You can see, in a virtual reality experience, a near real-world," Sackman says. "This solves a lot of problems with survey-based research.

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@data_nerd: A Badge of Courage

@data_nerd: A Badge of Courage | Data Nerd's Corner | Scoop.it
As the owner/founder of Analytical Solution, I am a data nerd. Here’s my backstory: I entered the University of Tennessee at Chattanooga in the spring of 1993. I was a single mother of two sons, but I was eager to pursue my degree and take the next step (I certainly don’t like to back down from a challenge). There, I excelled at math and gained more exposure to advanced mathematics. During my entire tenure at UTC, I worked in the Developmental Math Lab assisting students with all levels of mathematics. In 1998, I graduated with a double major (Applied Mathematics and Economics), and moved on to start my career in analytics in Chicago.
Carla Gentry CSPO's insight:

Today, I act as a liaison between IT departments and Executive staff by deciphering business needs via large, complicated databases; I come back to their teams with intelligence that quantifies spending, profit, and trends. Over the last 17 years, I have worked with Fortune 100 and 500 companies, such as Discover Financial Services, J&J, Hershey, Kraft, Kellogg’s, SCJ, McNeil and Firestone.

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Edward Snowden Wins 'Debate' With NSA Lawyer

Edward Snowden Wins 'Debate' With NSA Lawyer | Data Nerd's Corner | Scoop.it
Unfortunately, Snowden—in this case—didn’t take the bait and responded by pointing out the financial cost of the NSA’s actions in terms of the damage to the business of American high-tech corporations. Showing the photo of the NSA tapping into a Cisco router, he said: “this has a real cost, not just legally, not just morally, not just ethically, but financially.”
Carla Gentry CSPO's insight:

In his Wired interview with James Bamford, however, Snowden was quite eloquent about the moral and ethical costs (referencing Arendt’s Eichmann in Jerusalem: A Report on the Banality of Evil) and how a “culture of impunity” has developed at the NSA and other parts of our government:

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The Big Data Mistake In The Internet Of Things

The Big Data Mistake In The Internet Of Things | Data Nerd's Corner | Scoop.it
Event responses and machine behavior is all very well when it comes to new post-millennial products with their petabytes of sensor-generated data. But if we look more closely into the deeply unsexy world of predictive maintenance on industrial equipment, we will have to contend with massive files that are typically buried and inaccessible after years of being shuffled around by the IT department.
Carla Gentry CSPO's insight:

CEO of data management startup Peaxy is Manuel Terranova. The former GE Oil & Gas division CIO reminds us that, “No one will deny that telemetry data generated by embedded sensors has opened doors to a new universe of innovation. However, few realize that for Global 1,000 manufacturers to make the Industrial Internet a reality, engineering teams need to be able to compare this data the equipment’s original geometry schematics drawings and simulations, files that might have been generated as far back as the 1970s or ‘80s — it is not uncommon for industrial machinery to have a 30 year-plus lifecycle.”

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A quick look at data science

A quick look at data science | Data Nerd's Corner | Scoop.it
So what happens once a data scientist has had their way with data? Well, a number of things happen. A biblically verbose report could be written and sent around, which in turn could perhaps precipitate changes in the way a business operates. Taking the Netflix example once again, the service now encourages users to fill their wish-list and has a more comprehensive trial service.
Carla Gentry CSPO's insight:

So what about the skills required? After leafing about monster.co.uk, looking at job vacancies and noting the requirements, I collated the profiles of the ideal Data Scientist and Business Intelligence specialist. These are summarised in the Venn diagram below. Of course, this kind of analysis is not entirely accurate – after all, an advertised vacancy is not always an accurate representation of the underlying job.

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Data And Commerce Elope, Birth Unicorns

Data And Commerce Elope, Birth Unicorns | Data Nerd's Corner | Scoop.it
But do customers trust them to use that data to the customers’ benefit? Creepy factor eliminated? It depends. Customers expect Credit Karma to serve up better offers because that was the founding expectation of the relationship. But with Facebook, that was not and is not the case. Facebook has a great model for built-in data, but will always struggle with customer trust.
Carla Gentry CSPO's insight:

Amazon and eBay had to become unicorns before they had enough customer data to pull off predictive targeting. Now, companies like Facebook, LinkedIn, Credit Karma and Square are getting in the data game, too, using a core offer, where meaningful, kick-ass data is inherent to create sticky user bases.

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Expert Picks: Uncovering What Big Data Is Really All About

Expert Picks: Uncovering What Big Data Is Really All About | Data Nerd's Corner | Scoop.it
Get your bearings with this “great introduction to Big Data,” Marr says. “It’s a nice selection of visual slides that help to put Big Data into context and highlight the importance of Big Data for business and society. It starts simply by defining Big Data and then illustrating how ‘big’ Big Data really is.”
Carla Gentry CSPO's insight:

In this deck by Marr, he breaks down data into its simplest terms. “I give examples of the different types of data we can now collect and analyze, and then provide practical real-world examples of how Big Data is being used by companies today to turn data into value,” he says. Whether it’s for better understanding your customers, optimizing your business processes or improving our cities, health, sports performance or even national security, this deck covers it all.

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Facebook Data Scientists: Who Are They and What Do They Do?

Facebook Data Scientists: Who Are They and What Do They Do? | Data Nerd's Corner | Scoop.it
Ooyala data scientist, Matt Pasienski, says his job requires proficiency with a myriad of visualization tools and with processing data using programs like MySQL, Hadoop and STORM. He stresses that data scientists must understand the business and marketing side of business, as well as the technology side. If a company cannot afford to hire someone to ask key questions about their data, they can use software instead. Metamarkets founder, Mike Driscoll, describes a data scientist as “a person who can take big data, analyze it, and tell stories from the data.”
Carla Gentry CSPO's insight:

Finding people with such a broad bag of skills, and having the budget to pay them, is often a challenge for smaller start-ups, especially as data scientists generally work in teams. LinkedIn’s teams consist of five people while Facebook originally had a team of twelve. Big Data companies like Tableau and Metamarkets provide software and services that fill the data scientist niche. These companies provide dashboards that allow business analysts and company executives to analyze their own data, without the need for such deep technical skills.

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Analytics: The sideways approach to PR measurement

Analytics: The sideways approach to PR measurement | Data Nerd's Corner | Scoop.it
Measuring PR is complicated

The problem with these posts is that they’re trying to address a nuanced subject head-on (also that they are often written by people who don’t actually understand what PR is, or how to approach it strategically).

If you look at how practitioners in the real world are getting smart about measuring PR, you start to realize that they’re not meeting it head on. Instead, they’re taking an almost sideways approach to it.

Sidling up to measurement, as opposed to greeting it with scales in hand, allows us to think about why we engage in PR in the first place. There are business problems we are trying to solve through our work.

Analytics are at the heart of this approach.
Carla Gentry CSPO's insight:

Sideways analytics

Consider this recent case study (well, it’s not a case study yet, but it is recent work), which I discussed with Rebekah Iliff over at the AirPR blog:

We recently wrapped a project with a client in the education space; they were launching a new online offering. Registrations were the ultimate goal, and they were using campaign tracking in Google Analytics very well. What we did was to ensure the creation of tracking links to the relevant page, so that we could attribute visits and conversions from our efforts—our strategy had a mix of earned, owned, and paid media—as accurately as possible.

Based on traffic and conversion trends, we could see what worked (social and paid) and what didn’t so much (focusing on location too narrowly as opposed to niche and interest). That allowed us to pivot our strategy midway through the campaign and put more muscle behind what was working as opposed to what wasn’t…and ultimately reach the goal.

 
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A New Think Tank on Data and Society Is Off to a Great Start, Thanks to Heavy-Weight Backers - Science Research | Grants | Fundraising - Inside Philanthropy

A New Think Tank on Data and Society Is Off to a Great Start, Thanks to Heavy-Weight Backers - Science Research | Grants | Fundraising - Inside Philanthropy | Data Nerd's Corner | Scoop.it
The Data & Society Research Institute is a new, “think/do” tank based in N...
Carla Gentry CSPO's insight:

The institute was founded by Danah Boyd, a scholar and Microsoft researcher whose work in recent years has focused on young people and social media. Boyd is one of those rare Ph.D.s who can write in plain English, and she's authored two books that have received significant attention, most recently It's Complicated: The Social Lives of Networked Teens (2014). She's also long been involved in nonprofits and describes herself on her website as "both an activist and a scholar."

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Big data tops humans at picking 'significant' films: study

Big data tops humans at picking 'significant' films: study | Data Nerd's Corner | Scoop.it
NEW YORK (Reuters) - In the escalating battle of big data vs. human experts, score another win for numbers.The most accurate predictions of which movies the U.S.
Carla Gentry CSPO's insight:

The most accurate predictions of which movies the U.S. Library of Congress will deem "culturally, historically, or aesthetically significant" are not the views of critics or fans but a simple algorithm applied to a database, according to a study published on Monday.

The crucial data, scientists reported in Proceedings of the National Academy of Sciences, are what the Internet Movie Database (IMDb.com) calls "Connections" - films, television episodes and other works that allude to an earlier movie.

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Just four bits of credit card data can identify most anyone (Update)

Just four bits of credit card data can identify most anyone (Update) | Data Nerd's Corner | Scoop.it
The data set the researchers analyzed included the names and locations of the shops at which purchases took place, the days on which they took place, and the purchase amounts. Purchases made with the same credit card were all tagged with the same random identification number
Carla Gentry CSPO's insight:

For each identification number—each customer in the data set—the researchers selected purchases at random, then determined how many other customers' purchase histories contained the same data points. In separate analyses, the researchers varied the number of data points per customer from two to five. Without price information, two data points were still sufficient to identify more than 40 percent of the people in the data set. At the other extreme, five points with price information was enough to identify almost everyone.

Read more at: http://phys.org/news/2015-01-anonymous-credit-card-isnt.html#jCp

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How Microsoft Could Implement A Hybrid Embrace Of R

How Microsoft Could Implement A Hybrid Embrace Of R | Data Nerd's Corner | Scoop.it
Smith is an technology and open source sophisticate. He should know that creating a run time for an open source technology, something that I pointed out TIBCO Software has already done, does not make the project “closed” or no longer open source. Revolution Analytics offers its own version of R that includes enhancements that are not open source. But the R project remains open.
Carla Gentry CSPO's insight:

I spoke with Smith today and he disagrees that the GPL gets in the way of full integration of R into Microsoft’s ecosystem. “You can call out to R from anywhere you like. R was indeed created to be an embeddable way to use data science and statistics,” Smith said.

 

In one of my next stories on this topic, I will examine the process of calling R from Excel and other environments and examine how dramatically having a run-time would alter the experience.

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CSI Computer Science: Your coding style can give you away

CSI Computer Science: Your coding style can give you away | Data Nerd's Corner | Scoop.it
If you’ve been programming for any length of time, no doubt you’ve developed your own coding style. Every developer has preferences not only for things like spacing (e.g,, spaces vs tabs), naming styles (e.g., CamelCase vs. snake_case) and commenting, but also how he or she implements certain types of functionality. New research now shows that a developer’s coding style is a type of fingerprint, which can be used to identify who wrote an anonymous piece of code with a high degree of accuracy.
Carla Gentry CSPO's insight:

Researchers from Drexel University, the University of Maryland,the University of Goettingen, and Princeton have developed a “code stylometry,” which uses natural language processing and machine learning to determine the authors of source code based on coding style. Their findings, which were recently published in the paper “De-anonymizing Programmers via Code Stylometry,” could be applicable to a wide of range of situations where determining the true author of a piece of code is important. For example, it could be used to help identify the author of malicious source code and to help resolve plagiarism and copyright disputes.

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Can Hadoop Replace a Data Warehouse? -- TDWI

Can Hadoop Replace a Data Warehouse? -- TDWI | Data Nerd's Corner | Scoop.it
I personally don't believe Hadoop can replace a relational database management system, much less a relational data warehouse. [However,] I do believe we can reduce our footprint on expensive relational databases by migrating some data to Hadoop. That would make our data warehouse platform more affordable and free up capacity for growth, which in turn makes it look more valuable from an economic perspective.
Carla Gentry CSPO's insight:

Before I'm convinced that a data warehouse is really a warehouse, I look for certain data structures, namely multidimensional data, time series, aggregates, and lots of calculated values that don't exist in source systems. In my experience, many so-called warehouses are better described as a mart, operational data store, archive, or simply a generic database. I freely admit that making distinctions among these data models is akin to hair splitting.

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Yahoo sets Alibaba stake spinoff plan, shares jump

Yahoo sets Alibaba stake spinoff plan, shares jump | Data Nerd's Corner | Scoop.it
Yahoo Inc (YHOO.O) plans to spin off its 15 percent stake in China's Alibaba Group Holding Ltd (BABA.N), responding to pressure to hand over to shareholders its prized e-commerce investment valued at roughly $40 billion.
Carla Gentry CSPO's insight:

Shares of Yahoo rose about 7 percent to $51.45 in after-hours trading on Tuesday, following the tax-free spinoff announcement and earnings which just beat analysts forecasts even as its revenues slightly lagged estimates.

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Rivo Partners with AQITC to Strengthen Middle East Presence

Rivo Partners with AQITC to Strengthen Middle East Presence | Data Nerd's Corner | Scoop.it
STRATFORD, CT & HOUSTON, TX (PRWEB) January 19, 2015 Rivo, the market leading cloud based risk & performance management platform provider for leading brands around the world has announced its partnership with the American Qatari International Trade Company (AQITC) to establish a presence in the Middle East. This partnership marks a major step for the …
Carla Gentry CSPO's insight:

Headquartered in Doha, Qatar, AQITC is ideally placed to deliver their highly sought-after service: linking local organizations with international suppliers based on their specific business requirements. Rivo, who provide solutions to many recognized global organisations within high-risk sectors such as oil & gas, construction, engineering and logistics, is an ideal provider for the region. AQITC and Rivo will synergize their existing market strengths and capabilities, to help large organizations automate their ERM or EH&S systems with Rivo’s proven SaaS solutions.

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Newest Top Big Data Influencer

Newest Top Big Data Influencer | Data Nerd's Corner | Scoop.it
Though each year I’m invited to speak on text mining at about 20 industry events, and for years now I have manages two of the most popular analytics related groups on LinkedIn (Next Gen Market Research, and Data and Text Analytics Professionals - each with thousands of members), and I and my team at Anderson Analytics deal with BigData issues on behalf of Fortune 500 Clients on a daily basis, this is not something that Klout, PeerIndex or any other influence ranking system can capture.
Carla Gentry CSPO's insight:

Don’t get me wrong, I think Klout may have great value for marketers running a campaign trying to interact with hundreds or thousands of influencers in certain areas, but I don’t think it was ever really meant to be taken seriously at the individual/non-aggregate level. In other words, those Twitter Lists you see on blogs Ranking experts in various areas, take them with an extreme grain of salt!

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Innovation Outlook for 2015: Tackling Big Data Variety | Xconomy

Innovation Outlook for 2015: Tackling Big Data Variety | Xconomy | Data Nerd's Corner | Scoop.it
Companies have invested roughly $3-4 trillion on enterprise software over the last 20 years, with Gartner forecasting $320 billion in 2014 alone. A lot of that investment has gone into single systems and applications—from Oracle and SAP to proprietary enterprise resource planning and product lifecycle management systems to (more recently) Hadoop and Hive. The good news: organizations are sitting on vast reserves of diverse, potentially invaluable corporate data. The bad news: they can’t get at a lot of the value because it’s locked in data silos tied to these systems, applications, organizations, individuals, or all of the above.
Carla Gentry CSPO's insight:

Welcome to the world of Big Data Variety. Organizations now want to use this data broadly—along with all external data sources—for analytic applications. But most organizations don’t even know what they have—data sources, entities, and attributes—let alone how to get them to work together at scale to power new insights and discover long-tail business opportunities.

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12 Stats from around the #Digital World

12 Stats from around the #Digital World | Data Nerd's Corner | Scoop.it
Stat’s just the way it is. Some things will never change.

Via Eric_Determined / Eric Silverstein
Carla Gentry CSPO's insight:

Although the stats may change, the determination to bring you the very best insight will remain forever undaunted. 

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Eric_Determined / Eric Silverstein's curator insight, January 23, 10:36 PM

It's always great to end the week with a recap around #digital #marketing and #ecommerce world.


It's all about #Mobile - good #infographics


It includes one non-marketing stat from Canada, guess what it's about :)

Bharat Employment's curator insight, January 26, 11:35 PM
www.bharatemployment.com
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How To Test Drive Big Data Analytics

How To Test Drive Big Data Analytics | Data Nerd's Corner | Scoop.it
If we can accept the contention that big data analytics testing is not easy, then we can drill down to ask why exactly this job and procedure is so hard to execute in real world workplaces.
Carla Gentry CSPO's insight:
It is still comparatively early days for both Hadoop and for big data analytics, so it’s not unfair to suggest that firms will often exhibit a lack of the required levels of in-house testing infrastructure required to execute big data projects.
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The role of big data in financial inclusion

The role of big data in financial inclusion | Data Nerd's Corner | Scoop.it

Relevance and personalisation are delivered by data-driven insights; this is one of the new truths of business. As a mathematician and statistician this appeals to my inner geek; I enjoy numbers, patterns and formulas. For many years it wasn’t a “cool” thing to admit but now in the 21st century the geeks have inherited the earth and technology has penetrated every part of our lives. Thanks to the ubiquity of technology those same numbers, patterns and formulas that I learnt to love are opening new doors and delivering data insights that are changing the face of business and commerce.

Carla Gentry CSPO's insight:

Patterns and predictions can influence every part of our lives. What particularly interests me is how insights can deliver impact and influence in real world applications. I see the power of data every day, because we use it to inform our own business decisions at MasterCard. We use it as a route to identify areas for growth, address concerns, to understand our audiences and to drive social good on a global scale.

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Big data initiatives not quite delivering yet, survey shows | ZDNet

Big data initiatives not quite delivering yet, survey shows | ZDNet | Data Nerd's Corner | Scoop.it
A new survey of 226 executives surfaced some interesting results pertaining to big data adoption.

For starters, there's some notable progress with cloud. The survey report states that "only" 36 percent of global organizations use cloud-based big data and analytics platforms. Actually, 36 percent seems like a remarkable uptake of cloud-based data analytics, considering the fact that most analytics vendors have only just begin to start moving their clients to the cloud-based configurations.
Carla Gentry CSPO's insight:

The benefits have not materialized, either. In the survey, only 27 percent of respondents described their big data initiatives as "successful," and only eight percent described them as "very successful" In fact, organizations were found to be struggling even with their proof-of-concept projects, with an average success rate of only 38 percent.

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The Big Data Analytics Warehouse and Digital Data Models - SemAngel

The Big Data Analytics Warehouse and Digital Data Models - SemAngel | Data Nerd's Corner | Scoop.it
People have struggled to do anything useful with most big data sources. And while those sources do have lots of volume, and sometimes have lots of variety and velocity, these are not the root cause of our struggles. Analysts can, and have, handled cases of too much volume in their data with the simple but perfectly acceptable expedient of sampling.  Variety – a multiplicity of data sources – always creates integration challenges. But it doesn’t take a data scientist or a new technology to join data if you’ve done a credible job creating keys. And without keys, no big data system in the world does any better at putting data together. There are, it’s true, some advantages to systems that do late binding of data definitions when you’ve got lots of data sources. But this point would hardly justify new technologies and gains much of its apparent force from a confusion of production systems and analytics sandboxes. Give me a SQL-Server instance where I have complete control over the schema, I can add and drop tables at will, and load whatever data I want, and the practical difference between early and late binding of fields and business rules shrinks considerably. As to velocity, one can test the efficacy of this simply by asking whether the analysis and the data actually need to be done in real-time.  Real-time does present many unique challenges to both technology and analytic method. But the overwhelming number of big data systems I see no more address real-time than did their traditional predecessors. Batch is batch.
Carla Gentry CSPO's insight:

So if the size of data, the variety of data and the velocity of data aren’t really that interesting (I’m not even going to waste time with the absurd idea that data quality is somehow materially worse than it used to be), it would be tempting to think that big data is just hype. That isn’t my view.

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