Big Data: O(log n) Again to Calculating Bad Presentations and Lousy Management
May 26, 2013
I participated in a quite interesting Big Data “event” recently. (Sorry, no link. I want to leave my post adrift in the sea of saucisson which makes up the Internet today.)
Big Data as a concept has been with us as long as there are people and storage. If a stack of clay tablets would not fit in a cabinet in ancient Babylon, the hapless analyst had a Big Data problem. When I had a Wang mini in my closet, Big Data was anything larger than 80 megabytes.
In my view, Big Data is a bit of a marketing confection. When companies cannot sell their core product like enterprise search, these outfits just tell the sales and marketing consultants to whip something up. Big Data is in my view one popular junk food when processed by some folks.
Let me set the stage.
A self appointed “expert” tried to organize a two-day lecture series to explain the basics of Big Data to those seeking information about this hot concept. The line up of teachers included marketers who took an interesting intellectual approach and me, the addled goose.
Now shift gears and think in terms of airline food. You are hungry on a flight from New York to Paris and the airline serves up a stale cracker and a substance which, from a distance, looks like cheese. Once up close, the combination did not deliver haute cuisine. Heck, the Big Data event was not the equivalent of meals ready to eat or MREs left in the equatorial sun for a couple of weeks in an undisclosed location.
The aftermath of Chernobyl event captured my impression of how misinformation about Big Data can set the stage for flawed decisions and catastrophic financial issues. Those emergency systems sure worked well in the engineering models, didn’t they? A happy quack to http://goo.gl/5u2E3.
Three impressions struck me as I reflected on the two-day event I attended with two of my colleagues. (More about my two colleagues in a good news moment.)
First, the self-aggrandizing poobah who was the “maestro of Big Data” left about mid way through Day Two. I am familiar with “experts” and azure chip consultants who have more pressing business than sticking with something to it completion. I was reminded of the behavior of the Costa Concordia captain. Was this disappearing act an indication of disorganization or craw fishing from failure? The steady attrition of paying attendees was evident by the third talk on the first day of the seminar. In fact, on Day One, Hour One, I counted 58 people in a room which was set to handle about 120. When the “maestro of Big Data” flew the coop, there were 15 people in the room. My talk, the end note for the event, pulled 30 people, up from the low of 15 at 2 pm on Day Two. Who introduced me? No one. Who stepped in to handle the last two hours of the event? My team, thank you.
Second, in my opinion, the majority of the speakers’ presentations were like most of the content on Slideshare, a business marketing service owned by LinkedIn, a job hunting service. (I think some of the speakers are denizens of LinkedIn, which I find quite amusing.) In my opinion, the Slideshare approach business information for many “members” is to take familiar, well-worn buzzwords. Then add a couple of trendy Hacker News references. Transfer recycled information to PowerPoint slides. And then serve up cold. I learned a great deal about SAP and how wonderful the company is for just about anything Big Data. I tuned out after the sixth or seventh worshipful reference. Although addled, I pick up on stuff once I hear the same old refrain three or four times. If you are interested in what was not covered in the seminar lectures, navigate to “What does O(log n) mean exactly?” I included one diagram with information about Big O, but marketers in my lecture lapsed into a coma when I mentioned the concept.
Third, I learned from several of the attendees that the Big Data sessions did not meet their expectations. I did deliver a lecture, and I had 30 people in the audience, not counting my two colleagues. I am not sure where these folks came from. We let them in the lecture hall because the organizer’s staff had wandered off to do more important tasks I assume. And, then — surprise, surprise — after my talk, five individuals clustered around me. Two of my colleagues witnessed the clump of groupies. I was hoping for major press coverage and maybe a Project Runway designer as fans. Instead, I got five — I am still in shock — mathematicians. The key comment witnessed by two experienced special librarians was, “You were the only speaker who told me how to think about Big Data problems. Very good.” I am not much of a thinker. I was not sure whether the adoring PhD from Rutgers was pulling my leg or speaking about the dismal quality of the other folks who were doing the Slideshare marketing thing. I was pleased with the feedback.
And, most importantly, I want to thank my two colleagues, Constance Ard, an honest to goodness, straight shooting law librarian, and Delores Meglio, once a New York Times’ executive who also worked with me at Ziff and who was was part of the senior management team at Elsevier Knovel, for:
- Stepping in when the “maestro” of the event disappeared because he had more pressing business than witnessing the sinking of his Titanic event. The event organizer’s staff apparently had to beat the commute rush home
- Facilitating the question and answer period which lasted a full 20 minutes after my lecture ended at 5 pm Eastern
- Chasing down an audio visual person to turn on the microphone and turn on the projection device. Apparently the show organizer’s team had better things to do that watch one speaker after another drive people from the room. I do not know if any paying customers were crying, but I would not rule anything out.
Will I reveal who organized this event? Nope.
Will I write a memo to the organizer, offering helpful suggestions to the organizer? Nope.
Will I point out which speakers scored a perfect 10 on the Slideshare airline food quality scale? Nope.
Why not?
I was thrilled to experience once again how people on my team deliver even when it is not their job.
Believe me when I say I was proud of Constance Ard’s and Delores Meglio’s spontaneous action. They made the last two hours of the Big Data event a success for the remaining attendees.
Did I tell Constance and Delores to step in? Nope.
Like others on my team of 30 people, Ms. Ard and Ms. Meglio are old-school professionals. Both believed that those in the Big Data lecture hall deserved 100 percent attention and effort. I was able to focus on making my talk the best it could be.
Could I have done a better job? Sure. Did I try my to do my best? Yes. I delivered despite the unprofessional setting in which I was placed.
Perhaps conference organizers and Big Data maestros could learn something about commitment and initiative by talking with people like Constance Ard and Delores Meglio, and ignoring the marketers who promise and, in my opinion, frequently fail to deliver?
Shift to another event commitment I had that same day, right after the Big Data lecture.l
In sharp contrast was the Startupalooza sponsored by iBreakfast event at John Jay College of Criminal Justice. I was asked to evaluate 15 start up ideas over a period of three hours. I want to point out that the Startupalooza event was organized, dynamic, professional, and exciting.
The reason?
The iBreakfast team and the 43 participants and five evaluators, were engaged. The innovators pitching start up ideas responded to the professionalism of the event and stepped up their game.
For me, the difference between the two events was as clear as choking down an MRE and chowing down at Le Bernadin.
Oh, what about my presentation and work at Startupalooze?
Those groupie mathematicians thought my talk was pretty good. What do math people know anyway? But I had three entrepreneurs clump around me after Startupalooza. Constance Ard extracted me because I continued to deliver at the 100 percent even though I was burning will power to keep going at 9 pm after my Big Data lecture.
My hope is that those younger than me try hard, do a professional job, and stick with commitments. My team performs in this manner. Will others follow Startupalooza’s, Ms. Ard’s, and Ms. Meglio’s example?
I sure hope so. Events succeed for many reasons. Professionalism is just one element and may, in some situations, be the catalyst for rising above mediocrity.
Stephen E Arnold, May 26, 2013
Sponsored by Augmentext
The Mythical Man-Month by Fred Brooks Still Holds Vital Insights
May 2, 2013
An article in The Observer titled Why Big IT Projects Always Go Wrong explores the impact of computer scientist Fred Brooks’ seminal book from 1975, The Mythical Man-Month. The book, comprised of essays on how to manage large software projects, is based on the lessons Brooks gleaned from his time at IBM producing OS/360 operating system. The project dragged on endlessly with IBM simply throwing more programmers at the problem, which Brooks eventually realized only added to the delays in finishing. This is due to the types of work involved in big software projects: the writing of computer code and the co-ordination of the work of all of the programmers. The more programmers, the more effort to co-ordinate. The article discusses evidence supporting Brook’s claim,
“Oxford researchers examined more than 1,400 big IT projects – comparing their budgets and estimated performance benefits with the actual costs and results. The average project cost $167m and the largest a whopping $33bn. The researchers’ sample drew heavily on US-based projects but found little difference between them and European projects. Likewise, they found little difference between private companies and public agencies. One in six had a cost overrun of 200%. The message is clear: if you run a big company or a government department and are contemplating a big IT product, ask yourself this question: can your company or your ministerial career survive if the project goes over budget by 40% or more, or if only 25-50% of the projected benefits are realised? If the answer is “no” go back to square one. And read Fred Brooks’ lovely book.”
The article cites one disastrous example in Levi Strauss’s attempt in 2003 to streamline its IT system with the aid of a team of consultants from Deloitte. Ultimately Levi Strauss was forced to close its three distribution centers in the US for a week, along with taking a charge against earnings of $192.5 million in 2008. Obviously while Brooks’ book has influenced the field of managing software projects, it has not become mainstream knowledge.
Chelsea Kerwin, May 02, 2013
Sponsored by ArnoldIT.com, developer of Augmentext
Thomson Reuters: The Pointy End of a Business Sector
March 28, 2013
Thomson Reuters has been a leader in professional publishing for many years. I lost track of the company after the management shake up which accompanied the departure of Michael Brown and some other top executives. Truth be told I was involved in work for the US government, and it was new, exciting, and relevant. My work for publishing companies trying to surf the digital revolution reminded me of my part time job air hammering slag at Keystone Steel & Wire Company.
I read “Data Don’t Add Up for Thomson Reuters.” (This online link can go dead or to a pay wall without warning, and I don’t have an easy way to update links in this free blog. So, there you go.) You can find the story in the printed version of the newspaper or online if you have a subscription. The printed version appears on page C-10, March 28, 2013 edition.
The main point is that Thomson Reuters has not been able to grow organically by selling more information to professionals or by buying promising companies and surfing on surging revenue streams. This is an important point, and I will return to it in a moment. The Wall Street Journal story said:
Shares of Thomson Reuters remain 13% below where they were when the deal closed in April 2008, partly reflecting difficulty integrating two large, international companies.
The article runs though other challenges which range from Bloomberg to Dow Jones, from ProQuest to LexisNexis. The article is short, so the list of challenges has been truncated to a handful of big names.
Do the professional publishing companies have access to talent on a par with Julius Caesar’s capabilities? In my opinion, without management of exceptional skill, professional publishing companies will be sucked through the rip in the fabric of credibility which Thomson Reuters’ pointed spear has created: Flat earnings, more wrenching cost cutting, and products which confuse customers and do not increase revenue and profits. Image from Wikipedia Vercingetorix write up.
But let’s set aside Thomson Reuters. I want to look at the Thomson Reuters’ situation as the pointy end of a spear. The idea is that Thomson Reuters has worked hard for 20 or 30 years to be the best managed, smartest, and most technologically adept company in the professional publishing sector. With hundreds of brands and almost total saturation of certain markets like trademark and patent information, legal information, and data for wheeler dealers—Thomson Reuters has been trying hard, very hard, to make the right moves. Is time running out?
Like the professional publishing sector which includes outfits as diverse as Cambridge Scientific Abstracts, Ebsco Electronic Publishing, Elsevier, and Wolters Kluwers to name a few outfits with hundreds of millions in revenue. Each of these companies share some components:
- Information is “must have” as opposed nice to have
- Information is for-fee, not free
- Customer segments are not spending in the way the analysts predicted
- Deals have not delivered significant new revenue
- Management shifts replace executives with similar, snap in type people. Innovative and disruptive folks find themselves sitting alone at company meetings.
Android, Rubin, and the Google Management Circle
March 20, 2013
I read “Disconnect: Why Andy Rubin and Android Called It Quits.” I think the write up tells a great story. A human is an android. Now the human wants to turn his android talents to robots. A movie in the making.
I also noted this quote which I assume is spot on:
“I love working with Andy because he’s brilliant at setting big goals for the seemingly impossible – and then mobilizing small teams to achieve them,” Urs Hölzle, senior vice president of infrastructure at Google, said in a statement to The Verge. “He’s a great talent, very inspiring. I’m not sure anyone else could have made Android happen.” But Rubin was unwilling or unable to make big industry partnerships that could turn Android into a moneymaker for Google. While Samsung got rich off shipping phones built on Android, Google’s brand faded into the background and its influence was chipped away. “Andy is a solo artist who likes to run in a direction and ignore everyone else,” says one mobile industry executive who’s worked with Rubin. “When Android grew to a certain size and required interaction, collaboration and partnership both inside and outside of Google, he became frustrated and incapable of managing the business. Android has outgrown Andy and honestly, I don’t think he knows where to take it next.”
I read this with some interest because there are three issues bubbling under the surface of these snappy sentences.
First, Google has a management mafia. Some folks fit in; others do not. The ones who do not get an opportunity to find their future with robots or Yahoo. There are some similarities in the challenges too.
Second, the folks moving to the “consolidation” and “monetization” phase of Google’s game plan are not too keen on coming in second. Whether the threat is Apple or Samsung, some zip is needed. Zeal is good. Antipathy toward certain business practices can be helpful as well. Note that these skills do not require “mobile sensitivity.”
Third, the controlled chaos of Google is now becoming a fascinating feudal system. There are workers and their are leaders. Then there are the inner circle of managers who have one mission: keep those revenues going up. The inner circle, in my opinion, is triggering the hiring of “older stars” like certain university researchers and buying companies for “talent.” The idea is easy for me to understand. The existing workers are not able to make the leaps required to pump up those numbers, curtail escalating costs, and knock down pesky competitors.
Just my viewpoint. Quack.
Stephen E Arnold, March 20, 2013
IntelTrax Summary: November 2 to November 8
November 12, 2012
This week the IntelTrax advanced intelligence blog published some excellent article summaries regarding big data’s growing impact on the globalized workplace.
“Big Data Talent Pool Grows” explains how job seekers are embracing the big data analytics profession due to the fact that it welcomes new talent.
The article states:
“The just-released InformationWeek 2012 State of IT Staffing Survey reveals that 40% of those who cite big data and analytics as a top hiring priority say they’ll increase staffing in these areas by 11% or more during the next two years. At the same time, 53% of these companies say it will be hard to find big-data-savvy analytics experts. Respondents expect to try a mix of retraining of existing people, hiring of new employees and contracting of consultants and temporary employees to fill the gap.
Practitioners, vendors, and educators we spoke to for our Big Data IT Staffing report offer seven tips for finding the right talent.”
The article, “The Healthcare Analytics Trickle Down” shows how the pairing of healthcare and data analytics is starting to pay off for many companies and its starting to trickle down.
The article states:
“If you’re old enough to remember the Reagan administration, you remember the politically charged expression “trickle-down economics,” which referred to the theory that if you provide benefits and incentives to businesses and the wealthy, those benefits would trickle down to wage earners at lower socioeconomic levels.
In some ways, big data analytics is like trickle-down economics. Only the biggest healthcare providers with the deepest pockets can afford the kind of analytics platforms required to get useful intelligence from tens of thousands of patient records. But in theory, those benefits will trickle down to smaller providers that either don’t have the financial support or the large patient populations to do this type of data crunching on their own.”
We all knew that big data was something worth investing in, but save the world? that seems to be a little bit much. “50 Ways Big Data Can Save the World” showcases the new startup Bidgely, which aims to turn every appliance in your home into a data scientist, providing you with real time results on your energy usage.
The article states:
“Utilities worldwide are installing smart meters on homes and businesses, which means there could be as much as 50 terabytes of energy data that can emerge from a million or so homes in a year. The problem has been that there haven’t been very many ways to make good use of all this data to benefit the average consumer. But a startup called Bidgely, which raised a series A round from Khosla Ventures, says it has created algorithms that can dig into real-time smart meter energy-consumption data, can reduce consumers’ home energy use by between 4 percent to 12 percent, and can also deliver other beneficial home services to consumers.”
Whether you are looking to utilize big data to protect the environment, save lives, or boost business for your company, there are solutions available that can be very beneficial. Thanks to companies like Digital Reasoning, this technology is more affordable, accessible and customizable than ever.
Jasmine Ashton, November 12, 2012
Sponsored by ArnoldIT.com, developer of Augmentext
IntelTrax Summary: October 26 to November 1
November 5, 2012
The IntelTrax information intelligence blog posted some excellent articles this week discussing the importance of investing in data analysis technology to help improve the efficiency of workplaces.
“Big Data a Big Part of IT Spending” looks at some projections regarding the rate of IT spending growth, most of which went towards social media campaign spending. However, the spending is continuing to branch out as more and more industries are beginning to utilize the technology.
The article states:
“Big data this year will account for US$28 billion of IT spending worldwide, which will increase to US$34 billion in 2013, according to Gartner.
In a report released Wednesday, the market research firm said much of 2012 expenditure will be in adapting traditional tools to address issues related to the big data phenomenon such as machine data, social data, and the large variety and velocity of data. In contrast, only US$4.3 billion will be focused on new big data functionalities.”
As big data analytics becomes more mainstream, we are seeing more interesting ways that it is being utilized. “Big Data Justice League” examines the use of big data analytics to predict the criminal behavior of maritime pirates.
The article states:
“There are almost too many sources of unstructured data to grapple with: interviews with pirates in custody, news stories about piracy incidents, data from mobile phones found during investigations, e-mail traffic, and social media posts from the pirates themselves. And here’s where the story gets really interesting, in my opinion. Most of this data comes from disparate sources that can vex the best investigations. It’s not simply a matter of easily formatted spreadsheets with clean rows and columns. At warp speed, data comes in from the Web, mobile devices, PDF files and other documents — a potential treasure trove of hidden insights.”
Some companies that a new to the big data game take a little bit of time to see the return on their investment. “Data Scientists More Important Than Most Think” gives four major detractors to analytics success:
“1. 35% of the time, it is the missing analytics skills – For analysts – how well are they able to bridge the gap to business, to understand the real question behind the ask before they jump into the data pull? For PM’s and marketing managers – how well do they understand the recipe behind making decisions based on data (BADIR framework), how well familiar they are with the fundamental analytics technique?
2. 10% of the time, it is the missing decision making process – How does budget get allocated? What is the process of laying out product roadmap?
3. 25% of the time, it is the organization’s data maturity – how easy is to get to data, how many version of the truth exist, does data exist in its rawest form for everybody to aggregate as they please?
4. 30% of the time, it the management and leadership – how is the management making decision, how are they establishing roles and responsibility, how are they holding people accountable?”
Regardless of your industry or expertise in the data analysis field, Digital Reasoning can be of great help. It offers one of the best analytics platforms on the market and can get your house in order by using automated understanding for big data.
Jasmine Ashton, November 5, 2012
Sponsored by ArnoldIT.com, developer of Augmentext
Third Party ERP Resources Need Proven Search Application
October 22, 2012
The article highlights that companies should weigh the options:
“Third-party ERP support is probably not a good choice for companies that consider it important to have access to a vendor’s current version, patches and updates, Scavo says. However, ‘I think there are plenty of examples of companies that have gone off maintenance and at some point in the future decided to come back to the vendor for an upgrade. It’s very hard to imagine a situation where the vendor will not take that customer’s business back,’ he says. Doing so might save you money.”
Autonomy Releases Policy Management Solution
October 4, 2012
A new solution for policy management has been launched by HP’s Autonomy, according to the article “New Autonomy Solution Helps Automate Policy Management” on Compliance Week. The product, HP TRIM 7.3, integrates Autonomy ControlPoint with records management to allow organizations to automatically apply policy based on meaning to structured as well as unstructured data. This release will give companies the power to understand and make use of the concepts and ideas within their data.
We learn more about the features in the article:
“The new features of HP TRIM 7.3 and Autonomy ControlPoint 3.0 are built on Autonomy’s Intelligent Data Operating Layer (IDOL) platform, which allow organizations to identify the location and compliance status of their information assets, and then apply the correct organizational policy. The policy includes security, storage, and retention settings for each asset. This enables organizations to achieve a new level of governance by removing the significant burden of traditional manual approaches.”
The solution also allows customers to identify, classify, and manage business records and mitigate risk by applying policy to content across multiple repositories. As Big Data overwhelms, businesses would be wise to employ such an effective data management solution. More information about TRIM can be found here.
Andrea Hayden, October 04, 2012
Sponsored by ArnoldIT.com, developer of Augmentext.
Intel Trax Top Stories September 20 to September 27
October 1, 2012
This week the IntelTrax advanced intelligence blog published a series of articles that explained the importance of integrating analytics solutions to increase performance efficiency within the workplace.
Big data can be quite confusing. That is why it is always great to listen to the opinions of experts in the field. “John Whittaker on the Need for Data Integration for Big Data Analytics” explains why successful big data analytics requires integrating data from a multitude of sources.
When explaining why big data integration is necessary, Whittaker said:
“One of the big aspects that people are trying to get a handle right now, and one of our major uses, is big data analytics. Once you get beyond the Google or Facebook use cases and start talking about how the rest of us will use big data, it is going to be analytics. Whenever you’re doing analytics, you want to marry information from different sources. You might want to be able to correlate what’s happening within your ERP and the operational data that might exist there, with experiential data from your website. The operational data often tends to reside in relational databases, but when you’re talking about experiential data, about how people are utilizing your website or what people are saying on social media about you, that sort of data resides within the unstructured big data world of Hadoop. It’s really about being able to marry these sources together into one environment and drive better decisions based on the information there is the primary value that the big data environment is going to provide for the normal enterprise.”
Along with integrating big data, many experts are also making predictions regarding the future of big data. “Predicting the Next Big Thing in Big Data” talks about some of the new up in comes in the industry that may make a big impact.
When explaining a new report that has come out, the article states:
“Big Data – The Next Big Thing”, a first-of-its-kind report on the ‘Big Data’ industry, focusing on the opportunities, challenges, and its impact on businesses globally. ‘Big Data’ relates to rapidly growing, structured and unstructured datasets with sizes beyond the ability of conventional database tools to store, manage, and analyze them.
The report identifies five key insights on global ‘Big Data’ trends and the opportunity it throws up for IT and analytics players in India. First, Big Data has become all-pervasive with the potential to create significant benefits for a number of sectors. The early adopters driving the business with appetite for Big Data analytics are industries such as Manufacturing, Retail, Financial Services, Telecom and Healthcare.”
In “Marketing Analytics Industry Expected to See Dramatic in India” references a report that shows companies are increasingly using marketing analytics technology as a way to stay ahead of their competition. This is particularly relevant in India because the marketing analytics industry is expected to grow from $200 million to $1.2 billion by 2012.
The report explains:
“Over the past few decades, the evolution in traditional media and the emergence of digital media has revolutionized the way products are sold to the customers. Marketing analytics play a pivotal role in helping marketers take informed data-driven decisions and effectively reach out to the audience. The marketing analytics industry is poised for exponential growth and India will be one of the foremost forces leading this revolution. This report is an effort to showcase potential of analytics to organizations, analytics players and prospective employees and will help pave the way for concerted effort to increase the usage.”
While these articles may discuss different aspect of big data, they all have one thing in common. They all call for a need for companies to invest in solutions that evolve with the times. Digital Reasoning is a big data analytics company that works within nearly every business sector to promote automated understanding over human effort.
Jasmine Ashton, October 1, 2012
Sponsored by ArnoldIT, developer of Augmentext.
IntelTrax Top Stories: September 7 to September 13
September 17, 2012
This week the IntelTrax advanced intelligence blog published articles on current trends related to big data, fraud detection, and analytics solutions that will help both of the previously stated problems.
“Real Time Analytics Makes an Impact” discusses how companies have spent the last couple of years making it so that their analytics solutions have zero lag time.
The article states:
“Operational Intelligence, basically, is real-time analytics over operational and social data. Operational intelligence, or OI as we like to call it, provides three important capabilities. First is real-time visibility over a wide variety of data. Second is real-time insight using real-time continuous analytics, and third is what we call right-time action, which means being able to take action in time to make a measurable difference in the business. We decided to focus on Operational Intelligence because it addresses some very important business problems that we felt were not well served by traditional software products today. These problems include service assurance in telco, social analytics for dynamic selling and brand management, real-time supply chain management, smart grid management in electrical utilities, and dynamic pricing in retail. These are just some of the examples.”
One way that analytics solutions have positively impacted a variety of industries is through the detection of fraud. “Fraud Analytics Deliver on Fine Art Forgeries” explains a new niche in fraud analytics that helps prevent substantial losses from individuals and museums.
The article informs:
“Just as with credit card fraud detection, the data sets created by digital authentication are quite large. Similarly, the modeling tools are extremely sophisticated, looking for patterns that would be unlikely from the painter just as a given purchase would be unlikely for a credit card holder. Zeroing in on the fraud can save an enterprise millions of dollars. Digital authentication is not real-time — it took two days to identify the fake Van Gogh. But in the world of art, that’s more than fast enough.”
When discussing advancements made in the industry, the information is often more well received when it comes from experts in the field. “Analytic News is Best From the Experts” showcases on experts opinion on the topic:
“Werner Vogels, a data guru as chief technology officer for Amazon Web Services, has been touting his interpretation of big data for almost two years. For him, managing a behemoth like Amazon, it’s not exactly what big data is, but what can be done with it.
“Big data is the collection and analysis of large amounts of data to create a competitive advantage,” he told a conference earlier this year.
“I am an infrastructure guy and for me big data is when your data sets become so large that you have to start innovating how to collect, store, organise, analyse and share it.”
Since technology is continuing to progress at rapid rates it is important the companies seek out a data analytics provider that evolves with the times. Digital Reasoning’s solutions, not only will protect your business from fraud, but its automated understanding for Big Data allows companies to find the necessary information they need to stay ahead of the competition.
Jasmine Ashton, September 17, 2012
Sponsored by ArnoldIT.com, developer of Augmentext.
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