Eric D. Brown, D.Sc.

Data Science | Entrepreneurship | ..and sometimes Photography

Tag: Big Data (page 8 of 12)

Links for Sunday May 25 2014

The new CIO challenge: Assembling the right combo of human and machine smarts

Quote: Business peers are tech savvy, customers are plugged into your business like never before and digital disruptors are everywhere. Being a successful CIO in the digital enterprise is not about separating from your peers and customers, conference organizers said — it’s about effectively recognizing and integrating their strengths into your IT strategy.

Even Sweatshops are Getting Automated. So What’s Left?

Quote:The research is clear that technological progress has greatly benefitted people in the developing world so far. I wonder, though, if automation and deindustrialization might be creating a ‘silicon ceiling’ on growth — a situation in which even low wages are no longer an attractive alternative to technology. If so, the global shift away from labor and toward capital will only accelerate.

Innovation and the Hype Cycle

Quote: When an employee or consultant asks you what you mean when you say “innovation”, it’s not a throw-away line or a philosophical debate.  Defining and understanding the difference between innovation as a strategy, as a discrete, one time project or as a capability or discipline has implications.  Words matter, especially words that have hazy definitions that we allow others to define for us.  Executives, senior managers and innovators, pay close attention.  Define what innovation is, what it means, its purpose and goals, before anything else, or you too will end up a victim of the hype cycle.

Private cloud silliness

Quote: The bigger these clouds get (whether public or private), the more likely it is that additional resources will be there when an individual customer needs them. The bigger these clouds get (whether public or private), the greater the purchasing power and the more useful the economies of scale. Amazon’s data centres are probably bigger than those of most individual corporations, so Amazon has an advantage there. But that’s all it is – an advantage. Not a lock on the right to be called ‘cloud.’

Why the Human Story Will Always Beat Brand Storytelling

Quote: However, the “problem”, for want of a better word, with emotional marketing is it treads a very fine line between being authentic, and being a slickly-produced video or narrative for a new product. Get this part wrong and the connection you’re looking for is broken. A real human story, on the other hand, doesn’t suffer from this – because we know it’s real, and that’s where the power comes from.

Big Data, People and the SMB

Ebusiness ConceptAccording to the  2014 IDG Enterprise Big Data survey, most large organizations today (almost 49% of survey respondents) claim to be well along the implementation path for big data initiatives and projects. Additionally, those large organizations are well ahead of their small and medium business (SMB) counterparts.

There are a number of reasons for the lag between large organizations and SMB. The larger organizations have the money to address most of the big data requirements while small and midsized organizations haven’t found any budget to kick off big data initiatives.

In addition to budgetary differences, the larger organizations have access to more people. Whether via consulting companies or outsourcing big data work, large companies can find the people they need to ‘do’ big data. In the world of the SMB, the ability to bring in new people just isn’t there. Even though large organizations have money to pay for more people, the IDG survey points at the difficulty of finding skilled people as one of the most difficult challenges facing organizations today.

For me, the ‘people’ aspect of big data is the largest problem facing any organization. We can throw money at the technology issues and we’ll eventually find the right solution for our problem, but we can’t always throw money at the people problem, mainly because it isn’t necessarily a ‘money’ issue today.

Sure, it will take money to hire and train people but before that hiring and training occurs, organizations need to find the ‘right’ person or people for their big data initiatives. To me, this levels the playing field a bit for the SMB. The SMB may not have the budget to hire consultants, buy the newest and fanciest big data solutions or use the ‘best’ hardware and systems on the market, but those things aren’t what big data is about. Big data is about finding insights and value in data, and what better way to do that then to find people who are interested in analytics and giving them access to the organization’s data and saying ‘go’.

Rather than pigeon-holing people into being ‘developers’ or ‘analysts’ or ‘solution specialists’, SMB’s can give their people the ability see all aspects of the big data lifecycle as well as all aspects of the business. The ‘people’ problem of big data is an area that SMB’s can win if they are a bit creative in their approach. They may not have the million dollar big data budgets, but SMB’s can bring more value to the people equation by giving more opportunities to people interested in big data.

Big Data Starts with Data Management

Over on the Obsessive-Compulsive Data Quality blog, Jim Harris recently wrote:

 While organizations of all sizes are rightfully excited about the business potential of using big data, this excitement needs to be balanced by acknowledging the business risks associated with not governing the ways big data is used.

Well said.

Many organizations have been caught up in the ‘hype’ of big data. The good thing – the hype behind big data is generally driven by real-world success from organizations using big data. That said, there are risks involved in big data projects.

There are risks on the input side (the data that you use) and risks on the output side when you don’t understand the context of the data you are analyzing. To be successful ‘doing’ big data, organizations need to understand the inputs and outputs of big data. Starting with data management will help mitigate these risks since a good data management approach allows organizations to keep data quality in mind from the beginning of a big data project.

Starting with data management and data governance helps you understand and ‘control’ your data and eliminate risks from the outset. Additionally, governance allows you to manage multiple aspects of your data including how/when data is collected, who has access to data and how your data is archived.

When approaching big data projects, many consultants and vendors will talk about many aspects. They’ll talk about the value big data can bring. They’ll talk about systems and analytical approaches. Some may talk about statistics and visualizations. Before you dive in too deeply into any of these necessary topics, make sure to ask these same folks what they are proposing for data management and data governance.

IBMThis post was written as part of the IBM for Midsize Business program, which provides midsize businesses with the tools, expertise and solutions they need to become engines of a smarter planet. I’ve been compensated to contribute to this program, but the opinions expressed in this post are my own and don’t necessarily represent IBM’s positions, strategies or opinions.

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Don’t Chase Big Data

Last week I noticed this little gem over on ReadWriteWeb.com:

Gartner highlights that only 8% of enterprises have actually deployed big data projects despite 64% declaring their intention to do so.

Word Cloud "Big Data"That’s a big statistic.

Think about it. Out of all the hype and discussions about big data, less than 10% of enterprises have actually deployed big data projects.

Why the disconnect between the hype and the reality? I’m sure there are plenty of reasons (e.g., how Gartner identified ‘enterprises’, who they interviewed, how they defined ‘big data projects’, etc) but I suspect the real answer comes down to the simplest reason of all…nobody really understands big data enough to put big money into it.

Imagine out of all the large organizations out there with good-sized budgets. Then, imagine those same organizations struggling to implement big data. What does that mean for the small and midsized organization? if the ‘big boys’ can’t figure it out…how are the SMB’s supposed to?

Actually…if you are a SMB CIO or leader, you really shouldn’t care what the ‘big boys’ are or aren’t doing. You should be focused on how your organization can use the data you have. You should be focused on how you find information (and ultimately knowledge) from that data. The same goes for any size organization…don’t get caught up in the hype and think you have to ‘rush’ into big data projects.

Gartner says that only 8% of enterprises have deployed big data projects – but don’t think for a second that most of those 64% that have declared intent to deploy projects haven’t been spending money and trying to deploy. Don’t get caught in the hype and try to ‘keep up’. Instead, find what works for your organization and then figure out how to make those approaches work best for your data projects.

IBMThis post was written as part of the IBM for Midsize Business program, which provides midsize businesses with the tools, expertise and solutions they need to become engines of a smarter planet. I’ve been compensated to contribute to this program, but the opinions expressed in this post are my own and don’t necessarily represent IBM’s positions, strategies or opinions.

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Links for Sunday Feb 23 2014

  • What’s Your Story?

    Quote: Taking our corporate strategy, translating it into traceable, optimizable metrics, and using our data and models in a disciplined and iterative manner will allow us to be the best possible company we can be

  • IT Language Lessons « The Dark Side Geek

    Quote: So what is the “common language”? The answer was already there. In an IT organization properly aligned to business objectives, it is the business objectives themselves that provide the common language. Don’t think in terms of us vs. them trying to find some middle ground via Finance. Instead, IT needs to learn to speak in terms of “opportunity management”. What better way to be on the same page with your partners than using the most direct language possible?

  • How To Think

    Quote: If you believe that your school’s mission or your job as a teacher is simply to convey information, then it probably doesn’t seem necessary to subject your students to that kind of rigorous self-analysis. But if you’re trying to help them change their character, then conveying information isn’t enough. And while Spiegel didn’t use the word character to describe what she was teaching, there was a remarkable amount of overlap between the strengths David Levin and Dominic Randolph emphasized and the skills that Spiegel tried to inculcate in her students. Every day, in the classroom and at tournaments, I saw Spiegel trying to teach her students grit, curiosity, self-control, and optimism.

  • The Key For Hadoop Adoption: Learning How To Make Big Data Small – ReadWrite

    Quote: While it remains true that far more people are talking about big data than actually rolling out significant big data projects—Gartner highlights that only 8% of enterprises have actually deployed big data projects despite 64% declaring their intention to do so—the percentage of companies engaging in Hadoop-based big data projects should grow now that its primary proponents are selling substantive, achievable business value rather than Hadoop hype.

  • Do You Really Understand Your Numbers? | Partners in EXCELLENCE Blog — Making A Difference

    Quote: Know the critical numbers for each week. Know the numbers that lead you to achieving your goals. Know the numbers that look at overall organizational performance, effectiveness and efficiency. Look at longer term trends. Slice and dice the numbers across a number of dimensions–you’ll be amazed at what you discover.

  • MIT study says Twitter can predict major public events like protests — Tech News and Analysis

    Quote: An MIT study claims that Twitter can be used to predict major social events, thanks to heavy activity from specific communities.

  • Content Matters When Going Mobile A Smarter Planet Blog

    Quote: In terms of behavior, you need to know when your audience is checking their devices and what kind of information they are looking for when they do. Once you understand your consumer’s behavior, you must then think about your distribution channels.

  • The real promise of big data: It’s changing the whole way humans will solve problems | VentureBeat | Big Data | by Zavain Dar, Innovation Endeavors

    Quote: We’re seeing great emphasis not only in collecting new data, but also in storing and automating the actionability of this data. In the Valley we joke about how the term “big data” is loosely thrown around. It may make more sense to view “big data” not in terms of data size or database type, but rather as a necessary infrastructural evolution as we shift from analytic to synthetic problem solving.

  • How to deal with a Zombie product | On Product Management

    Quote: A zombie product is a product that is not successful by any measure (very few customers, little market share, lacking needed functionality, buggy etc.) but also cannot be “killed” or removed from the market because of some reason or another. Usually the reason for keeping an otherwise failing product on the shelf is that it is viewed as “strategic” or “important” in some way to those higher up in the company.

  • How Good is Your Data? | Big Data Forum

    Quote: Organizations are excited about big data and are looking for ways to incorporate the use of data and analytics, but I rarely hear anyone talking about data management, quality management and lifecycle management of data.

Two examples of data helping SMB’s

ku-xlargeWe often read anecdotal evidence of how companies and consultants are using big data to solve ‘big’ problems but it is rare that we see real world examples of the use of analytics and data to solve real-world business problems for small and midsized businesses.

IBM recently reported on two examples of SMB’s using big data to better manage their business in a piece titled “Here’s What Salame and Sequined Dresses Have in Common”. In this article, two SMB’s – Adrianna Papell and Columbus Foods – are described as is their use of analytics and data in understanding their clients and their business.

Adriana Papell, a fashion company founded in 1979, was having trouble trying to understand the enormous amount of data that they had been collecting and then find a way to use that data to better manage their business. The report states the following:

Using point-of-sale data, retail partner location, and time, they were able to get a sense of what their customers were buying and when they bought it. Armed with that insight, they were able to predict what would sell well, reduce production of what wouldn’t, and increase sales by fifteen percent.

Columbus Foods has been around since 1917 making salami and other deli meats. While they’ve been quite successful over their lifetime, the company is still trying to identify methods to improve their business. In this instance, they turned to data to:

to predict purchases and prevent inventory shortfall. By tracking historical sales data for their meats, they could more accurately predict buying patterns and make better-informed decisions about how much meat to make. So no matter how long it takes to make a batch of pepperoni, they don’t have to worry about spoilage.

Both companies are clear examples of using data to understand their business and make decisions based on the data within the business. There’s nothing “special” or “magical” about what these companies have done with data. They simply used the data they had and began to look at that data differently.

Big data isn’t always about new technologies, new data or even the size of data. It is about taking the data that you have, collecting new data if needed, and then analyzing that data in a way that makes sense for your business.

Don’t let the hype about big data scare you off. Your organization doesn’t need to be a huge company to incorporate data analytics into your business. The two companies described here and in the IBM report are perfect examples of how SMB’s are using big data methods to manage their business.

IBMThis post was written as part of the IBM for Midsize Business program, which provides midsize businesses with the tools, expertise and solutions they need to become engines of a smarter planet. I’ve been compensated to contribute to this program, but the opinions expressed in this post are my own and don’t necessarily represent IBM’s positions, strategies or opinions.

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