Big Data

Big Time — Elements of Data Size in Scaling

I’ve run into additional questions about scalability.  It is significant to understand the concept in terms of assessing software against data size, since there are actually various aspect of approaching the issue.

Unlike situations where data is already sorted and structured as part of the core functionality of the software service being provided, this is in dealing in an environment where there are many third-party software “tools” that put data into proprietary silos.  These act as barriers to optimizing data use and gaining corporate intelligence.  The goal here is to apply in real terms the concept that the customers generating the data (or stakeholders who pay for the data) own the data and should have full use of it across domains.  In project management and corporate governance this is an essential capability.

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I Can See Clearly Now — Knowledge Discovery in Databases, Data Scalability, and Data Relevance

I recently returned from a travel and much of the discussion revolved around the issues of scalability and the use of data.  What is clear is that the conversation at the project manager level is shifting from a long-running focus on reports and metrics to one focused on data and what can be learned from it.  As with any technology, information technology exploits what is presented before it.  Most recently, accelerated improvements in hardware and communications technology has allowed us to begin to collect and use ever larger sets of data.

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The Monster Mash — Zombie Ideas in Project and Information Management

Just completed a number of meetings and discussions among thought leaders in the area of complex project management this week, and I was struck by a number of zombie ideas in project management, especially related to information, that just won’t die.  The use of the term zombie idea is usually attributed to the Nobel economist Paul Krugman from his excellent and highly engaging (as well as brutally honest) posts at the New York Times, but for those not familiar, a zombie idea is “a proposition that has been thoroughly refuted by analysis and evidence, and should be dead — but won’t stay dead because it serves a political purpose, appeals to prejudices, or both.”

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The Future — Data Focus vs. “Tools” Focus

The title in this case is from the Leonard Cohen song.

Over the last few months I’ve come across this issue quite a bit and it goes to the heart of where software technology is leading us.  The basic question that underlies this issue can be boiled down into the issue of whether software should be thought of as a set of “tools” or an overarching solution that can handle data in a way that the organization requires.  It is a fundamental question because what we call Big Data–despite all of the hoopla–is really a relative term that changes with hardware, storage, and software scalability.  What was Big Data in 1997 is not Big Data in 2016, and will not be Big Data in 2030.

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Stay Open — Open and Proprietary Databases (and Why It Matters)

The last couple of weeks have been fairly intense workwise and so blogging has lagged a bit.  Along the way the matter of databases came up at a customer site and what constitutes open data and what comprises proprietary data.  The reason why this issue matters to customers rests of several foundations.

First, in any particular industry or niche there is a wide variety of specialized apps that have blossomed.  This is largely due to Moore’s Law.  Looking at the number of hosted and web apps alone can be quite overwhelming, particularly given the opaqueness of what one is buying at any particular time when it comes to software technology.

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Do You Believe in Magic? — Big Data, Buzz Phrases, and Keeping Feet Planted Firmly on the Ground

My alternative title for this post was “Money for Nothing,” which is along the same lines.  I have been engaged in discussions regarding Big Data, which has become a bit of a buzz phrase of late in both business and government.  Under the current drive to maximize the value of existing data, every data source, stream, lake, and repository (and the list goes on) has been subsumed by this concept.  So, at the risk of being a killjoy, let me point out that not all large collections of data is “Big Data.”  Furthermore, once a category of data gets tagged as Big Data, the further one seems to depart from the world of reality in determining how to approach and use the data.  So for of you who find yourself in this situation, let’s take a collective deep breath and engage our critical thinking skills.

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Let’s Get Physical — Pondering the Physics of Big Data

As a primer a useful commentary on the ethical uses of Big Data was published today at Salon.com in an excerpt from Jacob Silverman’s book, Terms of Service: Social Media and the Price of Constant Connection.  Silverman takes a different approach from the one that I outline in my article, but he tackles the economics of new media that were identified years ago by Brad DeLong and A. Michael Froomkin back in the late 1990s and first decade of the 21st century.  This article on First Monday from 2000 regarding speculative microeconomics emerging from new media nicely summarizes their thesis.  Silverman rejects reforming the system in economic terms, entering the same ethical terrain on personal data collection that was explored by Rebecca Skloot on the medical profession’s genetic collection and use of tissue during biopsies in the book, The Immortal Life of Henrietta Lacks.

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The Song Remains the Same (But the Paradigm Is Shifting) — Data Driven Assessment and Better Software in Project Management

Probably the biggest DoD-centric project management news this past week was the unofficial announcement by Frank Kendall, who is the Undersecretary of Defense for Acquisition, Technology, and Logistics USD(AT&L), that thresholds would be raised for mandatory detailed surveillance of programs to $100M from the present requirement of $20M.  While earned value management implementation and reporting will still be required on programs based on dollar value, risk, and other key factors, especially the $20M threshold for R&D-type projects, the raising of the threshold for mandatory surveillance reviews was seen as good news all around for reducing some regulatory burden.  The big proviso in this announcement, however, was that it is to go into effect later this summer and that, if the data in reporting submissions show inconsistencies and other anomalies that call into question the validity of performance management data, then all bets are off and the surveillance regime is once again imposed, though by exception.

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Brother Can You (Para)digm? — Four of the Latest Trends in Project Management

At the beginning of the year we are greeted with the annual list of hottest “project management trends” prognostications.  We are now three months into the year and I think it worthwhile to note the latest developments that have come up in project management meetings, conferences, and in the field.  Some of these are in alignment with what you may have seen in some earlier articles, but these are four that I find to be most significant thus far, and there may be a couple of surprises for you here.

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The Big (D) — Ways of Looking at Big Data

Recently I have been involved in several efforts regarding what is often referred to as Big Data, but of a particular kind.  Oftentimes the term, which was first defined by Doug Laney now at Gartner, is seen as utilizing data in order to monetize consumer information that is being collected to allow business to focus advertising, marketing, and product development.  More generally, however, big data (as defined by Laney) distinguishes itself from normal relational database management by its volume, variety, velocity, variability, and complexity.  The Wikipedia definition is slightly different with the additional attribute of veracity.

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