All in Big Data
More Perspectives on Sharing Large Open Research Data Sets: Physics
McCauley provides a nuanced view of open data in the CERN context that I believe helps make sense of a very complex situation.
Thinking About “Data Program Governance”
Creating a data program governance strategy is not unlike creating other types of enterprise business strategies.
Improved Data Access Requires More than Analytics and Technology
Whatever the environment, new data management and analysis technology may be important, but success and sustainability will also be driven by how we manage it and by how successful we are in putting data users and their priorities into the driver’s seat.
On Managing Health Data Programs: Some Thoughts After the Health Datapalooza Conference
As an extension of my own research and consulting on big data project planning and management, I wanted to improve my understanding of how data governance and program management practices impact how medical and health data are used.
What Kind of Management Structure Is Needed to Govern a Data Analytics Program?
I’m fairly “old-school” when it comes to planning and building information systems. That is, first you decide what your requirements are and what services you need to provide, then you decide which technologies you need to adapt, develop, or purchase to help you meet those requirements.
Learning From General Electric’s Big Data Challenges
Two risks are apparent for GE’s approach which may also be relevant to other industries where cloud-based analytical platforms are being developed and marketed. (I’m thinking here, for example, of medical devices, prescription medicine, and treatment costs.)
Can Government Regulations Drive Improvements in Enterprise Data Governance?
Government regulators need to be sensitive to the costs of complying with and overseeing the regulations they impose on data management, as do the organizations that are regulated. Costs related to data oversight, quality control, standardization, security, and privacy all need to be considered in comparison with the quantitative and qualitative benefits that will be generated.
How Important Is "Perfect Data" To Your Data Analytics Program?
If you’re doing exploratory data analysis to help you decide how much data prep might be needed to make your data public, that’s one thing.
What Goes Up Must Come Down: Comparing 'Big Data' with 'Web 2.0'
While I expect that the term “big data,” like the term “web 2.0,” will be with us for a long time, it use may very well decline as different organizations move ahead by incorporating improved analytics into both operations and their decisionmaking — regardless of what they call it.
Regarding Big Data One Manager's "Resistance" Is Another Manager's "Caution"
Given the wide variations that currently exist in most organizations in understanding the ins and outs of managing current data governance and analytics practices, it’s not surprising that bringing in potentially “disruptive” technologies will be even more of a challenge.
Challenges to DevOps May Be Deep-seated But Not Unexpected
After years in consulting and project management, though, I now view politics and culture as factors to be anticipated and managed rather than ignored. This is true whether one is planning an individual project or an enterprise wide portfolio management strategy.
Horatio Nelson, Dwight Eisenhower, SharePoint, and Big Data
There’s a lot more to collaboration than just providing a technology platform.
Developing a Basic Model for Data Analytics Project Selection
One of the benefits of focusing on behavioral outcomes as a way of assessing the effectiveness or usefulness of improved data analytics is that behavioral outcomes are potentially measurable.
Big Data Project Management - Where to Start? (Slide Deck)
A slide deck summarizing where I am on researching Big Data Project Management.
Introduction to PLANNING AND MANAGING BIG DATA PROJECTS: SELECTED ARTICLES
I began researching “big data project management” when I started seeing publications and online discussions concerning big data project “failures” being attributed to the classic reasons for project failure such as scope creep, poor stakeholder engagement, and inadequately understood requirements.
Understanding the Challenges of Big Data Project Management: “The Data Must Flow”
If what Nate Silver said in a recent presentation is true – “Big Data has Peaked, and that’s a Good Thing” – perceptions about big data are maturing.