Edd Dumbill is VP Strategy at Silicon Valley Data Science and Editor-in-Chief of the peer-reviewed journal Big Data. He’s also an entrepreneur, author, software developer, and chair of Strata conference. formerly was principal analyst at O’Reilly Radar. In a recent article titled “Big Data is
It turns out, borrowing key concepts from legendary business management gurus can play an important role in developing your big data strategy. Big Data Evangelist James Kobielus shares some of his favorite kernels of wisdom from the experts.
Big data is still relatively new with many organizations, and its significance in business processes and outcome has been changing every day. Here are some of the key best practices that implementation teams need to increase the chances of success.
1. Gather business requirements before gathering
In this episode of "Talking Big Data," we turn over the microphone to one of our clients, Jean-Marc Blaise, an experience DB2 user and consultant. Like many database administrators, users and consultants, he has questions about "big data." He will pose those questions to Leon Katsnelson, IBM
Within a few days of one another, IBM CEO Ginni Rometty shared her 3 Principles of Change at the Council on Foreign Relations, and the Wall Street Journal published a special series on big data and how it is changing the equation for business. This blog post reviews the key thoughts behind both
If you have ever tackled some sort of new technology, there is a very good chance you have run into one of these two guys: "This Changes Everything!" Guy or "This Will NEVER Work!" Guy. Tom Deutsch, program director for big data at IBM, has seen his share of both archetypes. He shares his thoughts
Progress demands that periodically we commit to infrastructure projects that create the conditions for innovation and delivering value. Mike Kearney draws parallels between the 19th century development of Australia, and its subsequent rewards, to 21st century big data projects.
Most organizations today still treat data as a raw material to be mined, with industrial processes for staged production. Your data isn’t an asset you lock up in a vault and protect long past its relevance. It is a product you combine with others, market and sell, buy and trade, to generate new
Big data can’t prove its business value if it remains in a perpetual proof-of-concept phase. How can you prepare your big-data deployment for delivery into a production IT environment? What exactly does it mean to say that big data, or any IT initiative, is truly production-ready? James Kobielus
There's no shortage of hype around big data. Consequently, there has been a fair amount of backlash. Now, Tom Deutsch, program director of big data at IBM, has some backlash against that backlash! He speaks out against the people who are spouting negative misinformation - without supporting facts