December 24, 2012 • big data, upstream • By Paul M. Davis
Delivering toys to millions of children around the world in one night: suffice to say, Santa and his helpers at the North Pole may have been the first enterprise to contend with Big Data’s challenges. How does he keep track of all those wish lists, perform QA tests on prototypes, and ensure that toy production is on track to meet his yearly launch date of December 24th?
Read more »
December 19, 2012 • big data, data warehousing, Hadoop, practitioners, predictive analytics, technical • By Will Davis
When our company was acquired by EMC in July of 2010, we could have easily been scooped up and monetized as a pretty nice data warehousing business for our parent company. They decided to do the opposite. EMC’s leadership believed in our team and our vision for leading the Big Data analytics industry and decided to double down on their investment.
Read more »
December 17, 2012 • data science, practitioners, predictive analytics, upstream, visualization • By Paul M. Davis
There’s a significant gulf between collecting Big Data and being able to confidently act upon it. In that gulf you’ll find data scientists developing and refining models, identifying questions, and communicating the insights and predictions that emerge. Effectively conveying these conclusions requires more than simply plotting points on a graph or map: it’s a narrative process.
Read more »
December 12, 2012 • data science, practitioners, upstream • By Paul M. Davis
With Big Data becoming one of the year’s top buzzwords, terms describing the practitioners working with said data can become confused. As Data Scientists grow in demand in the job market, it’s important that the role doesn’t grow conflated with that of Data Analytics.
Read more »
December 10, 2012 • big data, culture, data science, upstream • By Paul M. Davis
With the music industry still scrambling to make money in the age of digital distribution, companies and musicians are increasingly turning to data to crack the code. In response to the low royalty rates paid by streaming audio services, cellist Zoë Keating recently declared on her blog, “the law only demands I be paid in money, which at this point in my career is not as valuable as information.
Read more »
December 05, 2012 • big data, upstream, visualization • By Paul M. Davis
With data from social media platforms accounting for an ever-increasing amount of the Big Data deluge, collecting that data becomes an ever-moving target. As social networks proliferate, so do the respective services’ APIs and access policies. Social media aggregator Gnip aims to simplify the process, allowing businesses to focus on reaping social data insight, rather than tracking which services are hot, which are not, and which have changed their API policies.
Read more »
December 03, 2012 • best practices, data science, Hadoop, technical • By Donald Miner
One of the common questions I get from people about my new book MapReduce Design Patterns is “why did you write it?” In this post, I’ll explain the reasons, as well as what MapReduce design patterns are, why they need to exist, and why the time is right.
Read more »