As IBM's big data evangelist, James Kobielus is IBM Senior Program Director, Product Marketing, Big Data Analytics solutions. He is an industry veteran, a popular speaker and social media participant and a thought leader in big data, Hadoop, enterprise data warehousing, advanced analytics, business intelligence, data management and next best action technologies.
September 11, 2014
The customer is always right, even when some of them are totally unreasonable and, perhaps, a bit off their rocker.
September 4, 2014
The success of big data projects often depends on having access to robust, scalable data integration. You would be hopelessly naive if you didn't acknowledge the fact that integrating huge amounts of data into "data lakes" can be quite burdensome, costly, complex, time-consuming, labor-intensive and so on. Rest assured that big data integration doesn't need to be burdensome, especially if you're wielding the right platforms, tools, personnel and best practices. If you're suitably empowered, there's no need to fear the big data wolf at the door.
September 2, 2014
Transactions make the world go round, but fast analytics help the planet rotate even faster.
August 27, 2014
The consolidated memory cloud will be the dominant architecture of the big data future. For enterprises and service providers trying to get closer to that vision, however, the migration path will not always be straightforward.
August 21, 2014
Big data has been the heart of predictive and real-time weather analytics from the start. Throughout all eras, meteorological models have greedily devoured every high-performance computing resource thrown their way. Leveraging these resources, fine-grained local weather forecasting may not be as farfetched as it sounds. It might even be possible to use the Internet of Things and big data to control some atmospheric conditions in real time at the local level.
August 14, 2014
Working journalists are locked into a never-ending race against time. Not only are reporters always up against deadlines, but they are constantly scrambling to make sure they break the news before the competition. As more people turn to online news sources (including, but not limited to traditional news websites, streaming broadcasts and mobile apps) it's a bit bewildering to figure out who is scooping whom when on which breaking topics. Before long, we can expect to see the news services' data scientists build streaming tools that analyze how fast they and the competition are breaking news online, and bragging with data when they find themselves doing the scooping.
August 7, 2014
Wearable devices are becoming central to the modern lifestyle. These new devices will be among the first places where users originate personal data. They will also become the ultimate membrane where people consume the big data-driven personalized guidance being delivered from the cloud. In the process of supporting myriad roles in users' lives, wearables will almost certainly cache working data sets that push more deeply into big data territory in terms of their volumes, velocities and varieties. Nevertheless, under any likely scenario, individuals' personal data clouds will undoubtedly hold far more on the volume side of the equation than people store locally today.
July 31, 2014
There are complex challenges that a data scientist might face in statistically modeling real-time decision-support scenarios in fast-moving athletic competitions. Each sport needs to be modeled on its own terms. A within-game decision-support predictive model for one sport cannot be applied directly to another sport, even ones that share a common ancestor or many surface similarities. No two sports have exact same "game evolution" structure, embody the exact same rules, play on the same surface, use the same equipment or generate the same types of performance data.
July 24, 2014
Medical professionals are between the proverbial rock and hard place when trying to determine whether, how and why patients are failing to comply with doctor's orders. On the one hand, their ability to help people depends on having intimate, current and accurate knowledge of people's physical conditions and behaviors. On the other hand, doctors can't be Big Brother, engaging in 24x7 surveillance of their patients' private lives and wielding the power to punish recalcitrants. However, physicians can, within the bounds of privacy and propriety, use analytics to assess who might or might not be compliant. Using those insights, the healthcare system might identify the most appropriate real-time interventions to minimize the impacts of noncompliance on healthcare outcomes.
July 17, 2014
The recent controversy over the ethics of Facebook's attempts to influence moods through tweaks to its newsfeed algorithms is overblown. Essentially, Facebook data scientists conducted one of many real-world experiments that are standard operating procedure with them and with most online businesses these days. This was just a routine real-world experiment in big-data-driven sentiment analysis, content optimization and customer experience management.