Prescriptive analytics (optimization) is a sophisticated analytics technology. It can deliver great business value by helping decision makers handle the tough trade-offs that arise when limited resources force choices among options. Optimization was traditionally applied by Operations Research
Chief Data Officers, in particular, will want to take note of Generation Z as they begin to grow up, because many of their attitudes and behavior toward data are shifting from that of previous generations. Those that prepare for Gen Z early and build a relationship with them based on good data
The reality is that AI is still heavily-reliant upon smart, willing and trained humans in order for AI to behave in a manner that we would expect. Humans are needed to scope the problems, identify relevant examples and verify the results. Without humans as a guide, current AI is no more capable
Fundamentally, machine learning is a productivity tool for data scientists. As the heart of systems that can learn from data, machine learning allows data scientists to train a model on an example data set and then leverage algorithms that automatically generalize and learn both from that example
The need for information is paramount to our need to excel and succeed. Businesses rely on information for strategic planning and driving growth. Individuals rely on information to make decisions and gain understanding of things. All information is driven by knowledge, and for knowledge to be an
January marked the release of the long awaited Hidden Figures movie featuring an all-star cast and highlighting the contributions of both women and IBM's technology to history. Hidden Figures tells the true story of three African-American female mathematicians, Katherine Johnson, Mary Jackson, and
When the data lake is deployed as an infrastructure to be exploited by different users in various departments with their own needs, their own different requirements and often their own dialects in terms of a business language, then a universal translator can become very useful. Especially with the
There is so much talk about data as a new natural resource. The amount of data organizations and citizens across the globe produce, is authored in many systems and consumed by various organizations and users in different formats. This begs the following questions: Who owns this data? And why it is
CIOs are saddled with the incredible responsibility of ensuring all things IT are not just functioning, but are meeting the high demands of both internal enterprise users as well as those customers that rely on that enterprise as part of their own business. Though CIOs have an incredible
This is the first in a sequence of blogs that takes a peek at what is driving analytics onto the cloud, what are the challenges that will need to be overcome over the next 5 years and how they will be tackled.
In cognitive computing era, new revenue generation stream has emerged with data at center of the modern digital business model. One of the key capabilities cognitive computing enables for an organization is the ability to generate additional revenue streams by using data effectively. In the big
IBM’s community of big data developers continues to grow. As our Big Data Developer meetup program moves into its fifth year, this worldwide community of customers, partners and IBM developers is on the verge of enlisting its 100,000th member—when we published this blog, we counted 99,100.
It is said that more data has been created in the past two years than in the entire preceding history of mankind. It would be interesting to find out how much of this data has been analyzed and put to good use. Analyzing and harnessing big data is undoubtedly the major challenge of the day for all
IoT is the next goldmine of data. Today, it’s still largely untapped information that is primarily used for operational monitoring. By combining that data with traditional “corporate” data, you can improve customer service through faster problem recognition and response, react more quickly to a