Recently, I had the honor of speaking with a number of the world’s most influential thought-leaders in the fields of data science, data analytics, machine learning and digital transformation. This group of prominent data technologists was more than happy to answer a wide variety of question on
How do you change the culture and the concepts of governance within your enterprise from being that as a roadblock to really being an enabler or even an accelerant? Learn more about unified governance approaches from speakers like Seth Dobrin, VP and Chief Data Officer, IBM Analytics, IBM, at Fast
Smart companies are finding new ways to squeeze more value out of their massive data storehouses. They’re unlocking insights from their data that build new business models, improve customer experiences and outpace competitors. So where do these business-changing insights come from?
Perhaps one the single most significant changes to the analytics landscape in recent years had been the emergence of the data scientist. This role is continuing to evolve, with many organizations still in the process of establishing how best to incorporate this relatively new discipline into their
Analyze your way to business success. Learn more about data analytics and visualization from speakers like Marc Altshuller, General Manager, IBM Business Analytics, at Fast Track Your Data - live from Munich or join online June 22, 2017. Register now.
In any successful modern organization, analytics is likely to play a central role in helping decision-makers design and execute effective business strategies. At IBM, as we work with clients across the globe, we’re seeing ever-increasing levels of maturity and confidence in data-driven business
Imagine what you could build if you could leverage all the data that you couldn’t access before? Learn about hybrid data management from speakers like Nancy Hensley, Director, Growth & Strategy, IBM Analytics, at Fast Track Your Data - live from Munich or join online June 22, 2017. Register
This is the fourth in a series of blogs on analytics and the cloud. Read our introduction to the series. This blog concerns itself with the rise of open source software and how it is used for a whole host of analytical purposes. However, as will be seen in this blog, there are significant gaps in
In the past, the relationship between the different models that might be used in defining a data warehouse was a very linear one. There may have been different model artifacts used as the team responsible for developing the data warehouse progressed through the usually waterfall-type set of
Although NoSQL database technology has been around for a long time (before SQL actually), not until the advent of Web 2.0, when companies such as Google and Amazon began using the technology, did NoSQL’s popularity really take off. Market Research Media forecasts NoSQL Market to be $3.4 Billion by
The Academy Awards provided a great example of the challenges of data integration. The business output of the data integration processes in the award ceremony is the announcement of a winner in a specific category.
Building a data lake is one of the stepping stones towards data monetization use cases and many other advance revenue generating and competitive edge use cases. What are the building blocks of a “cognitive trusted data lake” enabled by machine learning and data science?