IBM Analytics VP of Marketing Jeff Spicer sits down with Data Scientist and evangelist Dez Blanchfield to recap IBM InterConnect 2017 and give his insights into a few of the announcements from this year's event.
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?
Data is often the catalyst that drives business direction and growth. However, if data is cryptic and not understood, then how can such data contribute to such direction or growth? Just like in life, we learn from our past, as we gain direction and insight from previous events or activities to make
Quite often, we see that the need for data security and governance makes some organizations hesitant about migrating to the cloud. This is perfectly understandable given the types of data gathered and used by businesses today, the regulations they must adhere to on both a local and global level,
Nutrition is the science of how food effects the human body and focuses upon disease prevention, healing and management of chronic conditions. A dietitians’ field of work is however much generalized. This includes working with different diets, applications, data sources, articles, and multiple
With the Geospatial Analytics service in IBM Bluemix, you can monitor moving devices from the Internet of Things. The service tracks device locations in real time with respect to one or more geographic regions. Geospatial Analytics can be used as a building block in applications that support
This white paper discusses the advantages of using the PySpark API, which enables the use of Python to interact with the Spark programming model. It starts with a basic description of Spark and then describes PySpark, its benefits, and when it is appropriate to use instead of "pandas" open source
This is the second in a series of blogs on analytics and the cloud. We will consider the rise of the Internet of Things (IoT), analytics used on that data and how the cloud can be utilized to drive value out of instrumenting a very wide range of ‘things’.
There is a growing need for versatile, hybrid architectures that can combine the best of both data warehousing and big data analytics. The cloud is the perfect solution, because it makes it easier to build a robust data warehouse as a central “hub”, and then add other environments that can be
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