IBM today announced exciting news about their Open Platform initiative with Apache Hadoop. And at its DataFirst Launch Event tonight, IBM will provide an early access view of the new IBM Project DataWorks with Watson, along with an introduction to DataFirst Services from IBM. IBM today also
Going forward, the businesses that truly disrupt their industries will be those who empower all of their personnel with open platforms, tools, and methodologies for data-driven app development. In that regard, this week’s announcement from IBM and our partners represent a key industry milestone.
When we look at all the uses of data organizations can embark upon, they fall into four main exercise groups of increasing benefit. Let’s go through each in turn and assess where your organization is in its journey to a healthier business.
Many marketing concerns have seen the light when it comes to the application of big data analysis as a means of outthinking the competition. Discover three best practices for implementing big data analytics for good data science in marketing initiatives.
Open data science initiatives can be a revolutionary force for innovation that spans diverse industries. And that force comes from the people in different roles and with various skill sets who use open source data science tools to develop and deploy new designs for working and living. Discover why
The productivity of data science teams—often challenged by access and formatting minutiae—can be enhanced by automating many of the manual tasks these teams need to process. Take a peek inside the mind of a data scientist, and see how acceleration of the data science development pipeline can boost
The importance of data science expertise, techniques and tools in a world rapidly employing advanced cognitive systems cannot be understated. Learn more about how business analysts, data scientists, data engineers, application developers and other professionals with analytical skills sets are using
As a working data scientist, you must deliver on your projects while at the same time staying up to speed on changes in your chosen field. That’s a tough balance, considering how stretched you already on the job and how quickly the world of data science is evolving. That’s where IBM World of Watson
The success of next-generation data science initiatives depends heavily on teamwork from the right mix of application developers, business analysts, data engineers, statistical modelers and other specialists. Discover more about the composition of high-quality data science collaboration through the
And they said resilience—continuous data access in the face of outages, failures and downtime—across distributed data sources is impossible. Yet the recent IBM BigInsights release offers this capability in its IBM Big Replicate technology. Get an inside look at resilience in an interview with Jim
Developers and data engineers’ horizons are broadening with the advent of technologies designed to help them build and deploy analytics applications quickly and easily. Take part in the open beta of the Basic Plan for IBM BigInsights on Cloud to find out what lies in your future as you build
A day in the life of data science professionals likely involves navigating the challenges and complexities of sourcing, preparing, modeling, developing and governing data, analytics tools and other assets in collaborative environments. Get a glimpse of the roles that compose data science teams and
To drive coordinated planning across diverse business functions, and deliver huge value to planners and decision-makers, the most efficient approach is to use common decision optimization tools that address business and process specifics.