IBM invented the SQL language and the concept of a query optimizer back in the late 1970s. Four decades later, how and where we store data has changed dramatically, but the expertise to optimize queries derived from decades of advanced research remains a core IBM competency. And the ability to
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
Chris Snow, a data and application architect, enjoys helping customers with their data architectures and is working extensively on an open source app project in his spare time. Hear what Snow has to say about his IT experience spanning several industries, his current efforts with customers and his
Has your business adopted a hybrid analytics architecture as part of its quest to compete? Listen as Martin Fleming, IBM’s chief analytics officer and chief economist, explains why doing data analytics on the cloud is creating opportunities for modern businesses, and be sure to take notes as he
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
Andrew Oliver is president and founder of Mammoth Data (formerly Open Software Integrators), a large data consulting firm based in Durham, North Carolina. In this interview, join Andrew and IBM data science evangelist James Kobielus for an enlightening discussion about doing data science in the
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
Many organizations can capitalize on big data solutions and technologies to make use of expanded volumes of data for enhancing the critical decisions that drive successful business outcomes. And yet, a number of these enterprises can be inhibited from moving big data initiatives forward for a