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.
Create meaningful client connections. Unlock the potential in your data by analyzing data from many sources using sophisticated, prebuilt industry-designed analytical models; leveraging dynamic segmentation by analyzing client behavior; and predicting key client life and financial events to create
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
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
Create meaningful client connections by unlocking the potential in your data when you do the following: • Analyze data from multiple sources using sophisticated, prebuilt industry-designed analytical models. • Leverage dynamic segmentation by analyzing client behavior. • Predict key client life
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
Unlock the potential in your data to create meaningful client connections with IBM Client Insight for Wealth Management with Watson. Analyze data from many sources with sophisticated, prebuilt industry-designed analytical models, personalize offers to match the changing needs of clients and
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
Joe Caserta is founder and president of Caserta Concepts, a New York–based innovation technology and consulting firm that specializes in big data analytics, data warehousing, ETL and business intelligence. Don’t miss this enlightening discussion between Joe Caserta and IBM data science evangelist