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.
Maybe classifying data as structured or unstructured isn’t so simple. What is structured to some may not be structured to others and vice versa. When it comes to the business value of data, consider another way to look at data—whether it is repetitive data or non-repetitive data.
When I spoke with Derek Schoettle, General Manager, Analytics Platform Services, the subject of open source capabilities came up a few times. Data is going to change the culture of business, and in fact it becomes the culture when you truly embrace it.
What is the key to staying ahead of the competition? Quite simply, data science. See why innovative companies have embraced the power behind data and analytics to move themselves way out in front of competitors.
Don’t let your business come to a standstill as a result of technical debt. Discover how a decision debt approach to tools and analytics help overcome the quick-fix solutions that contribute to technical debt and its impact on business.
Many organizations today have digital transformation at the center of their corporate strategy. At the heart of this transformation is the ability to develop actionable insights. The key is to gain smarter, more accurate insights faster than their competition and then translate that insight into
Are you a big data and analytics subject-matter expert? Do you enjoy writing? Would you like to be published? Check out IBM Press and the great opportunity to be a big data and analytics author. Share your expertise with readers from customer and partner organizations, colleagues and the greater
Insights from CIOs can reveal a lot about the industries in which they operate, and hearing from IBM’s CIO is no exception. Check out these highlights from a recent podcast featuring Jeff Smith, CIO at IBM, who offers a glimpse at his idea of focusing on culture, a story of transformation, the CIO’
Data analytics is fueling new strategies in law enforcement from the federal level down to local departments. Whether it's finding patterns across time and location, predicting new threats or linking resources to responders during major events, data is the future of proactive emergency plans.
Spark’s built-in machine-learning library (MLlib) provides a key differentiator from predecessor open source technologies and leverages Spark’s distributed, in-memory execution model. Take a look at some practical applications for specific Spark machine-learning algorithms in three advanced