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.
Now introducing the “Insight Ops” model. This new model will embrace and enable an agile environment for discovery and exploration and manage the transition necessary to deploy the insight to make it actionable.
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.
To ensure data science success, you need to provide data scientists with an environment that is open, engaging, and fosters collaboration. To explore how your data scientists can access all the open functionality and expertise they’ll need for critical projects, join the new Data Science Experience.
To ensure data science success, you need to provide data scientists with an environment that is open, engaging, and fosters collaboration. To explore how your data scientists can access all the open functionality and expertise they’ll need for critical projects, join the new Data Science Experience
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.
In this video, listen as IBM data science evangelist James Kobielus talks with Dean Wampler, a fast data product architect with the office of the CTO at Lightbend, about how data scientists can access the open functionality and expertise that are central to their work.
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.
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
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