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.
Scientists are using predictive weather data capabilities to analyze and forecast storm paths with increasing accuracy. They’re tapping into data from a variety of sources for information, and these developments and applications of data analytics help keep communities in the paths of oncoming
Missing the mark in customer segmentation marketing can be detrimental for consumer product companies. Marketing consumer products demands a fluid, dynamic process for customer segmentation that is in sync with today’s consumer. Learn more about how cognitive analytics leverages consumer and
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 scientists and others often encapsulate big data by its dimensions known as the four Vs: volume, variety, velocity and veracity. But when considering big data as a source for insight to enhance decision making, it may be best characterized by its three Cs—confidence, context and choice—with
The choice to flex a data warehouse on a private cloud is a personal one. It offers benefits in three key areas: enhanced control over data and apps, better management and monitoring, and custom tailoring that is built to address specific user requirements and self-service applications.
Reimagine the data science experience as an open experience with this IDE, which aims to facilitate a full range of development tasks, from data acquisition and data mining to prototyping and programming. When you do, discover how you can use Apache Spark and R to pursue open analytics by building
Machine learning is finding its way into a variety of applications. Discover an open source machine learning platform that combines the data processing power of Spark with powerful machine learning algorithms courtesy of the H2O platform to tackle challenges technologists face when applying machine
In the media and entertainment industry, audience analysis should be priority one for executives. Listen to an audio presentation of a white paper that explores the industry trends and highlights that can drive widespread adoption of audience analytics.
One of the biggest challenges for retailers has always been scaling great customer service, specifically how to better personalize in-store experiences. By combining data analysis, the Internet of Things, cloud and mobile technologies, retailers can make this level of personalization a reality for
Use open-source tools to supercharge the data science lifecycle, giving data science teams a boost as they work to provide compelling results in the complex team environments that mark modern corporations. Learn how you can make open data science an ongoing part of your business environment when
Whether organizations want to extract customer data beyond names and addresses from unstructured data sources; pull specific dates, times or monetary amounts; predict trends from sentiment data; or engage in many other uses, text analytics is the way to go. Learn the details of text analytics, and
A growing number of businesses and industries are finding innovative ways to apply graph analytics to a variety of use-case scenarios because it affords a unique perspective on the analysis of networked entities and their relationships. Gain an understanding of how four different types of graph