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
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
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
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
The connected nature of the digital era empowers energy and utility consumers to choose their providers and actively manage and monitor consumption. And energy and utility providers face new challenges to provide the services consumers demand and retain loyal customers. Learn more about a
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
Understanding data and data relationships is particularly vital in the energy and utilities industry. Discover how industry data models serve as blueprints for defining structures that provide a broad, in-depth view of business, and how they helped one energy and utilities organization extract data
Across the rail and freight logistics industries, traditional approaches to asset utilization are shifting to accommodate a data-driven and proactive future where analytics and data insights provide companies with greater returns.
By using predictive analytics, providers can use real-time data to see risk factors that previously went undetected. Armed with this information, healthcare systems can then intervene and hopefully change the course of the patient's future health.
Marketers looking to expand their customer base and achieve retention continually contend with cognitive era challenges of rising data influxes from disparate sources. To cut to the chase, what they really need is a tool that predictively and prescriptively offers the means for recommending next-
Business professionals need answers to critical questions that bolster the accuracy of predictive forecasting. And forecasting is a vital approach for a number of business measures including product demand, revenue, sales and more. Discover why predictive forecasting is essential for any line of
Spark just seems to be getting big play everywhere in the technology arena. What is Spark? And do you need it? Get a good glimpse into its in-memory execution capabilities, some of its key components, its integrations and its availability as a service.
Graph database technology powered by open source initiatives is helping fraud detection units catch intruders in the act of breaching data security. Tune in for an enlightening discussion of how modern approaches to analytics are bringing descriptive and predictive analytics together to help stop
https://www.ibm.com/cloud/db2-warehouse-on-cloudApache Spark not only excels at data warehousing, in-memory environments for building data marts and other functions, it also is well suited for pulling data from a wide range of sources and transforming and cleansing that data in an Apache Hadoop