As the market moves from fascination with the wonders of the current bloom of Big Data technologies to reconsideration of their risks and perils, enterprises and IT operations are left to figure out how these developments might impact their business—and when. Hadley Reynolds, co-founder of the Cognitive Computing Consortium, presents an open reference framework jointly developed with Babson College’s technology management program. The framework gives executives and operating managers a tool to characterize the impact and behaviors of potential AI applications. Beyond impacts and behaviors, the framework integrates profiles of skills and resources required to effectively execute cognitive tasks.

Many organizations have made the journey to the cloud or are about to embark on that path. How can you be sure the data is protected and stored with adherence to changing regulatory mandates? What do you move first? How do you avoid vendor lock-in?

Today’s data-driven businesses are adopting Big Data to boost analytical capabilities and to minimize their dependency on obsolete legacy systems. While enterprises are stabilizing their on-premise Hadoop clusters, a majority of them are already targeting the next big thing: moving their storage and processing to cloud. This migration may sound attractive, but it comes with challenges. Of them, data security, regulatory, and compliance requirements are the most significant. Additional concerns include the uncertainty of costs, perceived loss of control, and vendor lock-in. Kamal covers the successful solution patterns used in overcoming the most prominent challenges.

The shift to Big Data platforms creates both opportunities and challenges. Storing three copies of your data doesn't protect against human error, corruption, or threats like Ransomware. Compliance with stringent new regulations presents additional challenges. Keys to success include accurate and rapid point-in-time recovery, efficient storage tiering, streamlined cloud migration, and rapid identification of external security threats.

Cloud has become mainstream and today companies of all types are enjoying cloud success with solutions and services spanning the cloud stack.

AEG Presents, the live-entertainment division of Los Angeles-based AEG and the largest producer of music festivals in North America, chose the Pythian Kick Analytics as a Service solution to power its sophisticated, data-driven marketing operations. By integrating data from multiple sources, including financial, sales and marketing, with Pythian’s help, AEG can now get a 360° view of its customer experience and be able to identify opportunities to promote events to clients based on past purchases in an intelligent and timely way. This presentation is for enterprise/data architects, data analysts, and digital marketing analysts who would like to learn how to leverage the power of cloud for building and operating complex data platforms.

Cloud makes many processes easier and others harder. Find out what you need to know about staying in compliance with software licensing in an increasingly hybrid world.

As more and more organizations’ software infrastructure is being stretched between on-premise, public clouds, and hybrid clouds, maintaining compliance with software licensing is a more significant challenge than ever before. Sorting through all the FUD and getting straight answers from the vendors on the proper way to license software in this complicated world is not always easy. Some vendors have turned to software license audits as an easy way to generate additional revenue. This presentation discusses current software licensing trends in this cloud-fueled world, lessons learned, and steps every organization should take to stay in compliance.

Analytic processing––and the amount of data subject to analysis––is growing exponentially. Meanwhile, the amount of physical data center space isn’t keeping pace, and expansion of those environments is not becoming any more affordable. Find out where the cloud fits in.

The modern world of analytics abounds with cloud technologies that offer convenient, agile, and feature-rich approaches for running new analytic applications without requiring new investments in hardware, operating systems, or IT infrastructure. Jeschonek provides insights into how IT pros are leveraging the resources of the compute cloud to support assets running on premises without performance sacrifices or the need to rewrite existing file-based applications.

For the last 2 days, we've heard about exciting developments with technologies focused on the business uses for data, including machine learning, cloud computing, Hadoop, and, of course, cognitive computing. What we do with these technologies to advance business opportunities and avoid business risks is now up to each individual attendee. What are the takeaways that impact us?