Sponsor: IBM Corporation

Life revolves around prediction—for example, the route you take to get to work, whether to go on a second date, or whether or not to keep reading this sentence are all forms of prediction. Predicating our future is very much tied to progress. We use it to help us plan our lives so we can increase our likelihood of success. The problem is that the human mind cannot possibly process all of the insight flowing from big data. Machine learning is the answer to this problem, through its capacity to augment our decision making in the moment to deliver transformative business outcomes. We are already seeing machine learning powered by Apache Spark changing the face of innovation at IBM.

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IBM Cognos Analytics delivers a personal approach to analytics by empowering business users to solve individual or workgroup challenges on their own while providing IT with a proven solution that can be easily scaled as business needs grow.

What's new in IBM Cognos Analytics? - In October 2015, IBM announced a significant redesign of the user experience (UX) of its flagship business intelligence (BI) solution, IBM Cognos BI, based on self-service design principles. The new solution, called IBM Cognos Analytics, promises to bridge the divide between ad hoc, exploratory analytics and IT-driven traditional BI.

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As business grows more digital, the hunger for faster, more adaptive delivery of BI and analytics will increase. Read this Gartner paper and see how to give your business what it needs.

Mobility has changed the very nature of information technology. Users demand connectivity for a growing number and increasing variety of devices from laptop to smartphone, tablet and beyond. However, mobility presents challenges for securing users, networks and data. This Battlecard will provide key criteria to consider in each of the three phases of mobile security:

• 1. Beginning the mobile journey: Basics of securing devices and users
• 2. Encryption and the enterprise – what and how to raise your security profile
• 3. Providing full network access: Embracing mobility as part of an overall IT strategy

Where are you on your self-actualization scale for mobile?  This Battlecard, sponsored by IBM MaaS360 will help you prepare for secure access whether for must email, document sharing, or real-time interaction with peers and secure systems.

Even if you haven’t recognized it, you’ve benefited from deep learning. Deep learning is an advancement essential to cognitive computing, as it partners computers with humans to help businesses automate labor-intensive processes. This progressive approach allows for a more advanced interpretation of data, and the effects are astounding. With the growth of the Internet and the shift to online business, enterprises worldwide struggle everyday to make sense of the staggering amount of unstructured data. Deep learning offers a solution.

Learn How to Unlock the Hidden Value in Unstructured Data

A new generation of API provider is packing the power of PhD-grade science, natural language processing, deep learning, image recognition and the semantic Web into something as simple as a basic RESTful API call. This makes it possible for organizations of all types and sizes to benefit from the experience, expertise and intelligence of a team of PhDs—without having to actually find and employ them. How is this all possible? In this case study from ProgrammableWeb, you can see the source code behind one company’s API implementation.

Leading IT analyst firm Enterprise Management Associates (EMA) has just completed its latest survey-based research on DevOps and Continuous Delivery and will be presenting the results during this webinar. Momentum continues to build for these two timely topics, and the initial findings are confirming the links between accelerated software delivery and revenue growth, which was first revealed by the 2014 EMA research on these same topics.

Join Julie Craig, research director at EMA, to get highlights of this new research.

This white paper will discuss key tips for improving a release process and strengthening release management. Once the following practices are in order, the process can be enabled to keep up with the pace of Agile, and reduce the risks associated with rapid deployments.

IBM® BigInsights™ on Cloud provides Hadoop-as-a-service on IBM’s SoftLayer® global cloud infrastructure. It offers the performance and security of an on-premises deployment without the cost or complexity of managing your own infrastructure.

BigInsights is an industry standard Apache Hadoop offering that helps enterprises cost-effectively manage and analyze big data.

BigInsights on Cloud provides the following features and benefits:

• Managed operations provide 24 x 7 monitoring
• IBM Open Platform with current and stable Apache Hadoop components
• Dedicated bare metal nodes for enhanced performance, data privacy and security
• High value in-Hadoop analytics features, including Big SQL, Big Sheets, Text Analytics, Big R and Machine Learning

IBM DataWorks is a fully managed data preparation and movement service for IBM Cloud Data Services. It enables business analysts, developers, data scientists and engineers to put data to work with a simple yet powerful cloud based interface. DataWorks gives both technical and non-technical users across the enterprise a point and click solution to discover, cleanse, standardize, transform and move data in support of application development and analytic use cases.

In the domain of data science, solving problems and answering questions through data analysis is standard practice. Often, data scientists construct a model to predict outcomes or discover underlying patterns, with the goal of gaining insights. Organizations can then use these insights to take actions that ideally influence future outcomes for the better. The flow of IBM's data science methodology ensures that as data scientists learn more about the data and the modeling, they can return to a previous stage to make adjustments, iterate quickly and provide continuous value to the organization.

Life revolves around prediction—for example, the route you take to get to work, whether to go on a second date, or whether or not to keep reading this sentence are all forms of prediction. Predicating our future is very much tied to progress. We use it to help us plan our lives so we can increase our likelihood of success. The problem is that the human mind cannot possibly process all of the insight flowing from big data. Machine learning is the answer to this problem, through its capacity to augment our decision making in the moment to deliver transformative business outcomes. We are already seeing machine learning powered by Apache Spark changing the face of innovation at IBM.

Uptime isn’t everything; it’s the only thing. With recent IDC research demonstrating the average cost of a critical application failure at between $500K and $1M, the need to keep downtime at bay is clear. Unfortunately, the average number of deployments is expected to double over the next two years putting additional pressure on keeping application running.

This Battlecard looks at how DevOps-led project not only accelerate delivery and deployment, but also can have a positive, serious impact on application quality and uptime. It demonstrates how IBM DevOps tools enhance security and compliance, and what businesses should do today to eliminate downtime as part of a continuous application delivery process.