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Whitepapers and resources on implementation, optimisation, strategy, products and more

Open Source Software: Security Risks and Best Practices




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Up to 80% of the source code in many new commercial and enterprise applications is open source software (OSS). OSS allows developers to build apps faster but may also introduce risk to organizations through security vulnerabilities in the libraries. This paper examines steps you can take to mitigate these risks and will help engineering and security teams work together to build and enforce best practices in the selection, use, and monitoring of open source components.

Sponsor: Rogue Wave

   

Static Code Analysis in an Agile World




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To keep pace with ever-increasing customer demands on software functionality and time-to-market expectations, software developers are having to develop higher quality code faster. As a result, Agile development is becoming more common. However, to fully realize the benefits of Agile, a repeatable process for ensuring code is free of defects and security vulnerabilities is critical. This paper examines how source code analysis can enhance the Agile development process and empower Agile teams.

Sponsor: Rogue Wave

   

Challenging Some of the Myths About Static Code Analysis




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Every developer wants to write good code – code they can be proud of. Good static analysis tools will actually help you identify and address code problems faster. This guide provides four common myths about static code analysis, which serve mostly to distort the true value static analysis can bring to your software development lifecycle. Download this whitepaper to learn about the truths to these myths, and how easily you can write code that you’ll be proud of.

Sponsor: Rogue Wave

   

Follow the Money: Big Data ROI and Inline Analytics




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Wikibon conducted in-depth interviews with organizations that had achieved Big Data success and high rates of returns. These interviews determined an important generality: Big Data winners focused on operationalizing and automating their Big Data projects. They used Inline Analytics to drive algorithms that directly connected to and facilitated automatic change in the operational systems-of-record. These algorithms were usually developed and supported by data tables derived using Deep Data Analytics from Big Data Hadoop systems and/or data warehouses. Instead of focusing on enlightening the few with pretty historical graphs, successful players focused on changing the operational systems for everybody and managed the feedback and improvement process from the company as a whole. If you are ready to be a Big Data winner, download this report today.

Sponsor: IBM

   

Big Data: Why Transaction Data is Mission Critical to Success




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In this report, analyst Mike Ferguson of Intelligent Business Strategies writes about the enhanced role of transactional DBMS systems in today's world of Big Data. Discover how Big Data provides richer transactional data and how that data is captured and analyzed to meet tomorrow’s business needs. You'll learn about: - Making insights available to the right people at the right time - Using transactional data to deliver greater ROI on your investment in Big Data systems - Combining relational and NoSQL transaction data to provide real-time analytics and deliver business value If you are ready to begin making the most of your Big Data systems, download the report today.

Sponsor: IBM

   


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