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Business Intelligence and Analytics

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  • How AI is Transforming the World of Analytics
    How AI is Transforming the World of Analytics Andrew Yeung, Sr. Director of Product Marketing, ThoughtSpot Recorded: Dec 14 2017 47 mins
    Artificial Intelligence is a transformative capability that promises immense business potential—especially when infused in data analytics.

    Join ThoughtSpot to learn best practices for leveraging AI as a key enabler for analytics. We’ll discuss how to best understand and manage the potential opportunities and risks involved.
  • RIDE Containerized Data Science IDE server For Enterprise
    RIDE Containerized Data Science IDE server For Enterprise Ali Marami, Data Science Advisor at R-Brain Recorded: Dec 14 2017 45 mins
    RIDE is an all-in-one, multi-user, multi-tenant, secure and scalable platform for developing and sharing Data Science and Analytics, Machine Learning (ML) and Artificial Intelligence (AI) solutions in R, Python and SQL.

    RIDE supports developing in notebooks, editor, RMarkdown, shiny app, Bokeh and other frameworks. Supported by R-Brain’s optimized kernels, R and Python 3 have full language support, IntelliSense, debugger and data view. Autocomplete and content assistant are available for SQL and Python 2 kernels. Spark (standalone) and Tesnsorflow images are also provided.

    Using Docker in managing workspaces, this platform provides an enhanced secure and stable development environment for users with a powerful admin control for controlling resources and level of access including memory usage, CPU usage, and Idle time.

    The latest stable version of IDE is always available for all users without any need of upgrading or additional DevOps work. R-Brain also delivers customized development environment for organizations who are able to set up their own Docker registry to use their customized images.

    The RIDE Platform is a turnkey solution that increases efficiency in your data science projects by enabling data science teams to work collaboratively without a need to switch between tools. Explore and visualize data, share analyses, all in one IDE with root access, connection to git repositories and databases.
  • How to build a successful analytics culture in your organisation
    How to build a successful analytics culture in your organisation Andy Kriebel, Eva Murray, Paul Banoub, Emma Whyte, Josh Tapley, Simon Beaumont Recorded: Dec 14 2017 91 mins
    Hear from our expert panel how they built a strong analytics culture in their organisations to enable data-driven decision-making.

    We have invited Paul Banoub (UBS, United Kingdom), Emma Whyte (The Information Lab, United Kingdom), Simon Beaumont (NHS), and Josh Tapley (ComCast, United States) to discuss the following topics with us:
    -How to find talented people and how to keep them engaged, challenged and motivated
    -How to establish the right environment with processes and systems that foster innovation, learning, collaboration and analytical excellence
    -How to setup best practices and governance while staying responsive to the organisation's need for information and insights RIGHT NOW
    -How to make self-service analytics a success

    During the panel discussion you have the chance to ask questions and get answers from our experts.

    Presenters: Andy Kriebel, Head Coach at The Data School & Eva Murray, Head of BI and Tableau Evangelist at Exasol
    Panel: Paul Banoub (Director, Analytics as a Service at UBS Investment Bank), Emma Whyte (Head of Centre of Excellence and Customer Advocacy at The Information Lab), Josh Tapley (Director, Data Visualization at Comcast)
  • Enterprise Analytics Journey, the IBM point of view for IBM Z customers
    Enterprise Analytics Journey, the IBM point of view for IBM Z customers Hélène Lyon, IBM, Distinguished Engineer, IBM Z Solutions Architect Recorded: Dec 14 2017 41 mins
    IT is a key player in the digital and cognitive transformation of business processes delivering solutions for improved business value with analytics. This session will step by step explain the journey to secure production while adopting new analytics technologies leveraging mainframe core business assets
  • Big Data Analytics vs Privacy: Risks and Opportunities
    Big Data Analytics vs Privacy: Risks and Opportunities Rob Anderson, Head of Field Operations (Privitar),Tim Hickman, Associate (White & Case) Recorded: Dec 14 2017 58 mins
    Today's modern businesses gain competitive edge and remain innovative by using advanced analytics and machine learning. Utilising big data can build customer loyalty by improving personalised marketing campaigns; optimises fraud detection; and improves products and services by advanced testing. However, the data sets required for advanced analytics are often sensitive, containing personal customer information, and therefore come with an inherent set of privacy risks and concerns.

    This roundtable will cover a few key questions on data utility and privacy:

    - In what ways advanced analytics help businesses gain competitive edge?

    - What is defined as sensitive data?

    - Will GDPR affect the way you're allowed to use customer data?

    - What opportunities are there to utilise sensitive data?

    Unlocking the data’s true value is a challenge, but there are a range of tools and techniques that can help. This live discussion will focus on the data analytics landscape; compliance considerations and opportunities for improving data utility in 2018 and beyond.

    Key takeaways:

    - A view of the data protection landscape

    - How to remaining compliant with GDPR when using customer data

    - Use cases for advanced analytics and machine learning

    - Opportunities for maximising data utility in 2018
  • Mixed Reality - Market Potential and Use Cases
    Mixed Reality - Market Potential and Use Cases Adnyesh Dalpati, Solutions Architect Recorded: Dec 14 2017 37 mins
    Mixed reality is the result of blending the physical world with the digital world. Though it is relatively new technology and its adoption is still in initial stages. Mixed Reality devices and applications are projected to be the next technological era after smart phones.

    The webinar will give a brief on Mixed Reality Potential Usecases those provide an immersive experience but also revenues streams to the creators.
  • Data Fabric: A New Paradigm For Self-Service Data & Data Scientists
    Data Fabric: A New Paradigm For Self-Service Data & Data Scientists Kelly Stirman, VP Strategy, Dremio Recorded: Dec 12 2017 45 mins
    Data Scientists are rare and highly valued individuals, and for good reason: making sense of data, and using the machine learning libraries requires an unusual blend of advanced skills. Why is it then that Data Scientists spend the majority of their time getting data ready for models, and a fraction actually doing the high value work?

    In this talk we introduce the concept of Data Fabric, a new way to provide a self-service model for data, where data scientists can easily discover, curate, share, and accelerate data analysis using Python, R, and visualization tools, no matter where the data is managed, no matter the structure, and no matter the size.

    We will talk through the role of Apache Arrow, the in-memory columnar data standard that is accelerating analytics for GPU-based processing, as well as the role of Pandas and Arrow in providing unprecedented speed in accessing datasets from Python.
  • Quality & Testing SIG Talk Introduction
    Quality & Testing SIG Talk Introduction Richard Bishop, Todd DeCapual, Chris Trimper Recorded: Dec 12 2017 68 mins
    Vivit launches their first ever SIG Talk event with three speakers who will give you insights into StormRunner Functional, Dynamic data handling in performance tests as well as AI and machine learning as it applies to testing.

    We will discuss:

    How StormRunner Functional is the latest functional test offering from Micro Focus. In this session, Chris Trimper, an early adopter and beta tester, will share his experiences with this new product

    How Virtual Table Server (VTS), in days of Mercury Interactive, was the often-overlooked repository for dynamically updated real-time test data. Even after a revamp and relaunch in 2014, many people still don't use it, but they should. Richard's VTS demo will help you to get value from this great add-on for LoadRunner and Performance Center

    How Big Data, Artificial Intelligence and Machine learning are rapidly impacting businesses and customers, enabling another massive shift through technology enablement. In this session, Todd DeCapua will share how these capabilities are being leveraged in Performance Engineering now, and into the future.
  • The Human Role in AI
    The Human Role in AI Peter Bruce, President and Founder, The Institute for Statistics Education at Statistics.com Recorded: Dec 12 2017 36 mins
    Artificial Intelligence (AI) is a hot topic, and there is widespread alarm that AI will replace humans in the analytical process. Adam Selipsky, the CEO of Tableau, terms this a myth, and said recently that AI's role will remain that of an assistant to the analytics professional.

    In this talk we go beyond that, and look at some interesting aspects of the human role as an integral component of machine learning and statistical modeling.

    We discuss how human expertise "supervises" machine learning, how reliance on multiple sources can deliver surprising expertise, and when that system can go wrong.
  • AI in social housing
    AI in social housing Vicki Howe, Head of Product Development, HouseMark; Jason Lee, CEO, illumr Recorded: Dec 12 2017 18 mins
    This session explores what artificial intelligence can add to data analysis in the social housing sector. Is it better than traditional statistical techniques?

    HouseMark is the leading provider of data analysis and insight solutions to social housing providers. Illumr took part in HouseMark’s accelerator programme introducing innovative technology start-ups to the social housing sector. HouseMark have worked with illumr to test out the appetite for AI and explore what insights can be gained using data typically held by social housing providers.

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