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Business Intelligence and Analytics

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  • From Data with Love: How the data economy is impacting the insurance sector
    From Data with Love: How the data economy is impacting the insurance sector JS Gourevitch, Luca Schnettler, Petra Wildermann, Anil Celik, Thomas Lethenborg Recorded: Nov 20 2017 60 mins
    The data economy and digital technologies are deeply transforming almost all areas of our lives. One of the most heavily transformed revolve around insurance and healthcare with a number of really interesting development possibly redefining the way we take care of ourselves and the way we consumer and use insurance as well.

    From harnessing the power of data to better help mental health patients, carers and medical personnel with their treatments to assessing the risk of developing broad range of illnesses and engaging better with users to propose them personalised healthy life plans to using big data and analytics to track down and prepare for epidemics to using data to better cover cars and drivers with car insurances and finally using social media data for insurers to better engage with customers, this webinar will propose a fascinating exploration of the opportunities, risks, new models supporting the digital transformation in banking.

    Moderated by Jean-Stéphane Gourévitch
    With:
    Luca Schnettler, CEO and Founder, HealthyHealth (UK)
    Petra Wildermann, Business Development Director, Metabiota (Switzerland)
    Anil Celik, Co-founder and CEO Urbanstats (US)
    Thomas Lethenborg, CEO, Monsenso (Denmark)
  • IOT Future Roadmap - Adoption & Standardization
    IOT Future Roadmap - Adoption & Standardization Adnyesh Dalpati, Solutions Architect Recorded: Nov 10 2017 46 mins
    Internet of Things (IoT) envisions that everything in the physical world is connected seamlessly and is securely integrated through Internet. New products are innovated under the umbrella of IOT and opening up different opportunities. This webinar will discuss the future potential of IOT and the trend in which it is moving in adoption and standardisation.
  • Predicting Football Results With Statistical Modelling
    Predicting Football Results With Statistical Modelling David Sheehan, Senior Customer Scientist, MoneySuperMarket Recorded: Nov 9 2017 64 mins
    Football (or soccer to any American readers) is full of clichés: “It’s a game of two halves”, “taking it one game at a time” and “Liverpool have failed to win the Premier League”. You’re less likely to hear “Treating the number of goals scored by each team as independent Poisson processes, statistical modelling suggests that the home team have a 60% chance of winning today”.

    This webinar will introduce some basic statistical models that have been devised to predict the results of football matches. It won't help you make lots of money, but you will learn about programming, statistics and modelling through this fun intuitive topic.
  • Setting up BI in FinTech companies: challenges and opportunities
    Setting up BI in FinTech companies: challenges and opportunities Mari Hermanns, Head of Business Intelligence at Solaris Bank Recorded: Nov 2 2017 48 mins
    Today most companies collect more data than ever and as we all know: data is the new oil. However gaining insights and turning them into action is easier said than done. In my experience this is a challenge for many companies, including innovative FinTechs.

    In order to create a data driven business and organisational culture it is important to integrate data collection and an appreciation for data driven truth from the starting of a venture. This webinar is a brief overview of the hurdles and challenges BI faces in growing FinTech companies and how they can be overcome. Furthermore this webinar will briefly mention new BI trends and tools and how they could impact businesses.
  • Effective High-Speed Multi-Tenant Data Lakes
    Effective High-Speed Multi-Tenant Data Lakes Sean Suchter, CTO and founder, Pepperdata Recorded: Oct 25 2017 45 mins
    Big Data has increased the demand for big data management solutions that operate at scale and meet business requirements. Big Data organizations realize quickly that scaling from small, pilot projects to large-scale production clusters involves a steep learning curve. Despite tremendous progress, critically important areas including multi-tenancy, performance optimization, and workflow monitoring remain areas where the operations team still needs management help.

    Intended for enterprises who already have a data lake or are setting up their first data lake, this presentation will discuss how to implement data lakes with operations tools that automatically optimize clusters with solutions for monitoring, performance tuning, and troubleshooting in production environments.

    Sean is the co-founder and CTO of Pepperdata. Previously, Sean was the founding GM of Microsoft’s Silicon Valley Search Technology Center, where he led the integration of Facebook and Twitter content into Bing search. Prior to Microsoft, Sean managed the Yahoo Search Technology team, the first production user of Hadoop. Sean joined Yahoo through the acquisition of Inktomi, and holds a B.S. in Engineering and Applied Science from Caltech.
  • Three Ways To Accelerate Your Data Lake Migration To Cloud
    Three Ways To Accelerate Your Data Lake Migration To Cloud Kelly Stirman, VP Strategy, Dremio Recorded: Oct 25 2017 45 mins
    Public cloud deployments have become irresistible in terms of flexibility, low barriers to entry, security, and developer friendliness. But the sheer inertia of traditional data lakes make them difficult to transition to cloud. In this talk we'll look at examples of how leading companies have made the transition using open source technologies and hybrid strategies.

    Instead of following a "lift and shift" strategy for moving data lake workloads to the cloud, there are new considerations unique to cloud that should be considered alongside traditional approaches related to compute (eg, GPU, FPGA), storage (object store vs. file store), integrations, and security.

    Viewers will take away techniques they can immediately apply to their own projects.
  • Becoming Data Driven: Building the Foundation of Digital Success
    Becoming Data Driven: Building the Foundation of Digital Success Nigel Turner Recorded: Oct 25 2017 54 mins
    Many organisations aspire to become digital, data driven enterprises. In these organisations data is viewed as a critical asset, both to generate new digitally based products and services, and to guide and improve business operations and decision making. But many companies are failing to live up to this aspiration. They struggle to develop and implement data strategies that align with, and help to deliver, new business strategies.


    This webinar will explore what becoming ‘data driven’ really means, examines some of the reasons why many organisations are failing to realise their ambitions, and propose ways of overcoming the challenges. Key to these is a strong emphasis on the increasingly critical importance of established data management disciplines, especially Data Governance, Data Quality and MDM, which all have a critical role to play in the digital business of the future.

    This session will explore:


    •What is a data driven organisation and how does it differ from a traditional company?
    •The main challenges of creating a data driven organisation
    •Building a data driven capability - the role of business and IT
    •The central importance of a business aligned Data Strategy and how to achieve it
    •Why a successful data strategy needs an integrated focus on Data Governance, Data Quality and MDM
  • Designing Data Lakes: Architecture options with open source tools
    Designing Data Lakes: Architecture options with open source tools Maloy Manna, PM Engineering, AXA Data Innovation Lab, Paris Recorded: Oct 25 2017 63 mins
    The concept of Data lakes evolved to address challenges and opportunities in managing big data.

    Organizations are investing massive amounts of time and money to upgrade existing data infrastructures and build data lakes whether on-premises or in the cloud.

    This talk will discuss architectures and design options to implement data lakes with open source tools. Also covered are challenges of upgrade & migration from existing data warehouses, metadata management, supporting self-service and managing production deployments.
  • Virtual Data Lake: A Reality
    Virtual Data Lake: A Reality Hélène Lyon, IBM, Distinguished Engineer, IBM Z Solutions Architect Recorded: Oct 25 2017 42 mins
    As an Enterprise customer, you are potentially using IBM Z in a hybrid cloud implementation. Let's understand how to benefit from cloud access to mainframe data without moving it outside z; thereby improving security, reducing integration challenges and answering your GDPR auditor's needs.
  • Bias in the Web
    Bias in the Web Ricardo Baeza-Yates, CTO, NTENT; ACM Fellow; IEEE Fellow Recorded: Oct 24 2017 52 mins
    The Web is the most powerful communication medium and the largest public data repository that humankind has created. Its content ranges from great reference sources such as Wikipedia to ugly fake news. Indeed, social (digital) media is just an amplifying mirror of ourselves. Hence, the main challenge of search engines and other websites that rely on web data is to assess the quality of such data. However, as all people have their own biases, web content, as well as our web interactions, are tainted with many biases.

    Data bias includes redundancy and spam, while interaction bias includes activity and presentation bias. In addition, sometimes algorithms add bias, particularly in the context of search and recommendation systems. As bias generates bias, we stress the importance of de-biasing data as well as using the context and other techniques such as explore & exploit, to break the filter bubble.

    The main goal of this talk is to make people aware of the different biases that affect all of us on the Web. Awareness is the first step to be able to fight and reduce the vicious cycle of bias.

    Ricardo Baeza-Yates areas of expertise are web search and data mining, information retrieval, data science, and algorithms. He is CTO of NTENT, a semantic search technology company based in California, USA since 2016. Before, he was VP of Research at Yahoo Labs, based first in Barcelona, Spain, and later in Sunnyvale, California, from January 2006 to February 2016. He also is part time Professor at DTIC of the Universitat Pompeu Fabra, in Barcelona, Spain, as well as at DCC of Universidad de Chile in Santiago.

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