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Big Data Management

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  • Embracing the Data Revolution - What to Expect at Big Data LDN 2018
    Embracing the Data Revolution - What to Expect at Big Data LDN 2018
    Richard Corderoy, Oakland Data & Analytics | Andy Mott, Arcadia Data Recorded: Nov 8 2018 60 mins
    With just a few weeks to the UK's largest data & analytics event, we've gathered some of the elite speakers who will be taking the stage to debate the latest trends, hottest solutions and the biggest opportunities (and challenges) for businesses in a data-driven world.

    * Fast Data & DataOps
    * Self-Service Analytics
    * Artificial Intelligence
    * Customer Experience
    * Data Governance

    What will they be talking about at The Olympia, London, on the 13-14 November 2018, what do they want to hear about, what are they looking forward to?

    Join this panel discussion and arm yourself for excellence in this brave new data-driven world.

    Richard Corderoy, Chief Data Officer, Oakland Data and Analytics
    Andy Mott, Senior Consultant, Arcadia Data
  • Flash Storage with 24G SAS Leads the Way in Crunching Big Data
    Flash Storage with 24G SAS Leads the Way in Crunching Big Data
    Greg McSorley, Amphenol; Rick Kutcipal, Broadcom; Kevin Marks, Dell; Jeremiah Tussey, Microsemi Recorded: Oct 24 2018 49 mins
    The recent data explosion is a huge challenge for storage and IT system designers. How do you crunch all that data at a reasonable cost? Fortunately, your familiar SAS comes to the rescue with its new 24G speed. Its flexible connection scheme already allows designers to scale huge external storage systems with low latency. Now the new high operating speed offers the throughput you need to bring big data to its knobby knees! Our panel of storage experts will present practical solutions to today’s petabyte problems and beyond.
  • How to Leverage Big Data for Customers: Lessons from a Purpose-Driven Bank
    How to Leverage Big Data for Customers: Lessons from a Purpose-Driven Bank
    Paul Clark, CTO, Tandem Recorded: Jul 17 2018 42 mins
    For years, banks have been sitting on a goldmine of customer data. Only recently have they started exploiting that, although not surprisingly for their own benefit.
    Personal data can give great insights to drive bank outcomes by decreasing credit losses and reducing fraud losses. In this webinar Paul Clark, CTO, will look at how we can use customer data to;
    * Drive customer’s own advantage
    * Avoid slip ups
    * Dodge nasty charges
    * Optimise the customer’s finances end to end.
  • Semantic AI: Bringing Machine Learning and Knowledge Graphs Together
    Semantic AI: Bringing Machine Learning and Knowledge Graphs Together
    Kirk Borne, Principal Data Scientist, Booz Allen Hamilton & Andreas Blumauer, CEO, Managing Partner Semantic Web Company Recorded: May 23 2018 64 mins
    Implementing AI applications based on machine learning is a significant topic for organizations embracing digital transformation. By 2020, 30% of CIOs will include AI in their top five investment priorities according to Gartner’s Top 10 Strategic Technology Trends for 2018: Intelligent Apps and Analytics. But to deliver on the AI promise, organizations need to generate good quality data to train the algorithms. Failure to do so will result in the following scenario: "When you automate a mess, you get an automated mess."

    This webinar covers:

    - An introduction to machine learning use cases and challenges provided by Kirk Borne, Principal Data Scientist at Booz Allen Hamilton and top data science and big data influencer.
    - How to achieve good data quality based on harmonized semantic metadata presented by Andreas Blumauer, CEO and co-founder of Semantic Web Company and a pioneer in the application of semantic web standards for enterprise data integration.
    - How to apply a combined approach when semantic knowledge models and machine learning build the basis of your cognitive computing. (See Attachment: The Knowledge Graph as the Default Data Model for Machine Learning)
    - Why a combination of machine and human computation approaches is required, not only from an ethical but also from a technical perspective.
  • Audit Ex Machina: Digital Learning Systems and Transactional Data
    Audit Ex Machina: Digital Learning Systems and Transactional Data
    Erik McBain, Strategic Account Manager, MindBridge Ai, Recorded: May 17 2018 44 mins
    How are financial service firms around the world using machine learning systems today to identify and address risk in transactional datasets?

    This webinar will look at a new approach to transaction analysis and illustrate how the combination of traditional rules-based approaches can be augmented with next-generation machine learning systems to uncover more in the data, faster and more efficiently.

    We will span the various applications in banking, payments, trading, and compliance; looking at a variety of use cases from bank branch transaction analysis to trading data validation.

    Anyone interested in financial technology, next-generation machine learning systems and the future of the financial services industry will find this webinar of specific interest.

    About the speaker:
    Erik McBain, CFA is a Strategic Account Manager for MindBridge Ai, where he specializes in the deployment of emerging technologies such as artificial intelligence and machine learning systems in global financial institutions and corporations. Over his 10-year career in banking and financial services(Deutsche Bank, CIBCWM, Central Banking), Erik has been immersed in the trading, analysis, and sale of financial instruments and the deployment of new payment, banking and intelligent technologies. Erik's focus is identifying the various opportunities created through technological disruption, creating partnerships, and applying a client-centered innovation process to create transformative experiences, products, and services for his clients.
  • The Teslification of Banking: The Role of Ethical AI in Sustainable Finance
    The Teslification of Banking: The Role of Ethical AI in Sustainable Finance
    Richard Peers, Director Financial Services Industry, Microsoft Recorded: May 17 2018 37 mins
    Artificial Intelligence has a huge role to play in banking, no more so than in sustainable finance. However, data is very patchy and much source data is not available to inform Sustainable Finance. The challenge as we set off on this new journey is to make sure that the data and algorithms used are transparent and unbiased.

    In this session, Richard Peers, Director of Financial Services industry at Microsoft will share how disruption and new entrants are bringing new business models and technology to play in banking as in other industries like the Auto Industry

    One new area is sustainable Finance, a voluntary initiative as part of the COP agreement on climate change but the data to inform the markets is a challenge. Big Data, Machine Learning and AI can help resolve this.

    But with such important issues at stake, this session will outline how AI much be designed to ethical principles

    Tune in to this session for a high-level view of some key trends and technologies in banking. Get insight into sustainable finance; why AI can help and why Ethical AI is important; and the Microsoft principles for Ethical AI.
  • Network Telemetry & Analytics in the Age of Big Data & AI
    Network Telemetry & Analytics in the Age of Big Data & AI
    Ruturaj Pathak, Senior Product Manager, Networking BU, Inventec Recorded: May 15 2018 35 mins
    We are seeing a sea change in networking. SDN has enabled improvements in network telemetry and analytics.

    In this presentation, I will talk about the current challenges that are out there and how the technology change is helping us to improve the overall network telemetry. Furthermore, I will share how deep learning techniques are being used in this field. Please join this webinar to understand how the field of network telemetry is changing.
  • Open Banking - Data, Analytics and the Tragedy of the Commons
    Open Banking - Data, Analytics and the Tragedy of the Commons
    Dr Louise Beaumont (techUK), Natasha Kyprianides (Hellenic Bank), Tony Fish (AMF Ventures), Katrina Cruz (Anthemis Group) Recorded: May 15 2018 59 mins
    The tragedy of the commons, first described by biologist Garrett Hardin in 1968, describes how shared resources are overused and eventually depleted. He compared shared resources to a common grazing pasture; in this scenario, everyone with rights to the pasture acting in self-interest for the greatest short-term personal gain depletes the resource until it is no longer viable.

    The banking ecosystem and the data that binds it together is not all that different. For many years, through miss-selling scandals, cookie cutter products and dumb mass-marketing have seen players acting in their own interest in accordance to what they believe the ecosystem should look like, how it should evolve and who controls it.

    But with the introduction of open banking, there are signs that new banking ecosystems are set to thrive. Taking Hardin’s notion, collaboration in the open banking future could benefit everyone in the ecosystem – the traditional banks, the FinTechs, the tech titans with their expertise in delivering services at scale, and yet-to-be-defined participants, likely to include the large data players such as energy firms, retailers and telcos.

    Join me to explore the Open Future.
  • Having fun with Raspberry(s) and Apache Projects
    Having fun with Raspberry(s) and Apache Projects
    Jean-Frederic Clere, Manager, Software Engineering, Red Hat Recorded: Mar 29 2018 49 mins
    You can do a lot with a Raspberry and ASF projects. From a tiny object
    connected to the internet to a small server application. The presentation
    will explain and demo the following:

    - Raspberry as small server and captive portal using httpd/tomcat.
    - Raspberry as a IoT Sensor collecting data and sending it to ActiveMQ.
    - Raspberry as a Modbus supervisor controlling an Industruino
    (Industrial Arduino) and connected to ActiveMQ.
  • Comparing Apache Ignite & Cassandra for Hybrid Transactional Analytical Apps
    Comparing Apache Ignite & Cassandra for Hybrid Transactional Analytical Apps
    Denis Magda, Director of Product Management, GridGain Systems Recorded: Mar 28 2018 61 mins
    The 10x growth of transaction volumes, 50x growth in data volumes and drive for real-time visibility and responsiveness over the last decade have pushed traditional technologies including databases beyond their limits. Your choices are either buy expensive hardware to accelerate the wrong architecture, or do what other companies have started to do and invest in technologies being used for modern hybrid transactional analytical applications (HTAP).

    Learn some of the current best practices in building HTAP applications, and the differences between two of the more common technologies companies use: Apache® Cassandra™ and Apache® Ignite™. This session will cover:

    - The requirements for real-time, high volume HTAP applications
    - Architectural best practices, including how in-memory computing fits in and has eliminated tradeoffs between consistency, speed and scale
    - A detailed comparison of Apache Ignite and GridGain® for HTAP applications

    About the speaker: Denis Magda is the Director of Product Management at GridGain Systems, and Vice President of the Apache Ignite PMC. He is an expert in distributed systems and platforms who actively contributes to Apache Ignite and helps companies and individuals deploy it for mission-critical applications. You can be sure to come across Denis at conferences, workshop and other events sharing his knowledge about use case, best practices, and implementation tips and tricks on how to build efficient applications with in-memory data grids, distributed databases and in-memory computing platforms including Apache Ignite and GridGain.

    Before joining GridGain and becoming a part of Apache Ignite community, Denis worked for Oracle where he led the Java ME Embedded Porting Team -- helping bring Java to IoT.

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