About Enterprise Analytics Online

Join us on October 18th, 2017, between 8:00 am and 2:30 pm Pacific Time.
This online event is a full day of live sessions presented by industry experts. The in-depth educational program is designed to teach anyone working with data to execute and implement a successful Data Analytics program. Presentations will focus on Data Science, Business Intelligence, Data Lakes and Warehouses, Machine Learning, Cognitive Computing, and the future of Analytics in the enterprise.

Agenda

AGENDA

8:00

Distinguishing Analytics, Business Intelligence & Data Science

Presented by Pragyansmita Nayak
Data Science is a journey — an exploration of data (both big and small) to identify patterns and trends, ask interesting questions, and prove hypotheses. As part of this information-explorer journey, you will have to navigate through the multiple terms and methodologies that mean "almost" the sam thing and yet have distinct characteristics. This talk will make you conversant with terms such as Data Analytics (sub-domains such as descriptive, predictive, prescriptive, and cognitive analytics), Business Intelligence, and Data Science (vs. data engineer).

9:00

Data Lake vs. Data Warehouse

Presented by Kelle O'Neal
Modern data analysis is moving beyond the Data Warehouse to the Data Lake, where analysts are able to take advantage of emerging technologies to manage complex analytics on large data volumes and diverse data types. Yet, for some business problems, a Data Warehouse may still be the right solution.

If you’re on the fence, join this session as we compare and contrast Data Lakes and Data Warehouses, identifying situations where one approach may be better than the other and highlighting how the two can work together.

Get tips, takeaways, and best practices about:
  • The benefits and problems of a Data Warehouse
  • How a Data Lake can solve the problems of a Data Warehouse
  • Data Lake Architecture
  • How Data Warehouses and Data Lakes can work together

  • 10:00

    Modern AI, from Machine Learning to Cognitive Computing

    Presented by Adrian Bowles
    In this session you will learn how Analytics tools and technologies can co-exist with Machine Learning, Deep Learning, and Cognitive Computing technologies to enable augmented and Artificial Intelligence applications.

    11:30

    Keynote: The Future of Analytics

    Presented by Nipa Basu
    Let’s start by acknowledging that the analytics revolution is a result of the technology revolution — disruptive analytics enabled by disruptive technology. Early developments in statistical/econometric theory were dominated by the need for efficient use of the scarce computing power, and thus scarce data. That problem has been turned on its head with our ability to crunch data at incredible speed: the Big Data revolution.

    In this keynote session, we will:
  • Identify a few areas where this big data is leading to incredible insight
  • Identify areas where big data is still primarily big data, and not YET big insight
  • Review current and future trends in the business world

  •  

    12:30

    Applied Machine Learning

    Presented by Charlie Vollmer
    Machine Learning is Business 2.0, simply put. Enterprises that utilize the applications and algorithms of Machine Learning are not just realizing the gains, they are revolutionizing their fields. From manufacturing and retail to travel, energy and healthcare, Machine Learning catalyzes growth, efficiency, and improvements.

    Gartner, McKinsey, and Accenture find that most large enterprises ($500m+) are crediting Machine Learning for improving marketing performance, increasing efficiency, and reducing customer churn. They also find that 80% of those companies are deploying Machine Learning for targeting and achieving higher sales growth.

    In this talk, we will explore the application and capability of Machine Learning in the financial industry for a nagging problem that has been getting attention for a long time, but has yet to be solved: credit card fraud. The Nilson Report estimates that in 2016 credit card fraud losses topped $25 billion worldwide. Barclays estimates 50% of all credit card fraud happens here in the U.S. We will build deep neural networks to predict consumer credit card fraud in real time, from point-of-sale transaction details. We will compare the performance of these models with other Machine Learning algorithms and explore the intricacies of this particular problem. We will look at the tools available to quickly prototype software utilizing these algorithms and explore the considerations of building enterprise-quality applications that take full advantage of their technological prowess.

    1:30

    How To Get the Most Value From Data Science Teams

    Presented by Cindi Thompson
    Organizing around data is a concern for the whole business. The myth of the lone ranger data scientist is very much that. But how do you incorporate data scientists into the team? Cindi will share experiences from three years of effectively deploying Data Science in enterprise organizations. She will share insights into hiring, managing, and organizing Data Science teams.

    Sponsors

    Interested in sponsoring this online event?
    Contact Warwick Davies by email: warwick@dataversity.net or phone: 1-781-354-0119.

    Become a Sponsor

    FAQ

    Here are a few good reasons why you should register:
  • Registration is free
  • Six, 40-minute webinars
  • Learn from the best in the industry
  • Experience-based learning
  • Access to all recorded sessions, slides, and materials presented
  • Live Q&A following each webinar session
  • It's OK if you can't attend the live event on October 18, 2017. Register and you will get access to the recordings of all the presentations and links to download the slides.
    Yes, we produce several face-to-face events around the country. DATAVERSITY is home to many educational events, online training options, webinars, white papers, articles, and blogs. We're proud to offer the worldwide data community so many educational opportunities both online and face-to-face. To learn more about what we do, visit dataversity.net.
    No, you do not need to pay anything to watch the live sessions presented during this event. When you register, we also give you free access to the on demand recordings a couple of days after the event.
    You should receive your login details immediately following your registration. We also send login info the day before the live event and the morning of in case you've misplaced it.
    DATAVERSITY Education, LLC is an educational and publishing resource for business and Information Technology (IT) professionals on the uses and management of data. Our team strives to provide high-quality educational resources to our worldwide community of practitioners, experts, and developers who participate in and benefit from face-to-face hosted conferences, live webinars, white papers, online training, daily news, articles and blogs, and much more.

    Contacts

    Copyright © 2017 DATAVERSITY Education, LLC. All Rights Reserved.

    info@dataversity.net

    1 (310) 337-2616

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