About Enterprise Analytics Online

Enterprise Analytics Online will cover key strategies and share how Analytics-driven professionals have overcome their data challenges. Tap into the combined expertise of several industry-leading professionals and hundreds of data peers during this day of live, webinar-style sessions.
Registration is free and gives you access to the sessions presented throughout the day, the live Q&A with the speakers, and all recorded presentations and materials.

The Agenda

AGENDA

8:00

Roles in Enterprise Analytics

Presented by Evan Terry
We will kick off the conference looking at the roles involved in Enterprise Analytics today, from analysts to data scientists to chief analytics officers. Bombarded with a constant release of new technology in this space, how are roles affected within businesses analyzing volumes of data in real time? How are job descriptions evolving and what jobs are companies looking to fill?

9:00

How to Succeed with Self-Service Analytics: Organizational, Architectural, and Governance Issues

Presented by Wayne W. Eckerson
Self-Service Analytics has been the holy grail of Business Intelligence (BI) leaders for the past two decades. Although analytical tools have improved significantly, it is notoriously difficult to achieve the promise of Self-Service Analytics. This session will explain how to empower business users to create their own reports without creating data chaos. Specifically, it examines seven factors for leading a successful BI program: right roles, right processes, right tools, right organization, right architecture, right governance, and right leadership. Ultimately, it will show how to build a self-sustaining analytical culture that balances speed and standards, agility and architecture, and self-service and governance.

You Will Learn:

  • Trends and business dynamics driving Analytics adoption
  • The conundrum of Self-Service Analytics
  • Success factors for leading a successful BI program
  • How to survive and thrive in the new world of Big Data Analytics
  • How to increase user adoption and facilitate self service
  • 10:00

    Ushering in the Age of Machine Learning

    Presented by Kristen Serafin & Lizzie Westin
    Machine Learning is being implemented across our enterprise to further leverage the potential of existing data assets to help solve problems in innovative ways. Teams across the enterprise have come together to learn about Artificial Intelligence and Machine Learning, experiment, and collaborate to implement many pilot projects/POCs. But how did Machine Learning get from being just an idea to a concerted effort that led to a subsequent culture shift across departments? Learn how FINRA hit the ground running with ML by facilitating cross-department communication, getting staff the proper support and training, and identifying and prioritizing opportunities for implementation.

    Attendees will learn:

  • How to identify use cases for Machine Learning and determine their viability
  • How to leverage existing datasets for labeling and use in ML-Models
  • Techniques to empower and support staff to build necessary skillsets to work in an ML environment
  • Approaches to gain support from and partner with the business
  • 11:00

    Break

    We will return at 11:30 AM Pacific for the Keynote, Trends in Enterprise Analytics.

    11:30

    Keynote: Trends in Enterprise Analytics

    Presented by Pragyansmita Nayak
    Enterprises globally recognize the emerging trend in data and analytics-focused applications and predict their investments will continually increase over the coming years. Corporations are depending on their Chief Data X (Scientist/Officer) to tactfully identify the right opportunities and grow the team strategically. The characteristics of the data are as diverse as the different domains with unexplored problems – broadly categorized into the three categories of structured, unstructured, and semi-structured data. Data Fusion for DataOps (not a typo for DevOps!) is critical for added advantage and effective Self-Service Analytics (and so many more – Descriptive, Predictive, Prescriptive, Cognitive, Domain Informatics, Infographics).

    If you are just starting to consider data application, it is important to first set goals and define expected outcomes. Scientific databases following the mantra of defining "five questions" to focus the effort is a good start. This will additionally help foresee the need for Algorithmic Orchestration to accomplish the desired goals of Machine Learning and Deep Learning-based projects. "Everything is a GRAPH" – or a relational database – think about the different possibilities and define the problem scope early on.

    As Data Scientists are working towards defining and solving a problem, specifically as the field is becoming more accessible with increased access to data, storage, and computing resources, they should not lose sight of the associated management needs – data ethics, model explainability, and Data Governance and lineage. We do need Data Analytics to solve our own problems as well – a recursive "Graph Analytics application for Analytics of Analytics"!! As complex as everything appears, we should not forget the power of KISS (Keep it Simple) – Occam's Razor should be prime.

    12:30

    Databases vs. Hadoop vs. Cloud Storage

    Presented by William McKnight
    Relational databases are old technology, right? Thirty years is a long time for a technology foundation to be as active as relational databases, but, like NFL coaches, we must “tolerate them until we can replace them.” Are their replacements here? In this session, we say no.

    Databases did not sit around while Hadoop emerged. The Hadoop era generated a ton of interest and confusion, but is it still relevant as organizations are deploying cloud storage options like a kid in a candy store? We’ll discuss Hadoop’s continued potential relevance and the cloud storage option that seems vital. Use what when? This is a critical decision that can dictate two to five times additional work effort if it’s a bad fit.

    Drop the herd mentality. In reality, there is no “one size fits all” right now. We need to make our platform decisions against this backdrop. This session will distinguish these analytic deployment options and help you platform for success.

    The Sponsors

    Interested in sponsoring? 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
  • There are five, 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. 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. Visit dataversity.net to learn more.

    Contact Us

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