Dataware Symposium Seattle

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W Seattle

1112 4th Ave

Seattle, WA 98101

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Dataware Symposium Seattle:

One secret ingredient to solve for your three biggest data challenges.

If you're like most organizations, you're struggling to solve for three big data challenges along your AI and analytics journey:

1) Feeding data-hungry applications and tools
2) Orchestrating your data across data silos
3) Managing data from edge to cloud

We're ready to share the secret ingredient that solves for these data challenges and more. Hint: The secret ingredient is dataware. Come join us at Dataware Symposium to learn more.

Whether you're a developer, data scientist, CxO, or anyone in between, this is an event you won’t want to miss. With dataware, we will pave the way for a better future for AI and analytics.

Areas of Focus:

Use cases, artificial intelligence, data analytics, edge analytics, analytics in cloud, hybrid and multi cloud, containers, microservices, data and cyber security, intelligent applications, global event systems, IoT transformation

We look forward to seeing you in Seattle




AGENDA

8:00a-9:00a | Breakfast/ Registration

9:00a-9:10a || Intro to the Day

9:10a-9:35a || Unlocking AI Value at Scale: 3 Building Blocks and 1 Massive Mistake to Avoid || Jack Norris, Senior Vice President Data & Applications, MapR

9:35a-10:00a || MapR to the Rescue! - Cequint's MapR Use Cases || Charles Wheelus, Principal Data Scientist at Cequint

10:00a-10:20a | Break

10:20a-10:45a || Presentation by Pepperdata

10:45a-11:15a || Featured Keynote by Rohan Mathews, Global Storage Tech Evangelist, AWS

11:15a-11:40a || Fraud Detection || Justin Vincent, Data Scientist at MapR Technologies

11:40a-12:00p || Stories from the Edge ( Fireside Chat )

11:40a-12:40p | Lunch

12:40p-1:20p || Connected Driver || Audrey Egan, Sr. Solutions Engineer, MapR

1:20p-1:40p || Tackling the Fraud Giant with Real-time Adaptive Behavioral Analytics || Andrew Chung, Director of Architecture and Analytics, Gesa Credit Union

1:40p-2:05p || Feature Engineering from Event-Based Data || Davor Bonaci, CEO and Emily Kruger, VP of Product, Operiant

2:05p-2:30p || A Reference Architecture for Scalable Search Relevance || Jake Mannix, Data Scientist at Salesforce

2:30p-2:50p | Break

2:50p- 3:00p || Kyligence Augmented OLAP on MapR Platform || Li Kang, Technical Director, Partnership, Kyligence

3:00p-3:25p || Driving Data-Driven Enterprise Transformation Using Kubernetes, Cloud and Edge || Ted Dunning PhD, Chief Executive Officer, MapR

3:25p-3:45p || Featured Partner Presentation

3:45p-4:15p || Expert Panel

4:15p-6:00p | Meet the Experts Happy Hour | Complimentary Book Signing: AI and Analytics in Production by Ted Dunning and Ellen Friedman

*more info coming soon



Featured Speakers



Ted Dunning PhD, Chief Technology Officer at MapR Technologies

Ted Dunning is Chief Application Architect at MapR and has years of experience with machine learning and other big data solutions across a range of sectors. Ted was the chief architect behind the MusicMatch (now Yahoo Music) and Veoh recommendation systems. He built fraud detection systems for ID Analytics (later purchased by LifeLock) and he has 24 patents issued to date plus a dozen pending. Ted has a PhD in computing science from the University of Sheffield and is active with open source projects as committer, PMC member, mentor and currently serving as a board member for the Apache Software Foundation. When he’s not doing data science, he plays guitar and mandolin. He also bought the beer at the first Hadoop user group meeting.

View Ted's LinkedIn profile





Jack Norris, Senior Vice President Data & Applications at MapR Technologies

Jack drives understanding and adoption of new applications enables by data convergence. With over 20 years of enterprise software marketing experience, he has demonstrated success from defining new markets for small companies. Jack’s broad experience includes launching and establishing analytic, virtualization, and storage companies and leading marketing and business development for an early-stage cloud storage software provider. Jack has also held senior executive roles with EMC, Rainfinity (now EMC), Brio Technology, SQRIBE, and Brain and Company. Jack earned an MBA from UCLA Anderson and a BA in Economics and honors and distinction from Stanford University.

View Jack's LinkedIn profile




Charles Wheelus, Principal Data Scientist at Cequint

Charles Wheelus is an accomplished data scientist and serial entrepreneur with expertise in the application of machine learning and predictive analytics for solving real world problems. Charleshas over two decades of experience in deploying and integrating server based solutions, including performance analytics in environments with a high degree of complexity. Charlesis a published columnist, a frequently invited guest speaker for data science topics, and has been called as an expert witness in Internet related litigation.

In 2012, Mr. Wheelus received the Revolution award and title "Splunk Ninja". This award recognized his work in SLA Compliance Assurance for wireless telecommunications. In addition to his professional duties, Charlesis a Ph.D. candidate in Computer Science at Florida Atlantic University. His research domain is machine learning and predictive analytics for network and cyber security.




Davor Bonaci, CEO at Operiant

Davor is a co-founder and CEO of Operiant, an early-stage, venture-backed Seattle startup. Previously, he was a software engineer in Google Cloud and led the Apache Beam open source project that unified the batch and streaming programming model for distributed data processing.





Emily Kruger, VP of Product at Operiant

Emily is VP of Product at Operiant. Previously, she ran product management for AWS Lightsail and has also led product management teams at several other Seattle-area software companies.




Jake Mannix, Data Scientist at Salesforce

Living in the intersection of search, applied machine learning, and distribute systems, currently Search Relevance Architect at Salesforce. Previously Chief Data Engineer at Lucidworks, doing research and development of data-driven applications on Apache Lucene/Solr and Apache Spark, and before that worked on the Semantic Scholar project at the Allen Institute for Artificial Intelligence; built Twitter's user/account search system and creating the Personalization and Interest Modeling team, focused on text classification and graph-based authority and influence propagation; and before that worked at LinkedIn, first in search infrastructure, and then a founding member of the Recommender Systems team. Apache Mahout committer, PMC Member (and former PMC Chair).




Li Kang, Technical Director, Partnership at Kyligence

At Kyligence Li works with our technology partners to build joint solutions. Li has extensive experiences in data and analytics field. Before joining Kyligence, he worked at companies like Oracle, Informatica, and MapR where he helped customers build database, data warehouse, and big data solutions.





Justin Vincent, Data Scientist at MapR Technologies

Justin is a Data Scientist at MapR where he works with internal engineers, sales representatives, and clients to design machine learning workflows and deliver custom machine learning applications and artificial intelligence solutions to clients. Before joining MapR, Justin was a postdoctoral research fellow in the Neurobiology Department at Harvard Medical School and Massachusetts General Hospital. Justin has co-authored one patent and twenty peer-reviewed publications in journals such as Nature and the Proceedings of the National Academy of Sciences. Collectively, his scientific publications have garnered over 16,000 citations, which led Clarivate Analytics to identify him as one of the world’s most influential minds every year since 2014. Justin is a graduate of the Cognition, Brain, and Behavior doctoral program at Harvard University.




Andrew Chung, Director of Architecture and Analytics at Gesa Credit

Andrew Chung is Director of Architecture and Analytics at Gesa Credit where he is responsible for the Architecture and manages the Analytics and Development team. He has worked in the Credit Union industry for over 15 years, using technology to a driver to be more efficient, cut cost, and be a differentiator in the banking world. Andrew received a BS in Management Information Systems from San Jose State University and a MS in Manage Information Systems from Florida State University.




Featured Sessions


Unlocking AI Value at Scale: 3 Building Blocks and 1 Massive Mistake to Avoid

Speaker: Jack Norris, Senior Vice President Data & Applications, MapR Technologies

When it comes to transforming businesses - engaging customers, improving products, optimizing services, and managing risk - the focus often moves to AI and analytics. Which AI tool? What algorithm? Who’s the Data Scientist? These are important questions but by no means the keys to initial and continuous success. This session will delve into the three building blocks and the one massive mistake to avoid for any organization looking to leverage AI.




MapR to the Rescue! - Cequint's MapR Use Cases

Speaker: Charles Wheelus, Principal Data Scientist at Cequint

Join Charles Wheelus, as he details his experiences in the Big Data Ecosystem, and how his team has been able to use MapR to successfully overcome obstacles. As Cequint's Principal Data Scientist, his team has many initiatives all centered around managing and analyzing large volumes of data. Charles will discuss the challenges they face, and how they have been able to deploy MapR to interoperate with other technology stacks and saved money in the process.



Connected Driver

Speaker: Audrey Egan, Solutions Engineer at MapR Technologies

The mechanical automobile is becoming a mobilized data hub. Technological advances are equipping vehicles to collect on board data(OBD) giving carmakers access to more vehicle and driver information than ever before. The challenge is now investing in technologies that provide agility and scalability as data grows and new products and services are revolutionized to change the driving experience. The MapR Data Platform is the next generation dataware platform which can collect, store, and analyze this information from IoT edge devices to cloud environments or on-premises. Let MapR simplify the management and machine learning ecosystem so you can drive more innovation from your data.



Feature Engineering from Event-based Data

Speakers: Davor Bonaci, CEO and Emily Kruger, VP of Product at Operiant

Machine learning is no longer just an academic pursuit. It is beginning to produce meaningful impact across organizations, driving recommendation and ranking engines, supply chain logistics, fraud detection, and more. Much of the progress to date has focused on models, but feature engineering remains the most difficult and important part of a successful ML system. Feature engineering is an art, requiring domain expertise, data science expertise, and data engineering ​—​ and many data teams struggle to execute all three well. High-impact machine learning systems typically construct features from event-based data streams. Yet, standard tools and processes do not support event-based data well and can result in stale features and less accurate predictions in production environments. These circumstances present additional challenges to an already difficult problem. Come hear Davor and Emily survey best practices for building feature engineering organizations and systems using event-based data. You will leave with a good understanding of the problem, possible solutions, pitfalls, and next steps for your own project.



A Reference Architecture for Scalable Search Relevance

Speaker: Jake Mannix, Data Scientist at Salesforce





Kyligence Augmented OLAP on MapR Platform

Speaker: Li Kang, Technical Director, Partnership at Kyligence

To achieve high performance or interactive analytics on a big data set, most massively parallel processing (MPP) solutions resort to putting a large proportion of the dataset into memory and launch as many CPU cores as possible to deliver query results in time. By nature, MPP solutions could easily hit throughput bottlenecks at high concurrency or budget issues when datasets grow too large to fit in memory.

Kyligence uses a different strategy to speed up analytical queries with pre-built OLAP Cube (which is essentially groups of aggregate tables). The Cubes are built with MapReduce/Spark on MapR platform so that a large volume of datasets can be handled easily.



Driving Data-Driven Enterprise Transformation Using Kubernetes, Cloud and Edge

Speaker: Ted Dunning PhD, Chief Executive Officer, MapR

A range of new technologies is transforming the landscape of business and technical organizations. This presentation provides practical, real-world value as part of an integrated "Dataware" architecture. The MapR Data Platform makes these technologies more powerful, making the cloud and container journey easier and more agile while naturally integrating the edge. This session is intended to help attendees understand how, when and why for implementing and adopting emerging technologies beyond buzz words by blending real reference architectures and real-world implementations.



Tackling the Fraud Giant with Real-time Adaptive Behavioral Analytics

Speaker: Andrew Chung, Director of Architecture and Analytics

Fraud continues to impact the financial industry with growing losses and challenges to keep up with the latest fraud tactics. Much of the fraud comes from the debit card and ATM channels, where the fraud detection systems are still lacking and do not detect fraud quickly enough to stop losses from occurring. This session will cover some of the real-life fraud cases in the banking industry and how Gesa Credit Union is planning to tackle fraud with the help of MapR through real-time data streams and using adaptive behavior analytics for debit card fraud detection.






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W Seattle

1112 4th Ave

Seattle, WA 98101

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