StampedeCon Big Data Conference

July 25th, 2017 - St. Louis, MO

Experts and thought leaders discuss Big Data architecture, tools and industry use cases at the 6th annual StampedeCon Big Data Conference.

PARKING

Premier Sponsors

Speakers

Paul Boal

Paul Boal

VP, Solution Delivery at Amitech Solutions; Adjunct Instructor at Washington University & St. Louis University

Enabling New Business Capabilities with Cloud-based Streaming Data Architecture

Using big data isn’t about doing the same things we’ve always done just with different technologies. The technology advances that we’ve chosen to label as big data create the opportunity for wholly new kinds of solutions. Two of the key advances that are enabling new business capabilities are cloud-based data management platforms and streaming data processing and analytics.

In this session, Paul Boal will drill into the cloud-based streaming data architecture that has made possible EVŌ, a new breakthrough health and wellness platform. EVŌ uses a game-changing approach that leverages over 60 billion data points and a predictive analytics engine to intervene BEFORE someone becomes critically ill. All of this is possible by leveraging data from smartphones and wearable fitness devices along with advanced analytics which then help users develop and sustain positive behaviors. Attendees will learn how to create a cloud- based architecture that can receive data, apply multiple layers of dynamic business rules, and drive alerts and decisions through real-time stream processing using technologies including web services, Amazon DynamoDB and Kinesis, Drools, and Apache Spark.

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Mitchell Henderson

Mitchell Henderson

Solutions Engineer Manager at DataStax

Graph in Customer 360

Enterprises typically have many data silos of partial customer data and a  common theme in big data projects to use big data tools and pipelines to unify all siloed customer data into a single, queryable, platform for improving all future customer interactions.  This data often comes from billing, website traffic, logistics, and marketing; all in different formats with different properties.  Graph provides a way to unify all of the data into a single place for use in tracking the flow of a user through the various silos.  Graph can also be used for visualizations and analytics that are difficult in other systems.

In this talk we will explore the ways in which Graph can be leveraged in a customer 360 use case.  What it can add to a more conventional system and what the approach to developing a graph based Customer 360 system should be.

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Andrew Psaltis

Andrew Psaltis

HDF/IoT Product Solutions Architect at Hortonworks

Apache Beam: The Case for Unifying Streaming API’s

Our needs for real-time data are growing at an unprecedented rate; it is only a matter of time before you will be faced with building a real-time streaming pipeline. Often a major key decision you would need to quickly make is which stream-processing framework should you use. What if instead you could use a unified API that allows you to express complex data processing workflows, including advanced windowing and event timing and aggregate computations? Apache Beam aims to provide this unified model along with a set of language-specific SDKs for defining and executing complex data processing, data ingestion and integration workflows. This simplifies and will truly change how we implement and think about large-scale batch and streaming data processing in the future. Today these pipelines can be run on Apache Flink, Apache Spark, and Google Cloud Dataflow. This is only a start, come to this session to learn where the future of streaming API’s is headed and get ready to leverage Apache Beam for your next streaming project.

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Tony Shan

Tony Shan

Independent Big Data Consultant

Big Data Antidotes

49% of large companies are implementing Big Data solutions today. But 65% of Big Data projects failed. How can you not get stuck with various syndromes? This talk presents a comprehensive set of Big Data antipatterns, defined as common responses to recurring problems that are usually ineffective and risks being highly counterproductive. We introduce an overarching framework represented in a cube with 3 dimensions: Category, Area, and Type (CAT). Each cube edge is broken down to 3 parts. The Category edge comprises Business, Application, and Technology (BAT). The Area edge is composed of Plan, Implement, and Govern (PIG). Likewise, the Type edge consists of Resource, Architecture, and Management (RAM). Further, each of the 27 cells in the 3X3X3 hexahedron contains classified Big Data antipatterns, which are from lessons learned in the real-life projects and initiatives. We will zoom in to the definition and characterization of the CAT dimensions, and then dive deep to selected antipatterns like Golden Hammer, Dependency Dilemma, Data Swamps, Unimodality, and Product Pollution in detail. Real-world user stories and case studies will be discussed, along with best practices to avoid the pitfalls and traps.

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Cliff Gilmore

Cliff Gilmore

Confluent

Building Streaming Applications with Apache Kafka

Learn how the Apache Kafka’s Streams API allows you to develop next-generation applications and micro services built upon the proven reliability, scalability, and low latency of Apache Kafka. In this session, you will learn about the architecture of the Streams API along with an overview use cases where it can be best applied.

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Donald Miner

Donald Miner

‎Founding Partner at Miner & Kasch

End-to-end Big Data Projects with Python

This talk will go over how to build an end-to-end data processing system in Python, from data ingest, to data analytics, to machine learning, to user presentation. Developments in old and new tools have made this particularly possible today. The talk in particular will talk about Airflow for process workflows, PySpark for data processing, Python data science libraries for machine learning and advanced analytics, and building agile microservices in Python.

System architects, software engineers, data scientists, and business leaders can all benefit from attending the talk. They should learn how to build more agile data processing systems and take away some ideas on how their data systems could be simpler and more powerful.

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Adam Doyle

Adam Doyle

Manager, Information Architect at Daugherty Business Solutions

So You Don’t Have an Admin Team – Doing Big Data using Amazon’s analogs

Big Data doesn’t have to just mean Hadoop any more. Big Data can be done in the cloud, using tools developed by the Cloud providers. This session will cover using Amazon AWS services to implement a Big Data application. We will compare and contrast different services from Amazon with the Hadoop equivalents.

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Rob Peglar

Rob Peglar

Senior Vice President and Chief Technology Officer of Symbolic IO

The New World of Analytics using Persistent Memory

For decades, we have used memory in its volatile form – DRAM.  However, we now have persistent memory – memory which retains its data across power loss or shutdown – and the impact on the control and execution of analytics workflows is significant.  This talk will explore persisting data in the memory channel, especially in server architecture, and explore the optimization possibilities of using persistent memory in Spark, graph solvers, and other useful analytics tools.  The reality of 10-100X (not percent – X) reduction in execution runtimes and the economics of persistent memory will be discussed.

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Agenda

Time Session Title
8:00 - 8:45

Check-in, Networking and Breakfast

8:45 - 9:00

Opening Remarks

9:00 - 9:45

Enabling New Business Capabilities with Cloud-based Streaming Data Architecture

Paul Boal VP, Solution Delivery at Amitech; Adjunct Instructor at SLU

9:45 - 10:30

The New World of Analytics using Persistent Memory

Rob Peglar Senior Vice President and Chief Technology Officer of Symbolic IO

10:30 - 11:15

Networking Break

11:15 - 12:00

Big Data Antidotes

Tony Shan Independent Big Data Consultant

12:00 - 12:45

Building Streaming Applications with Apache Kafka

Cliff Gilmore Confluent

12:45 - 1:15

Lunch (provided)

1:15 - 2:00

End-to-end Big Data Projects with Python

Donald Miner ‎Founding Partner at Miner & Kasch

2:00 - 2:45

Graph in Customer 360

Mitchell Henderson Solutions Engineer Manager at DataStax

2:45 - 3:30

Networking Break

3:30 - 4:15

Apache Beam: The Case for Unifying Streaming API’s

Andrew Psaltis HDF/IoT Product Solutions Architect at Hortonworks

4:15 - 5:00

So You Don’t Have an Admin Team – Doing Big Data using Amazon’s analogs

Adam Doyle Manager, Information Architect at Daugherty Business Solutions

5:00 - 6:30

Closing Remarks (5 minutes),
Networking Reception

Location: Eric P Newman Education Center, Washington University Medical School

PARKING:

Park in the Metro Parking Garage
4560 Children’s Place
St. Louis, MO 63110

Daily Rate is $15
Map — Click Here for Printable Map and Directions

EPNEC is an IACC-certified conference center on the campus of Washington University Medical Center in St. Louis, Missouri

Eric P. Newman Education Center

Eric P. Newman Education Center
320 S Euclid Ave, St. Louis, MO 63110, USA
PARK AT: Metro Parking Garage, 4560 Children’s Place, St. Louis, MO 63110

PARKING for Eric P Newman Education Center

For StampedeCon, Park at 4560 Children’s Place, St. Louis, MO 63110
Click Here for Printable Map and Directions

Blog

Enabling Value-Based Healthcare with Big Data

This post was contributed by the Amitech Solutions team. Amitech is a sponsor and will be providing featured speaker, Paul Boal, at the 6th Annual StampedeCon Big Data Conference 2017 in St. Louis. Boal will be speaking on Enabling New Business Capabilities with...

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Growth of Streaming Analytics

The post originally appeared on DellEMC's blog written by Keith Manthey, CTO of Analytics at EMC Emerging Technologies Division. It has been republished on the StampedeCon blog with permission. DellEMC is a sponsor of the 6th Annual StampedeCon Big Data Conference in...

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