Data Driven sessions
First, we need to know how to deal with massive amounts of data. Then we have to put it to use with techniques like streaming and edge computing to create fast, reactive, resilient applications for all types of customers.
1:30pm–5:00pm Monday, July 15, 2019
Jamiel Sheikh walks you through building an Ethereum decentralized application (DApp) using Solidity. You'll learn some basic Solidity syntax, how to send ether to a smart contract, how gas works, how to programmatically compile and deploy Solidity code, and how to invoke a smart contract from Remix.
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9:00am–12:30pm Tuesday, July 16, 2019
Join Tim Berglund to learn how to produce and consume a Kafka topic, integrate Kafka with a database using Kafka Connect, and perform real-time stream processing on Kafka data.
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11:00am–11:40am Wednesday, July 17, 2019
Today’s world generates different kinds of data at unbelievably rapid rates. Grishma Jena explains data science, the data science pipeline, and algorithms using real-life examples.
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11:50am–12:30pm Wednesday, July 17, 2019
Blockchain is now established as a valid technology to be used across enterprise applications. Brian Behlendorf discusses what he sees as the next stage of maturation for the tech—professionalization. Join in to explore standards, certifications, and training options for developers, blockchain as a service solutions, and how to avoid vendor lock-in.
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11:50am–12:30pm Wednesday, July 17, 2019
Fires caused by electric grid failures are increasing at an alarming rate. Michael Enescu and Peter Enescu examine how the energy adaptive networks technology built on open source and used to monitor and control power grids forms a planetary skin that can be used to predict and avoid such disasters as the Napa and Paradise Fires.
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1:45pm–2:25pm Wednesday, July 17, 2019
Applications from social media to healthcare to media are increasingly focused on humans and their relationships. But people do not lend themselves easily to being reduced to small slots. Christophe Pettus draws on his experience in data modeling and application design to examine how to successfully approach modeling humans and their relationships and legal compliance issues in a GDPR world.
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2:35pm–3:15pm Wednesday, July 17, 2019
ixo is the blockchain for impact, helping individuals and organizations around the world to achieve the UN Sustainable Development Goals by 2030. Herman Smith dives into how ixo can help you count what matters and value what counts using new Web 3.0 protocols and the ixo blockchain.
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2:35pm–3:15pm Wednesday, July 17, 2019
Streaming analytics is a popular subject in enterprise organizations because customers want real-time experiences, such as notifications and advice based on online behavior and other users’ actions. Bas Geerdink details an open source reference solution for streaming analytics that covers many use cases that follow a "pipes and filters" pattern, built with Scala, Flink, Kafka, and Cassandra.
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4:15pm–4:55pm Wednesday, July 17, 2019
When designing APIs such as the new GCP Firestore real-time database and Google Assistant, how did Google decide which trade-offs to make? Wenbo Zhu dives deep into the challenges faced while deploying a real-time streaming API designed for clients from data centers to the internet and details the trade-offs API developers need be aware of when designing such an API.
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4:15pm–4:55pm Wednesday, July 17, 2019
E. coli. Salmonella. Listeria. Last year saw several major outbreaks of foodborne illnesses. Tracing the source of contamination took days, even months; we should have the technology to do better. Using the 2018 outbreaks of E. coli in romaine lettuce as a case study, Erin Vincent examines blockchain technology, explains how it works, and compares types of blockchains and their use cases.
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5:05pm–5:45pm Wednesday, July 17, 2019
If you've ever wanted to get into blockchain development but haven't found a good place to start, you're in the right place. Horea Porutiu walks you through the basics of the Hyperledger Fabric platform by building a simple blockchain application and analyzing the main components required to run a blockchain network.
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5:05pm–5:45pm Wednesday, July 17, 2019
Cassandra is one of the most popular datastores in big data and ML applications. Data analysis at scale with fast query response is critical for business needs, and while Cassandra with Spark integration allows running an analytical workload, it can be slow. Shradha Ambekar dives into the challenges faced at Intuit and the solutions her team implemented to improve performance by 100x.
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11:00am–11:40am Thursday, July 18, 2019
Graphs provide a method to store and analyze the relationships within the data. Algorithms deepen our understanding of data through aggregation and perspectives to help developers make valuable business decisions for the future based on existing scenarios. Amy Hodler and Mark Needham lead you through a crash course in how to use graph algorithms as part of your big data toolkit.
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11:50am–12:30pm Thursday, July 18, 2019
Managing large stateful applications is tough. Matt Schallert outlines the challenges of automating stateful systems at scale and details how embracing a declarative approach can ease operation and automation of these systems on orchestrators such as Kubernetes. He then demonstrates how to apply this methodology to different types of stateful workloads.
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1:45pm–2:25pm Thursday, July 18, 2019
Data-intensive applications, with many layers of transformations and movement from different data sources, can often be challenging to maintain and iterate even after they are initially built and validated. Jiaqi Liu explores how to factor in monitoring, alerting, and tracing data lineage when building data applications that move and transform data across multiple dependencies.
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2:35pm–3:15pm Thursday, July 18, 2019
Alex Silva outlines lessons learned, common pitfalls, and design traps when designing your streaming data infrastructure, and he shares 21 best practices and standards used at Pluralsight.
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4:15pm–4:55pm Thursday, July 18, 2019
With so many moving parts, it's hard for the average database administrator (DBA) or database developer to come up with a good explanation for why the optimizer chooses certain query plans. Vicențiu Ciorbaru dives deep into how a modern database query optimizer works to optimize your queries and how you can help it work for you.
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