Jesse Anderson

Managing Director at Big Data Institute

Talk

Working Together as Data Teams
YET TO BE SCHEDULED
Topics:
Level:
General

Your rating:
0/5

Description:

Between books and the real world lies the actual reality of implementing and creating data teams. Creating data teams represents the difficulty of taking scientists, engineers, and operations people then forcing them to actually get something working that solves a business problem. This talk covers the balancing act that data team managers and members deal with.


Abstract:

Between books and the real world lies the actual reality of implementing and creating data teams. Creating data teams represents the difficulty of taking scientists, engineers, and operations people then forcing them to actually get something working that solves a business problem.


This talk covers the balancing act that data team managers and members deal with. I share some of the shared experiences that every manager and member of a data team should know. However, these issues aren’t well known or talked about. This makes managers or team members think they’re alone or unique in facing these issues. The reality is that these are common issues and they should be addressed.


These common issues include:

- Dealing with the politics of the organization. How do you get data from people siloed due to politics?

- High bandwidth connections in data teams. How do you create high bandwidth connections between the teams to allow for the fastest help and least friction?

- Communicating the value of data teams to the rest of the organization. How do managers educate the rest organization on what they do and the value each data team creates?

- Getting credit to data engineering and operations. How do managers make sure that all credit for the work doesn’t just go to the data scientists?

Workshop

Professional Kafka Development (2 days)
Tuesday+Wednesday 9:00 - 17:00 -
Topics:
Kafka
Avro
Data at scale
Kafka Connect
Kafka Streams
KSQL
Level:
Intermediate
Your rating:
0/5

Takes a participant from no knowledge of Apache Kafka to be able to develop with it professionally. We cover Kafka and its ecosystem of technologies. It covers the concepts behind Kafka and how to write your own producers and consumers. Then, we cover the best practices for designing and architecting Kafka solutions, like Apache Avro. Finally, we cover the Kafka ecosystem with Kafka Streams, Kafka Connect, and KSQL. This class doesn’t just cover the easy or Hello World-level consideration; we go deeply into the advanced topics of Kafka.

Intended Audience: Technical, Software Engineers, QA, Analysts

Prerequisites: Intermediate-Level Java

Day 1

Data at scale

  • Data movement concepts
  • Moving data at scale

Kafka concepts

  • Kafka system
  • Basic concepts
  • Advanced concepts

Developing with Kafka

  • Using Apache Maven
  • Kafka API
  • Kafka API caveats

Advanced Kafka development

  • Advanced consumers and producers
  • Advanced Offset Handling
  • Transactions
  • Multithreading consumers

Day 2

Kafka and Avro

  • Why serialize
  • Avro and serialization formats

Kafka Connect

  • Using Kafka Connect
  • Importing from JDBC
  • Exporting to HDFS

Kafka Streams

  • Kafka Streams
  • Kafka Streams API

KSQL

  • Using KSQL


About

Jesse Anderson is a Data Engineer, Creative Engineer and Managing Director of Big Data Institute. He works with companies ranging from startups to Fortune 100 companies on Big Data. This includes training on cutting edge technologies like Apache Kafka, Apache Hadoop, and Apache Spark. He has taught over 30,000 people the skills to become data engineers. He is widely regarded as an expert in the field and for his novel teaching practices. Jesse is published on O’Reilly and Pragmatic Programmers. He has been covered in prestigious publications such as The Wall Street Journal, CNN, BBC, NPR, Engadget, and Wired.