IN-PERSON: Data Streaming Meetup

Join us for an IN-PERSON Data Streaming meetup on Tuesday, March 3 from 6:00pm hosted by Improving!

📍Venue:
Improving
11675 Rainwater Dr #100, Alpharetta, GA 30009

🗓 Agenda:

• 6:00pm: Doors open
• 6:00pm - 6:30pm: Food, drinks and networking
• 6:30pm -7:00pm: Olena Kutsenko, Staff Developer Advocate, Confluent
• 7:00pm - 7:30pm: Viktor Gamov, Principal Developer Advocate, Confluent
• 7:30pm-8:00pm: Additional Q&A & Networking

💡 Speaker One:
Olena Kutsenko, Staff Developer Advocate, Confluent

Title of Talk:
Keeping data private in real-time pipelines

Abstract:
We all love real-time data — clicks, payments, rides, messages — but most of it comes with a catch: it contains personal information we’re not supposed to leak, such as names, emails, locations, or even small clues that can identify someone. The challenge: how do we keep streaming data useful and safe at the same time?

In this talk, we’ll explore practical ways to protect privacy in streaming systems using Apache Kafka, Apache Flink, and Apache Iceberg. We’ll cover:
- simple tricks like masking and tokenizing PII;
- why “anonymous” data often isn’t anonymous (the re-identification problem);
- techniques like bucketing, k-anonymity, and adding noise;
- how to balance privacy with data utility (too much hiding makes data useless).

Along the way, we’ll look at real-world stories: from public data leaks to surprising deanonymization attacks, and show live demos of pipelines that anonymize data before it’s written to storage.
If you’ve ever wondered how to build privacy-aware pipelines, this talk will give you practical patterns you can use right away.

Bio:
Olena Kutsenko is a Staff Developer Advocate at Confluent and a recognized expert in data streaming and analytics. With two decades of experience in software engineering, she has built mission-critical applications, led high-performing teams, and driven large-scale technology adoption at industry leaders like Nokia, HERE Technologies, AWS, and Aiven.

A passionate advocate for real-time data processing and AI-driven applications, Olena empowers developers and organizations to use the power of streaming data. She is an AWS Community Builder, a dedicated mentor, and a volunteer instructor at a nonprofit tech school, helping to shape the next generation of engineers.

As an international speaker and thought leader, Olena regularly presents at top global conferences, sharing deep technical insights and hands-on expertise. Whether through her talks, workshops, or content, she is committed to making complex technologies accessible and inspiring innovation in the developer community.

💡 Speaker Two:
Viktor Gamov, Principal Developer Advocate, Confluent

Title of Talk:
One Does Not Simply Query a Stream

Abstract:
Streaming data with Apache Kafka® has become the backbone of modern day applications. While streams are ideal for continuous data flow, they lack built-in querying capability. Unlike databases with indexed lookups, Kafka's append-only logs are designed for high throughput processing, not for on-demand querying. This necessitates teams to build additional infrastructure to enable query capabilities for streaming data. Traditional methods replicate this data into external stores such as relational databases like PostgreSQL for operational workloads and object storage like S3 with Flink, Spark, or Trino for analytical use cases. While useful sometimes, these methods deepen the divide between operational and analytical estates, creating silos, complex ETL pipelines, and issues with schema mismatches, freshness, and failures.

In this session, we’ll explore and see live demos of some solutions to unify the operational and analytical estates, eliminating data silos. We’ll start with stream processing using Kafka Streams, Apache Flink®, and SQL implementations, then cover integration of relational databases with real-time analytics databases such as Apache Pinot® and ClickHouse. Finally, we’ll dive into modern approaches like Apache Iceberg® with Tableflow, which simplifies data preparation by seamlessly representing Kafka topics and associated schemas as Iceberg or Delta tables in a few clicks. While there's no single right answer to this problem, as responsible system builders, we must understand our options and trade-offs to build robust architectures.

Bio:
Viktor Gamov is a Principal Developer Advocate at Confluent, founded by the original creators of Apache Kafka®. With a rich background in implementing and advocating for distributed systems and cloud-native architectures, Viktor excels in open-source technologies. He is passionate about assisting architects, developers, and operators in crafting systems that are not only low in latency and scalable but also highly available.

As a Java Champion and an esteemed speaker, Viktor is known for his insightful presentations at top industry events like JavaOne, Devoxx, Kafka Summit, and QCon. His expertise spans distributed systems, real-time data streaming, JVM, and DevOps.

Viktor has co-authored "Enterprise Web Development" from O'Reilly and "Apache Kafka® in Action" from Manning.

Follow Viktor on X - @gamussa to stay updated with Viktor's latest thoughts on technology, his gym and food adventures, and insights into open-source and developer advocacy.

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DISCLAIMER
We do not cater to those under the age of 21.
If you would like to speak or host our next event please let us know! community@confluent.io