Name: WIX X Pinot Meetup
Start: 2024-06-18T15:00:00.000Z
End: 2024-06-18T17:00:00.000Z
Location: Prądnicka 20A

We're excited to invite you to join us for a Gen Ai x Pinot session!
9 AM PDT \| 12 PM EST
[Join the event online here>](https://www.linkedin.com/events/7192181752126218240/about/)

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RAG stands for Retrieval-Augmented Generation.
It’s a technique that enhances the responses returned by a large language model (LLM) to be more accurate. LLMs alone can answer many questions provided to them. But to respond with accurate answers and cite sources, the LLM needs help to do some research.
In this post, we’ll show how to do this in real-time using Apache Pinot.

**[Hubert Dulay](https://www.linkedin.com/in/hkdulay/)**
Author of the O'Reilly book “streaming data mesh." Developer Advocate at StarTree. He is currently writing his second book "Streaming Databases." Hubert is a veteran engineer with over 20 years of experience in big & fast data and ML.
Join our community on Slack [here>](http://stree.ai/slack)

Real Time Analytics Meetup New York

StarTree

Hubert Dulay

Kannu Priya

Real-Time Gen AI x Pinot

Online event

RSVP to the event [HERE>](https://www.meetup.com/datascienceportugal/events/300075986/)
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We're excited to arrive in Porto, Portugal, in collaboration with Data Science Portugal (DSPT) meetup group.
[Tim Berglund](https://www.linkedin.com/in/tlberglund/), VP od DevReal @[ StarTree](https://dev.startree.ai/) will give an introduction to Real Time Analytics with [Apache Pinot](https://pinot.apache.org/)!

=== Agenda ===
The preliminary agenda for the meetup is the following:
• 18:15 - 18:30: Get together;
• 18:30 - 19:00: Talk + Q&A: **“LLMstudio: Powering Enterprise Grade LLM Applications With Open-Source”** by **Cláudio Lemos**;
• 19:10 - 19:40 Talk + Q&A: **“Real-Time Analytics With Apache Pinot”** by **Tim Berglund**;
• 19:50 - 20:30: Networking.

**Abstracts:**

* **LLMstudio: Powering Enterprise Grade LLM Applications With Open- Source : TBD**
**Cláudio Lemos, Co-Founder of TensorOps, VP R&D**
Cláudio is a FEUP alumni. Two years ago, he co-founded TensorOps, helping clients accelerate their AI adoption. Currently, he is leading the development of LLMstudio, an open-source LLM gateway that helps users add observability to their LLM pipeline, while accessing multiple LLM vendors and optimizing costs.

* **Real-Time Analytics With Apache Pinot**

Analytics is arguably the oldest task of digital computers, and has remained an important part of business computing during its 80-year history. What could possibly be new in this space? A better way to serialize data? A better way to run distributed queries over a data lake? An exciting new integration technology? We need all these things urgently, but to be ready for the future, we something even more: we need analytics that can deliver results to users in real time, in the interaction layer, not to internal decision makers seconds or minutes later. We need what Apache Pinot delivers.
Pinot is a database optimized to serve analytical queries at extremely high levels of concurrency, at latencies measured in the tens of milliseconds, on data ingested from the streaming pipeline that underlies more and more of the systems we're building. It's an OLAP database, but one engineered from the ground up to power user-facing features, not executive-facing dashboards. In this talk, we'll look at how it's built, how to get data into it, how to query it, and the typical role it plays in a next-generation system exposing analytics-powered features to its users.

**Tim Berglund, VP of DevRel @ StarTree**
Tim is a teacher, author, and technology leader with StarTree, where he serves as the VP of Developer Relations. He is a regular speaker at conferences and a presence on YouTube explaining complex technology topics in an accessible way. He tweets as @tlberglund, blogs every few years at http://timberglund.com, and lives in Littleton, CO, USA. He has three grown children and two grandchildren, with a third on the way.
https://startree.ai/

**RSVP to the event [HERE>](https://www.meetup.com/datascienceportugal/events/300075986/)**
[Join Pinot community on Slack>](https://apache-pinot.slack.com/ssb/redirect)

Real Time Analytics meetup Porto

Alexander Kravchenko

Real Time Analytics meetup in Porto!

NOTE: Seats are limited, please complete your registration [here>](https://docs.google.com/forms/d/e/1FAIpQLSfDO_bFOGpOSKmUWH4nKP2qal5hJoZRTx3noNMoZxjIHbRWng/viewform)
Entry to the building will be allowed upon registration
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We're thrilled to co-organize our first meetup in Krakow, with WIX!
Join us for great content, kombucha and snacks!
**Agenda**
05:00-05:30 Snacks and Networking
05:30-05:35- Opening remarks
05:35\-06:05 Making Kafka Queryable with Apache Pinot\| Tim Berglund
06:05\-06:35\- Boosting Wix analytics performance with Pinot \| Daniil Dubin & Oleksandr Kylinskiy
06:35\-07:00 Proactive Anomaly Detection for BI Events using Apache Pinot \| Vladyslav Shamaida
07:00-07:30 Snacks and Networking

**Making Kafka Queryable with Apache Pinot**
[Tim Berglund](https://www.linkedin.com/in/tlberglund/), VP of DevRel @[ StarTree](https://dev.startree.ai/)
Apache Kafka has become the standard infrastructure for event-driven and streaming data systems. The stunningly simple abstraction of the distributed log provides exactly what modern microservices and real-time systems need, but no choice is without its tradeoffs. Logs are an excellent way to keep track of events, but they are notoriously difficult to query. Given a constellation of services exchanging events with each other and reacting to inputs in real time, how can you find out—and gain insight into—what has just happened? How, in other words, do you query a log? This is where Apache Pinot comes in.Developed at LinkedIn alongside Kafka, Pinot is a distributed, real-time analytics database designed to ingest data from Kafka (and other sources) and make it instantly queryable at low latency in the face of a huge number of concurrent requests. All that data tucked neatly away into topics, maintaining an immutable record of how the state of the system has evolved, can now be ingested into Pinot and made accessible through simple SQL queries.This talk explores Pinot’s internal architecture, how its integration with Kafka is specially optimized, and how Pinot fits architecturally in the modern streaming stack. You’ll leave understanding how Pinot works, how it fits together with Kafka, where it has been used successfully in the real world, and what steps to take next in your own Pinot learning journey.

**Boosting Wix analytics performance with Pinot**
[Daniil Dubin](https://www.linkedin.com/in/daniil-dubin-8692b9103/), Data Engineering @ [WIX](www.wix.com)
[Oleksandr Kylinskyi](https://www.linkedin.com/in/okylinskyi/), Engineering Manager @ [WIX](www.wix.com)
In order to provide Wix's 250M+ users with insights into their business we developed Wix Analytics – the product with dashboards and reports on multiple subjects.
Originally built on top of Snowflake warehouse and Looker it became an immediate success. Unfortunately as the popularity grew, higher RPM resulted in degrading performance and high costs. We analyzed the workload and realized that for the relatively simple high RPM low latency queries Snowflake + Looker combination was not the best fit.
We went on a journey to discover a more performant and cost effective solution ending up with a complex pipeline based on kafka SQL for data enrichment and pre-aggregation and Pinot as the query engine. The result over-exceeded our expectations. Today we are serving 100K+ RPM with sub second latency.
During the talk we'll go over the problem, decision making process, evaluation of alternatives and highlight some pitfalls that may save you some time should you decide to build a similar solution.

**Proactive Anomaly Detection for BI Events using Apache Pinot**
[Vladyslav Shamaida](https://www.linkedin.com/in/gsvlad/) Senior Software Engineer @ [WIX](www.wix.com)
In Wix, we collect a vast amount of business intelligence (BI) events that represent information about the usage of our products. With dozens of teams, hundreds of artifacts, and billions of BI events daily, it's crucial to have a real-time anomaly detection system to ensure prompt issue resolution and maintain the health of our BI data.
As our Data Infrastructure team had already achieved great results by integrating Apache Pinot into our user-facing analytics system, the solution lay on the surface. So we decided to build an anomaly detection system on top of it. It's a real-time datastore and a performant query engine - exactly what we need to run frequent checks over a big number of time-series data.
Furthermore, we explored ThirdEye, a managed solution that seamlessly integrates with Apache Pinot to provide advanced anomaly detection capabilities.
In this talk, we will share our experience, the technical details, and the benefits new tools have brought to our organization in ensuring the reliability and integrity of our mission-critical BI data.

Join our community on [Slack>](stree.ai/slack)

Real Time Analytics meetup Kraków

Illia Chmut

Vinay Lokwani

WIX X Pinot Meetup

Prądnicka 20A

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