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| Title & Speakers | Event |
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ClickHouse Meetup in Amsterdam
2024-12-03 · 17:00
Location: Xebia Amsterdam, Wibautstraat 200, 1091 GS Amsterdam Hey there, data enthusiasts and ClickHouse aficionados! We've got some exciting news to share - our next meetup is on the horizon, and it's going to be an epic data-driven shindig! Get ready for a delightful mix of mind-boggling data tales, insightful conversations, and maybe even a surprise or two up our sleeves. But here's the deal: to secure your spot, make sure you register ASAP! Agenda: 1800 - 1830
If you are interested in speaking, please contact [email protected] |
ClickHouse Meetup in Amsterdam
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DuckDB in Action
2024-08-21
Dive into DuckDB and start processing gigabytes of data with ease—all with no data warehouse. DuckDB is a cutting-edge SQL database that makes it incredibly easy to analyze big data sets right from your laptop. In DuckDB in Action you’ll learn everything you need to know to get the most out of this awesome tool, keep your data secure on prem, and save you hundreds on your cloud bill. From data ingestion to advanced data pipelines, you’ll learn everything you need to get the most out of DuckDB—all through hands-on examples. Open up DuckDB in Action and learn how to: Read and process data from CSV, JSON and Parquet sources both locally and remote Write analytical SQL queries, including aggregations, common table expressions, window functions, special types of joins, and pivot tables Use DuckDB from Python, both with SQL and its "Relational"-API, interacting with databases but also data frames Prepare, ingest and query large datasets Build cloud data pipelines Extend DuckDB with custom functionality Pragmatic and comprehensive, DuckDB in Action introduces the DuckDB database and shows you how to use it to solve common data workflow problems. You won’t need to read through pages of documentation—you’ll learn as you work. Get to grips with DuckDB's unique SQL dialect, learning to seamlessly load, prepare, and analyze data using SQL queries. Extend DuckDB with both Python and built-in tools such as MotherDuck, and gain practical insights into building robust and automated data pipelines. About the Technology DuckDB makes data analytics fast and fun! You don’t need to set up a Spark or run a cloud data warehouse just to process a few hundred gigabytes of data. DuckDB is easily embeddable in any data analytics application, runs on a laptop, and processes data from almost any source, including JSON, CSV, Parquet, SQLite and Postgres. About the Book DuckDB in Action guides you example-by-example from setup, through your first SQL query, to advanced topics like building data pipelines and embedding DuckDB as a local data store for a Streamlit web app. You’ll explore DuckDB’s handy SQL extensions, get to grips with aggregation, analysis, and data without persistence, and use Python to customize DuckDB. A hands-on project accompanies each new topic, so you can see DuckDB in action. What's Inside Prepare, ingest and query large datasets Build cloud data pipelines Extend DuckDB with custom functionality Fast-paced SQL recap: From simple queries to advanced analytics About the Reader For data pros comfortable with Python and CLI tools. About the Authors Mark Needham is a blogger and video creator at @LearnDataWithMark. Michael Hunger leads product innovation for the Neo4j graph database. Michael Simons is a Java Champion, author, and Engineer at Neo4j. Quotes I use DuckDB every day, and I still learned a lot about how DuckDB makes things that are hard in most databases easy! - Jordan Tigani, Founder, MotherDuck An excellent resource! Unlocks possibilities for storing, processing, analyzing, and summarizing data at the edge using DuckDB. - Pramod Sadalage, Director, Thoughtworks Clear and accessible. A comprehensive resource for harnessing the power of DuckDB for both novices and experienced professionals. - Qiusheng Wu, Associate Professor, University of Tennessee Excellent! The book all we ducklings have been waiting for! - Gunnar Morling, Decodable |
O'Reilly Data Science Books
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ClickHouse Meetup in London
2024-06-19 · 17:30
Hey there, data enthusiasts and ClickHouse aficionados! We've got some exciting news to share - our next meetup is on the horizon, and it's going to be an epic data-driven shindig! Get ready for a delightful mix of mind-boggling data tales, insightful conversations, and maybe even a surprise or two up our sleeves. But here's the deal: to secure your spot, make sure you register ASAP! Agenda: 18:00 - 18:30 - Hosted by Checkout.com with welcome
18:30 - 19:00 - The Power of ClickHouse
19:00 - 19:30 - Lessons from self-hosting ClickHouse
19:30 - 20:00 - Game, Set, Match: Transforming Live Sports with AI-Driven Commentary
20:00 - 21:00
If you are interested in speaking, please contact [email protected] |
ClickHouse Meetup in London
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ClickHouse Meetup in London
2024-02-28 · 18:00
Location: 97 - 99 Camden High St (via, Mary Terrace, London NW1 7JN) ----- Hey there, data enthusiasts and ClickHouse aficionados! We've got some exciting news to share - our next meetup is on the horizon, and it's going to be in London! Get ready for a delightful mix of mind-boggling data tales, insightful conversations, and maybe even a surprise or two up our sleeves. But here's the deal: to secure your spot, make sure you register ASAP! Agenda: 18:00: Doors Open - Networking & Snacks 18:30: An Introduction to ClickHouse - Christoph Wurm\, ClickHouse 18:50: Building Real Time Analytics Systems With ClickHouse - Benjamin Wootton\, Founder & CTO Ensemble * Why ClickHouse (Cloud) is a good fit for systems like this * Machine learning architeceture (using SageMaker) * GUI layer (I can talk about the React GUI we are building) 19:10: Building a Data Platform with Clickhouse - Benji Lewis\, Zappi 19:30: Analytics on your laptop with ClickHouse Local - Mark Needham\, ClickHouse Although ClickHouse is usually used for large-scale data analytics with lots of concurrent users, we can also use it to run analytics from our laptop with ClickHouse Local and chDB. In this talk, we'll learn how to query various file formats including JSON and Parquet and we'll also see how we can join data from ClickHouse running on our machine with data from ClickHouse Cloud. Although ClickHouse is usually used for large-scale data analytics with lots of concurrent users, we can also use it to run analytics from our laptop with ClickHouse Local and chDB. In this talk, we'll learn how to query various file formats including JSON and Parquet and we'll also see how we can join data from ClickHouse running on our machine with data from ClickHouse Cloud. 19:55: Q&A Session 20:05: Dinner, Drinks & Networking 21:30: Event Concludes If you are interested in speaking at a future event, please contact [email protected] |
ClickHouse Meetup in London
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Building Real-Time Analytics Systems
2023-09-14
Mark Needham
– author
Gain deep insight into real-time analytics, including the features of these systems and the problems they solve. With this practical book, data engineers at organizations that use event-processing systems such as Kafka, Google Pub/Sub, and AWS Kinesis will learn how to analyze data streams in real time. The faster you derive insights, the quicker you can spot changes in your business and act accordingly. Author Mark Needham from StarTree provides an overview of the real-time analytics space and an understanding of what goes into building real-time applications. The book's second part offers a series of hands-on tutorials that show you how to combine multiple software products to build real-time analytics applications for an imaginary pizza delivery service. You will: Learn common architectures for real-time analytics Discover how event processing differs from real-time analytics Ingest event data from Apache Kafka into Apache Pinot Combine event streams with OLTP data using Debezium and Kafka Streams Write real-time queries against event data stored in Apache Pinot Build a real-time dashboard and order tracking app Learn how Uber, Stripe, and Just Eat use real-time analytics |
O'Reilly Data Engineering Books
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Join the event here>Have you ever received a notification that your flight has been canceled? Your first thought is unprintable, but after that you have to figure out what your options are and what to do next. This most likely involves speaking to a stressed out customer representative who is trying to deal with many other (angry) people who are in the same situation? Surely we can do better, and in this webinar we’re going to explore how we could build more useful notifications using Redpanda, Apache Pinot, and a sprinkling of a Large Language Model. This webinar will explore the following
Join StarTree slack>> Join Redpanda slack>> ---- About the speakers: Dunith Danushka: Senior Developer Advocate @ Redpanda Dunith has a passion for designing, building and operating large-scale real-time event-driven architectures. With over 10 years of experience, he enjoys sharing his knowledge through blogging, videos, and public speaking. Currently, Dunith serves as a Senior Developer Advocate at Redpanda, where he spends most of his time educating developers on how to build event-driven applications with Redpanda. @dunithd Mark Needham, Developer Advocate @ StarTree As a developer relations engineer, Mark helps users learn how to use Apache Pinot to build their real-time user-facing analytics applications.Mark also focuses on enhancing the developer experience, by working on product improvements and refining the documentation, simplifying the initial journey for newcomers. Mark writes about his experiences working with Pinot at markhneedham.com. He tweets at @markhneedham. |
Fusing Real-Time Analytics and Generative AI: Uplifting the Customer Experience
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Graph Algorithms
2019-05-16
Mark Needham
– author
,
Amy E. Hodler
– author
Learn how graph algorithms can help you leverage relationships within your data to develop intelligent solutions and enhance your machine learning models. With this practical guide,developers and data scientists will discover how graph analytics deliver value, whether they’re used for building dynamic network models or forecasting real-world behavior. Mark Needham and Amy Hodler from Neo4j explain how graph algorithms describe complex structures and reveal difficult-to-find patterns—from finding vulnerabilities and bottlenecksto detecting communities and improving machine learning predictions. You’ll walk through hands-on examples that show you how to use graph algorithms in Apache Spark and Neo4j, two of the most common choices for graph analytics. Learn how graph analytics reveal more predictive elements in today’s data Understand how popular graph algorithms work and how they’re applied Use sample code and tips from more than 20 graph algorithm examples Learn which algorithms to use for different types of questions Explore examples with working code and sample datasets for Spark and Neo4j Create an ML workflow for link prediction by combining Neo4j and Spark |
O'Reilly Data Science Books
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