Name: Make your data confess quickly with Druid and Neo4j databases
Start: 2021-10-28T18:30:00+02:00
End: 2021-10-28T20:00:00+02:00

Hello fellow Big Data and AI enthusiasts,

we are back again with a new meetup of the series Tech & More!
This time we are proud to have Imply with us, who will talk about Apache Druid.
Druid and Neo4j are databases designed for different purposes, but which share a common mission: to organise data in a structure that makes querying as efficient as possible. While Druid achieves this for large amounts of data, Neo4j focuses on the relationships in them, which it exploits to extract meaningful insights.
This meetup offers a gentle introduction to systems for large-scale data analysis and graph databases, and is well suited for beginner and intermediate levels. The more experienced will find additional insights and will have the chance to share their experience on the topic.

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Abstract Druid Talk:

Apache Druid is a modern cloud-native, stream-native, analytics database designed for workflows where fast queries and instant ingest are important. Druid excels at instant data visibility, ad-hoc queries, operational analytics, and handling high concurrency. It is a strong candidate for being the workhorse system for hot analytics.

Analytics-in-motion is here! Using a temperature-based way of categorising different analytics technologies, this talk gives the story of Apache Druid, a database designed to deliver instant data visibility, ad-hoc query, and high query concurrency. The talk will also include a description of end-to-end architectures from OSS Druid users (such as Lyft and Netflix), where streaming and stream-processing are the magic sauce that makes all the difference to users.

Requirements: Just an interest in systems for large-scale data analysis!

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Abstract Neo4j Workshop:

Powered by native graph technology, Neo4j stores and manages data in its more natural, connected state, maintaining data relationships that deliver lightning-fast queries, deeper context for analytics, and a pain-free modifiable data model.

After a short introduction on graphs, we will see the Property Graph model used by Neo4j, the main features of the database and the query language Cypher, by testing them on a Neo4j sandbox.

Requirements: If you want to better follow the workshop and test the commands yourself, you can create an account for the Neo4j sandbox in less than a minute here --> https://sandbox.neo4j.com/

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Speakers:

Peter Marshall (https://www.linkedin.com/in/petermarshallio/) leads the Technical Evangelism team at Imply (http://imply.io/), a company founded by the original developers of Apache Druid. He has 20 years architecture experience in CRM, EDRM, ERP, EIP, Digital Services, Security, BI, Analytics, and MDM. He is TOGAF certified and has a BA (hons) degree in Theology and Computer Studies from the University of Birmingham in the United Kingdom.

Lorenzo Graziano is a Data Engineer in Agile Lab, with a Master's degree in Computer Science and Engineering and a professional master in Artificial Intelligence. He currently works with Neo4j, where he uses graph databases to model the electricity grid worldwide.

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The event will last about 1,5 hours and consists of two talks:

18:30-19:15 - An introduction to Apache Druid with a focus on evaluation methods and use cases (45 mins)
19:15-19:25 - Q&A (10 mins)
19:25-19:55 - Introductory workshop on Neo4j (30 mins)
19:55-20:00 - Q&A (5 mins)

You will follow the event online. The streaming platform is Teams, we will provide a link as direct access for attendees.
Desktop: you can access via browser or with the Teams app.
Mobile: you need to access with the Teams app, unless you set your mobile browser as "Desktop Website".

We hope you will join us!
Please, send your RSVP as soon as possible to help us organize the event!

See you all on Thursday 28th October!

Riccardo Fino

Big Data & AI Milano

Technology

Open Source

Hadoop

Big Data

Apache Spark

Apache Kafka

Spark Streaming

Artificial Intelligence

Machine Learning

NoSQL

Data Visualization

MapReduce

Make your data confess quickly with Druid and Neo4j databases

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Make your data confess quickly with Druid and Neo4j databases

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