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Taipei Kafka Meetup: https://www.meetup.com/taipei-kafka/
贊助單位:
目前因應疫情的措施如下,請大家協助配合:
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請全程配戴口罩 (活動提供飲料,喝水時可以拿下來)
活動時程
Time | Topic | Speaker |
---|---|---|
19:00-19:30 |
Check in + Food Chat |
|
19:30-20:10 |
Apache Kafka: Journey to Event Driven Systems |
Mark Teehan, Principal Solutions Engineer, Confluent |
20:10-20:50 |
The Role and Position of Confluent in the Data Middle Platform with use case sharing |
Meso Wang, Data Solution Architech, WebComm Technology |
20:50-21:20 |
Open Discussion |
Panel Discussion |
21:20-21:30 |
Safe Home |
|
活動內容:
1. 主題: Apache Kafka: Journey to Event Driven Systems
講者: Mark Teehan
Mark Teehan is a systems engineer at Confluent in Singapore. In his day-to-day work, Mark engages with organizations that are interested in event streaming, realtime ETL or anything related to running Apache Kafka systems. Interest in Apache Kafka spans banks, telcos, airlines, digital natives, government departments, insurance and manufacturing.
簡介:
Why Apache Kafka is great for building Event Driven systems! After a brief history, we will look at the features of Kafka that make it the best platform choice to build event driven systems: including durability, schemas, clients, connectors and message replay; followed by a look at how AK compares with other platform options such as messaging or databases.
2. 主題: The role and position of Confluent in the data middle platform with use case sharing (Confluent在數據中台的角色與應用案例分享)
講者: Meso Wang
Meso Wang is the data solution architect at WebComm Technology Taiwan. Meso devoted himself in data and analytics solution resolution to make sure data reservoir solution fit for enterprise design with the ease for maintenance, the right design for demand, and make sure better time to market fulfillment.
簡介:
Wants to know more about the use case for how to design Data Middle Platform (數據中台) ? These days, data middle platfrom has been more and more popular for enterprises to consider the design nature to make business decisions smarter and service time to market with better data leverage with more precise decision as well as customized service. How can you leverage the right software with the right technology at the right component has become more and more critical.
Among all of the design, how does kafka/ Confluent make differences in the data middle platform? Want to know more about the use case? Welcome to discuss with us.