Kai Yu


Kai Yu is a Distinguished Engineer and a member of the Technical Leadership Community in Dell Technologies. Kai has 29+ years’ experience of architecting various IT solutions by specializing in Oracle database, Oracle EBS, virtualization &Cloud, Oracle BI Analytics and machine learning. Kai has been a frequent speaker at various IT/Oracle conferences such as IEEE HPCC, OOW, Collaborates, Oracle LAOUC tour, Oracle APAC tour, DOAG(Germany), UKOUG, RMOUG, HrOUG, POUG(Poland) etc with more 200 presentations in more than 20 countries. He also authored 35 articles in technical journals such as IEEE Transactions on Big Data, IOUG Select etc. Kai has published two Apress books “Expert Oracle RAC12c” and more recent “Machine Learning for Oracle Database Professionals”
Kai has been a Quest/IOUG conference committee member, IOUG RAC SIG president and IOUG Cloud SIG co-founder and the current vice president. Kai has been an Oracle ACE Director since 2010 and was featured as Oracle ACE Spotlight. He also received the 2011 OAUG Innovator of Year award the 2012 Oracle Excellence Award: Technologist of the Year: Cloud Architect by Oracle Magazine.

Kai Yu will present the following sessions at ConTech2022:

Achieving massive scalability &complete fault isolation with Oracle Sharding 21c

Oracle sharding architecture horizontally partitions data across discrete Oracle Databases (shards) that also collectively form a single logical database.
In this session we will discuss our experience of using Oracle sharding for the business including: what type of application best fit to Oracle sharding, configuring sharded database with HA replication for massive scalability and complete fault isolation and some lessons learned.
We will also discuss some new sharding features in Oracle 21c such as sharding with database in Persistent memory. Furthermore we will discuss our experience with Oracle sharding in Oracle Cloud Infrastructure including docker base deployment of Oracle Shard database and Oracle sharding database on Kubernetes.
The audiences will learn our experience of using Oracle sharding to achieve massive scalability and complete fault isolation. They will also learn Oracle sharding in Oracle Cloud Infrastructure such as Oracle sharding in docker and Kubernetes platform.
Oracle In-database Machine Learning with OML4SQL/OML4Py in Oracle Autonomous Databases

As next generation enterprise applications are more data driven and more intelligent, advanced analytics and machine Learning bring great business value. Oracle In-Database machine learning moves the algorithms to database where the data is stored.
In this session, we will discuss how Oracle In-database machine learning is provided in Oracle Database including Oracle Autonomous Database with scalability, simplicity and high performance.
We will discuss how to build, evaluate and deploys machine learning models natively with large enterprise data using Oracle Machine Learning for SQL(OML4SQL) and Oracle Machine Learning for Python (OML4Py).
This session will take some use cases as examples to show the process of machine learning: analyze and prepare data set; build and evaluate and apply machine learning model with Oracle Autonomous Databases environment. Some Oracle 21c new features such as AutoML will also be discussed.