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Emerging Data Modeling and Management Technology: Key-Value and Document Databases


AIT

About Emerging Data Modeling & Management Technology: Key-Value & Document Databases

Training Objective: This professional training course is part of a project co-funded by the Erasmus+ program of the European Union. The main objective is to build the capacity, improve the level of competencies and skills of IT professionals in Data Science and Artificial Intelligence (DS&AI).

Training Description: This training emphasizes on emerging databases and technologies suitable for managing different types and characteristics of data. The course focuses on the following important categories of NoSQL data management systems: key-value and document models. These NoSQL models and data stores gain increasing popularity due to the growth of non-relational, semi-structured data and data scalability issues. They can solve problems relational databases cannot handle and have become increasingly important in data-intensive application development for the modern era of data-driven decision making. The course explores the importance and applications of NoSQL databases, the classification of the databases and how to use them in a real-world scenario.

Training Dates: Thursday 1 - Saturday 3 April 2021, 8:45-16:00

Target Participants:
  • Business Analysts
  • Database System Specialists
  • IT Specialists
Training Outcomes: On successful completion of the training course, the training professionals will be able to:
  1. Design and organize various types of data using Key-value and Document models.
  2. Identify, implement and perform frequent data operations (CRUD: create, read, update and delete) on Key-value and Document model systems.
  3. Solve practical data modeling and management problems using key-value / document models.
  4. Explain basic database administration, physical design and performance tuning of the data stores.

Training Methods: Technical hands-on approach with practical tools, running examples, exercises and business use cases to design, create databases, load and query data. Business cases to be practiced during the training: Online Shopping System (customers data, product data, order, user-session, shopping carts, product-reviews)

Training Program:
Day1: 9:00-12:00 - Introduction to the training course
- Applications and Business Use Cases
- Recall: Relational Database Concepts & SQL
- Limitation of Relational Model
- NoSQL Database Concepts
13.00-16.30 Project and Case Study for the Training:
E-Commerce Application
Key-value Data Modeling and Management
- Key-value Model Concepts
- Benefits and Limitations
- Applications and Use Cases
Redis: Hands-on Session I:
- Getting familiarization with Redis Enterprise Cloud (free version)
- Redis Data Types: String, List, Set, Sorted Set, Hash
- CRUD Operations
Day2: 9:00-12:00 Redis: Hands-on Session II:
- Project Practice: Modeling and Managing User-sessions
13.00-16.30 Document Modeling and Management
  - Document Model Concepts
  - Semi-structured data modeling using JSON documents
  - Applications and Use Cases
MongoDB: Hands-on Session III:
  - Getting familiarization with MongoDB on cloud (Atlas).
  - CRUD operations on MongoDB
  - Modeling, managing and querying JSON documents
Day3: 9:00-12:00 MongoDB: Hands-on Session IV:
  - Project Practice: Modeling and managing Customer data, Product catalogs, Purchase Orders, Product reviews
13.00-16.30 - Redis and MongoDB: Hands-on Session V:
  - Put them all together into a data-oriented application:
- Training Certification / Preparation for the certification exam
- Wrap-up and Conclusion

Required Skills:

Knowledge of relational database modeling and SQL

Course Staff

Instructor

Dr. Chutiporn Anutariya (Main Instructor)

Chutiporn Anutariya is an Associate Professor in the Department of Information & Communication Technologies and the Associate Dean for Academic Affairs, School of Engineering and Technology (SET) at Asian Institute of Technology (AIT). She received her BSc (Statistics) with first class honors and a gold medal award from Chulalongkorn University, and obtained her MSc and DTechSc (Computer Science) from AIT. Her PhD thesis also won the Dissertation Award from the National Research Council of Thailand. She was a postdoctoral fellow at Faculty of Information Technology, Mathematics and Electrical Engineering, Norwegian University of Science and Technology (NTNU), Norway.

TA#2

Kantinee Katchapakirin (TA)

Kantinee is a Ph.D. student in Computer Science at the Asian Institute of Technology.

TA#2

Pattama Krataithong (TA)

Pattama is a Ph.D. student in Information Management at the Asian Institute of Technology.

TA#2

Phakpoom Ittirattanakomon (TA)

Phakpoom is a M.Sc. student in Computer Science (with DS&AI specialization) at the Asian Institute of Technology.

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