Overview
| Duration |
2 days |
| Course Time |
9.00am - 5.30pm |
| Enquiry |
Click here to contact us
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This course is offered and delivered by School of Continuing and Lifelong Education (SCALE), NUS.
This introductory course has been developed to introduce modern data management technologies to participants. Among the topics to be analysed are the definition of basic data management techniques and technologies, the background of such technologies, and the future trends of Data Technology and Management (DTM).
This course will also explain the differences between various Data Management approaches, environments, and tools, as well as the advantages and disadvantages associated with their diverse applications. Emerging trends in the field of DTM will be reviewed as well.
Key Takeaways
At the end of the course, participants will be able to:
- Understand the basic terms of DTM, along with the characteristics and applications of different DTM techniques
- Articulate the future trends of DTM
- Compare the advantages and disadvantages of the new DTM platforms and tools in different applications
- Recommend a set of tools for a given problem
Who Should Attend
This course is suitable for IT Engineers, IT Managers, IT Executives and IT Consultants.
Pre-requisites
Minimum two years of working experience in the field of IT.
ICT and SS Competency Framework
ICT and SS Competency Framework
As part of the ICTCF, this course falls under the Apps Management functional cluster and tagged to the following competencies:
- Data Management & Analytics
The course is mapped to the following job roles:
- Digital Service Manager
- Digital Business Analyst
- Project Manager (Agile)
Course Structure
The course is conducted virtually and cover the following topics:
- Course Introduction, description of the goals, contents, and scheme
- Data management technology: Definitions and basic terms
- Big Data and Big Data Technology: Definitions and basic terms
- A review of the DBMS/RDBMS technology and trend
- Technical details of Big data, Cloud and Edge techniques
- Hardware and software requirements
- Differences between ordinary DBMS/RDBMS and Big data
- Skills and resources needed for big data management
- Data quality for big data solutions: data quality assurance for big data systems
- Data quality for big data solutions: new methodologies
- Cloud and edge technologies introduction
- Moving to big data: architecture, infrastructure, application, metadata
- Future trends in big data technology
- Tools review: Airflow, Kubernetes, Docker, ML Flow, Google Cloud, Mongo DB, Graph Databases, No SQL, and Server-less technologies
- Tools Comparison: Airflow, Kubernetes, Docker, ML Flow, Google Cloud, Mongo DB, Graph Databases, No SQL, and Server-less technologies
- Security considerations in modern DM
- Versatility considerations: Technical and implementation
- Volume and Velocity considerations: Technical and implementation
- IoT and multi-resources considerations: technical and implementation
- Big data implementation: requirements, roadmaps, strategies
- Big data implementation: challenges, integration, and validation
- Big data analysis challenges and methodologies
- Big data scaling challenges, necessities, and the application side
- Data warehousing for big data and its challenges
- Describing future DTM trends
Instructors
Fees and Funding
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Full Fee
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Full Programme Fee
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S$1,900.00
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7% GST on Nett
Programme Fee
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S$133.00
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Total Nett Programme
Fee Payable, Incl. GST
|
S$2,033.00
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With effect till 31 Dec 2022
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Full Fee
|
|
Full Programme Fee
|
S$1,900.00
|
|
7% GST on Nett
Programme Fee
|
S$152.00
|
|
Total Nett Programme
Fee Payable, Incl. GST
|
S$2,052.00
|
With effect from 1 Jan 2023 till 31 Dec 2023
NOTE: Funding is available for this course. Please visit the training provider’s website to find out about the updated course fee funding breakdown, eligibility, terms and conditions.
Upcoming Classes
Class 1
Duration: 2 days
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08 Jun 2023 to 09 Jun 2023 (Full Time)
When :
Time : 9.00am - 5.30pm
Registration:
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Class 2
Duration: 2 days
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14 Sep 2023 to 15 Sep 2023 (Full Time)
When :
Time : 9.00am - 5.30pm
Registration:
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Class 3
Duration: 2 days
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04 Dec 2023 to 05 Dec 2023 (Full Time)
When :
Time : 9.00am - 5.30pm
Registration:
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How To Register
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Step 1
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Apply through your organisation's training request system. |
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Step 2
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Your organisation's training request system (or relevant HR staff) confirms your organisation's approval for you to take the course.
Your organisation will send registration information to the academy.
Organisation HR L&D or equivalent staff can click here for details of the registration submission process.
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Step 3
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The Digital Academy will inform you whether you have been successful in enrolment.
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