This course is designed for IT business analysts to, eventually, become data science consultants and provides the participants with a foundation in:
- Overview of data science techniques, process and technology
- Data science consulting skills
- Connecting business problem to data science
- Understand critical success factors of data science projects
- Managing analytics projects (both innovation cycle and deployment cycle)
- Extracting, cleaning and transforming raw data into analytics-ready data
At the end of the course, you will be able to:
- Understand data science capabilities and its limitations;
- Implement and manage the data science process for innovation and deployment cycles;
- Advise and deliver high quality data analytics projects.
Module 1: Advancing Data Analytics in the Organisation
- The big picture - big data and data analytics
- Overview of machine learning, data science, artificial intelligence and deep learning
- Discussion of analytics use cases
Module 2: Analytics Project Life Cycle
Overview of Analytics Project Life Cycle management
- Introduction to Analytics Project Life Cycle (APLC)
- Understanding Various stakeholders Roles (BAF, DS, Vendor, data owners) within APLC
- Pain and problem when dealing with data analytic projects
- Visualization Workshop: Visualization for data exploration
Module 3: Managing Data Analytics Project
Part 1: Managing Quality, Sustainability, Reliability and Timeliness of Data Analytics Projects through APLC
- Managing Quality and Reliability of Data Analytics Project
- Where is the data?
- What is going with the data in each phase?
- What are the questions you would need to ask when managing vendor who perform analytic services?
- From Prototype (usability) to Deployment (Scalability) to Maintenance (Sustainability)
What are the key considerations beyond prototype?
- Data Staging
- Data Transformation and results
- Computation and results
- Results accuracy
- Visualization requirement
Module 4: Analytics Workshop (Text Analytics)
Hands on practice
- Preparation (Text to Words)
- Topic Clustering
Participants should have 2 years of experience in the IT business analyst role.
Who Should Attend
IT Business Analyst
Mode of Training
Catherine Khaw is an evangelist for data and analytics literacy at economy, organisational and individual levels. She is the founder of DNA Capitals which drives competitive advantage for organisations in all industries through taking full advantage of the opportunities which arise from digitization and big data. As a data and analytics evangelist, she is an active member of Tech Talent Assembly (TTAB) association which nurtures tech talents for lifelong employability, learning and sharing.
Catherine was formerly the Practice Chief of Analytics & Intelligent System at NUS Institsute of Systems Science (NUS-ISS), where she imparted her experience and knowledge to graduate students, business leaders and ICT practitioners. She also continues to serve as adjunct lecturer and coach to NUS ISS students and short course participants.