September 2025 | Bali, Indonesia

As the demand for timely, granular, and dynamic statistics grows across the Asia-Pacific region, Mobile Positioning Data (MPD) has emerged as a powerful tool for statistical innovation. This three-week intensive short course is designed to equip technical professionals with hands-on skills to harness MPD for the production of official statistics.

Hosted by Statistics Indonesia (BPS) under the Regional Hub on Big Data and Data Science, this course offers a deep dive into the technical foundations, tools, and workflows necessary to process and analyze MPD. Participants will receive structured training in database systems, Python programming, distributed computing, and statistical analysis, all tailored to real-world use cases in mobility and tourism statistics.

Course Highlights

  • Learn to work with SQL, BigQuery, Python, and PySpark for MPD analytics
  • Apply advanced data techniques to real MPD datasets
  • Explore urban data systems through field visits to Denpasar and Badung Smart Cities
  • Collaborate on a final project simulating MPD use in official statistics
  • Engage with experts from government, telecom, and data science sectors

Program Components

The short course is structured into three integrated components, designed to provide a complete learning journey—from foundational knowledge to applied project work. This structure ensures that participants not only build technical skills but also gain practical experience in real-world scenarios.

1. In-Class Training (12 Days)

The in-class component delivers comprehensive technical instruction across four core modules:

Databases for Big Data Analytics (3 Days)
Participants will explore relational and distributed databases, covering SQL fundamentals, Google BigQuery, and Spark SQL. Emphasis is placed on designing scalable query workflows and data management strategies tailored to large datasets such as MPD.

Python for Big Data Analytics (3 Days)
This module introduces Python as a versatile tool for data manipulation and analysis. Training includes hands-on exercises in data wrangling, visualization, and an introduction to PySpark for distributed processing.

MPD Collection and Preprocessing (3 Days)
Participants will learn the technical pipeline for acquiring, cleaning, and structuring MPD for statistical purposes. Topics include spatiotemporal alignment, noise filtering, anonymization, and the transformation of raw logs into usable datasets.

MPD Analysis (3 Days)
The final technical block focuses on analytical techniques for deriving meaningful indicators from MPD. Use cases include mobility patterns, tourism flows, and population distribution. The module emphasizes reproducibility, visualization, and result validation for statistical reporting.

2. Benchmarking and Field Visits (2 Days)

To ground the course in real-world application, participants will visit:

Denpasar Smart City – A leading example of smart governance, using real-time data to optimize urban planning and mobility.

Badung Smart City – Known for its digital public service innovations and data-driven decision-making, especially in the tourism sector.

These benchmarking visits provide exposure to operational data ecosystems and foster regional dialogue on the use of MPD in public policy.

3. Final Project and Presentation (3 Days)

Participants will work in teams to design and implement a mini-project based on a real-world MPD use case. Guided by facilitators, teams will:

  • Develop an end-to-end data pipeline
  • Analyze MPD to generate statistical indicators
  • Present findings and receive feedback from a panel of experts

The final project encourages collaboration, innovation, and the practical application of all course content—serving as a capstone to the entire learning experience.

Contact

For any questions relating to the knowledge development series, please contact us by email at bigdatahub@stis.ac.id.