Big Data Analytics is a field that emerged due to the existence of vast, rapidly growing, and diverse data with different structures. Academics, researchers, and industries face challenges in accessing, pre-processing, classifying, and making accurate decisions based on detailed analysis. They also struggle to determine the best mechanisms for handling data, as such datasets require interdisciplinary knowledge and skills for effective anlysis.

Understanding the application of big data analytics rooted based on the understanding on what is big data and analytics.

Big Data is defined as extremely large and complex datasets that cannot be easily managed, processed, or analyzed using traditional data processing tools. It is typically characterized by the 3Vs:

• Volume – Massive amounts of data generated from various sources (e.g., social media, sensors, transactions).

• Velocity – Data is produced and processed at high speed in real-time or near real-time.

• Variety – Data comes in multiple formats, including structured (databases), semi-structured (JSON, XML), and unstructured (text, images, videos).

Malaysia needed 1,500 data scientists and 20,000 data professionals by 2020 to meet industry demands and remain competitive. However, according to the Malaysia Digital Economy Corporation (MDEC), only 80 data scientists were available in the local market. This significant gap required public universities to take proactive steps in creating an ecosystem that supports human capital development, adapts to Big Data Analytics (BDA) technology, fosters innovation, and positively impacts the national economy.

Universiti Teknologi MARA (UiTM) has taken the right initiative by introducing the Big Data Analytics Collaborative Group as a platform to equip staff and students with knowledge and skills in big data analytics. So far, no public university has offered a structured value-added program in BDA, highlighting the urgent need for UiTM to lead this national aspiration.

UiTM's BDA initiative began with the launch of Big Data Lab @ UiTM in Shah Alam on May 25, 2017, officiated by YB Dato’ Seri Idris Jusoh, Minister of Higher Education. UiTM then expanded its efforts by establishing 13 big data analytics labs across its campuses, officially launched on October 29, 2017.

Efforts have also been implemented to meet the needs of UiTM students and staff. One such initiative is the DataCamp program, designed to enhance UiTM members' knowledge in Big Data Analytics (BDA). The introduction of DataCamp courses was approved at the UiTM Executive Council level.

Students receive hands-on training in writing programming code using R, Python, or SQL with real data. On October 25, 2017, MDEC officially recognized students and staff who completed the DataCamp program as data professionals.

It is hoped that through the outlined BDA programs, the nation's second educational philosophy—developing human capital with a first-class mindset to face economic development challenges based on knowledge and innovation—can be realized.

Malaysia needed 1,500 data scientists and 20,000 data professionals by 2020 to meet industry demands and remain competitive. However, according to the Malaysia Digital Economy Corporation (MDEC), only 80 data scientists were available in the local market. This significant gap required public universities to take proactive steps in creating an ecosystem that supports human capital development, adapts to Big Data Analytics (BDA) technology, fosters innovation, and positively impacts the national economy.

a) Digital Sources

• Video Sharing

  • Introduction to Data Analytics (Note: video available) (watch here)

  • Data Analytics Awareness (Note: video available) (watch here)

• Types of Data Analytics

  • Descriptive Analytics (Note: video available) (watch here)

  • Diagnostics Analytics (in progress)

  • Predictive Analytics (in progress)

• Slide Sharing

  • Webinar - Data Analytics in Teaching and Learning: Visualization of Online Classroom Data (view)

  • Webinar - Teaching Big Data With Limited Resources: Practical Lessons from a Scaled-Down Lab (view)

b) Modules

• Module 1: Microsoft Teams for Education (in progress)

• Module 2: Data Collection for Students Insights (in progress)

• Module 3: Education Data Analytics: Analysing Students Engagement (in progress)

It will be conducted according to the relevant DataCamp modules required by UiTM. Specialized training according to domain requirements can also be carried out upon specific request.