Data Analysis

Data analysis transforms raw datasets into visual insights using tools like Tableau to explore relationships between dimensions and measures. Analysts employ techniques such as data blending to combine different sources and clustering to identify significant patterns or "hotspots" within the data.

Interface example

Data Analysis using Tableau

Data analysis and insight extraction through Tableau's interactive dashboards, showcasing how dimensions and measures can be blended and clustered to reveal patterns in complex datasets.

Tableau Interfaces showing data blending and clustering features

Example use cases

Data Analysis in Action

Health

Public Health

Tracking disease trends to allocate medical resources.

Justice

Crime Prevention

Identifying "hot zones" via historical threat data.

Commerce

Customer Insights

Analyzing buying patterns to optimize retail stock.

Application to SMARTER Nation

We act as the "connective tissue" between different government agencies. Our system takes messy, scattered data—like satellite fire images and wind speeds—and combines them to show the big picture. For example, if a fire is detected, the system instantly calculates exactly which neighborhoods will be hit by the smoke.

Bibliography · Data Analysis

REFERENCES

Few, S. (2012). Show me the numbers. Analytics Press.
Knaflic, C. N. (2015). Storytelling with data. Wiley.
Murray, D. G. (2019). Tableau your data!. Wiley.
Provost, F., & Fawcett, T. (2013). Data science for business. O'Reilly Media.
Wickham, H., & Grolemund, G. (2016). R for data science. O'Reilly Media.