InetSoft's Big Data Analytics Solution for Cities
The Challenge of Big Data for Cities
More than a buzzword for cities, Big Data is the term that describes the endless amounts of data created every day by a city's citizens, agencies, organizations, businesses, sensors, and machines. Understandably a city can struggle to reap the value of all this data. Without specially-trained staff or the latest analytic tools, it can be hard to easily understand the trends, patterns or relationships inside the data.
The value of Big Data is realized when information is extracted from the myriad sources, combined, and interpreted to uncover insights that lead to actions that make a difference in addressing the challenges facing our cities. Cities are complex, dynamic structures. With so many moving parts, they are challenging to predict. Yet, administrations are charged with managing the infrastructure and services with a goal of building a prosperous, resilient city.
One challenge is coping with contrasting areas of expansion and decline along with a diverse and changing populations. In terms of services affecting their economy, health, transportation and education are the essential services that affect anyone who lives, works, or travels in the city. All of these things are interconnected - which makes the analysis and the choice of actions more complex.
The Opportunity for Big Data
In the quest for economic success, social justice, and sustainability, Big Data can be an extremely powerful asset for cities. Linking data from different sources can break down the barriers between sectors or agencies. Examples of questions that could be asked of the data include: how does transportation usage vary with different weather conditions? Could social media be used for emergency planning?
Big Data allows cities to empower citizens' councils and city halls with better information about their communities and neighborhoods. The application of Big Data can help to tackle and answer hard questions affecting the future of the city, form policy, direct services, and justify budget to address housing, transportation, social and environmental issues.
InetSoft's unified Big Data solution will simplify turning a city's Big Data opportunities into actionable, self-service visual analytics.
How Memphis Uses InetSoft's Open Source StyleBI for Big Data Analytics
Modern cities face an unprecedented amount of data generated from transportation systems, utilities, public services, environmental sensors, and citizen interactions. The challenge lies in collecting, integrating, and analyzing this data effectively to make informed decisions that improve urban living. To address these challenges, Memphis has adopted InetSoft’s open-source StyleBI platform for its big data analytics initiatives. StyleBI provides a versatile and scalable business intelligence solution that enables the city to transform vast amounts of data into actionable insights, supporting smarter governance and more efficient operations.
One of the city’s primary goals was to consolidate data from disparate sources into a unified analytics environment. Transportation data, including traffic flow sensors, public transit usage logs, and ride-sharing records, is combined with environmental data such as air quality sensors, weather monitoring stations, and noise-level measurements. Social services data, including emergency calls, healthcare reports, and citizen complaints, is also integrated. StyleBI’s data mashup capabilities allow the city to bring these diverse datasets together without the need for complex ETL pipelines, enabling faster deployment and lower operational costs.
To gain operational visibility, the city built several interactive dashboards using StyleBI. The transportation operations dashboard visualizes live traffic data, congestion hotspots, and transit vehicle locations on an interactive map. Using real-time line and bar charts, city planners can monitor daily trends in ridership and road usage. KPI tiles display metrics such as average commute time, on-time bus arrivals, and public transit capacity utilization. The dashboard’s interactivity allows decision-makers to drill down by district, time of day, or transportation mode, enabling targeted interventions and resource allocation.
Environmental monitoring is another area where StyleBI has been instrumental. The city’s environmental dashboard aggregates data from air quality sensors, weather stations, and noise-level monitors. Heat maps highlight areas with high pollution levels or noise disturbances, while trend lines track changes over time. KPIs such as average PM2.5 levels, CO2 concentration, and decibel readings are displayed prominently, allowing environmental officials to respond quickly to emerging issues. Scenario modeling features in StyleBI allow analysts to predict the impact of policy changes, such as implementing traffic restrictions or green zones, on environmental quality.
Citizen engagement is critical for a data-driven city, and StyleBI supports the creation of dashboards that aggregate citizen feedback from multiple channels. Social media mentions, complaint logs, survey responses, and online service requests are visualized in real time. Word clouds and sentiment analysis charts help city officials understand citizen priorities and pain points. Funnel charts and bar graphs track the resolution rates of citizen complaints and requests, providing a clear measure of service performance. These insights help city administrators prioritize actions and enhance citizen satisfaction.
Big data analytics also plays a pivotal role in public safety management. StyleBI dashboards integrate data from police, fire, and emergency medical services, as well as real-time reports from CCTV and traffic cameras. Predictive analytics models identify crime patterns, accident hotspots, and emergency response bottlenecks. Map-based visualizations allow command center personnel to deploy resources strategically and optimize response times. Interactive dashboards let analysts simulate different scenarios, such as road closures or public events, to plan emergency services coverage more effectively.
The city has also leveraged StyleBI for budget monitoring and financial analysis. By connecting the finance department’s ERP systems with other operational data, the platform enables a holistic view of expenditures, revenues, and resource allocation. KPI tiles track budget utilization, departmental spending trends, and variance against forecasts. Charts and tables break down costs by category, project, or geographic area. This transparency supports more informed fiscal planning and improves accountability across city departments.
Healthcare analytics is another area where big data integration is providing tangible benefits. Hospitals, clinics, and public health agencies feed anonymized patient data, disease incidence reports, and vaccination records into the city’s analytics platform. StyleBI dashboards enable healthcare administrators to monitor disease trends, resource usage, and hospital occupancy rates. Predictive modeling helps anticipate healthcare demand spikes and manage staff and equipment allocation. Interactive visualizations allow healthcare officials to explore data by neighborhood, facility, or population segment to identify disparities and target interventions.
Education analytics also benefits from StyleBI integration. School enrollment, attendance, test scores, and resource allocation data are combined in interactive dashboards. KPIs such as student performance indices, teacher-student ratios, and graduation rates are visualized in charts and graphs. Drill-down capabilities allow education administrators to compare schools, districts, or student demographics. Scenario planning tools help forecast the effects of policy changes, such as new curriculum adoption or budget adjustments, on student outcomes.
StyleBI’s ability to perform predictive analytics and machine learning further enhances the city’s decision-making. Historical traffic patterns, environmental data, and citizen service requests are used to generate predictive models for congestion management, pollution mitigation, and emergency response. Scenario modeling tools simulate the effects of interventions such as traffic signal adjustments or new service policies, enabling city planners to make evidence-based decisions. This predictive capability allows for proactive rather than reactive governance, enhancing city efficiency and responsiveness.
Another key feature of StyleBI is its accessibility and self-service analytics capabilities. City employees without specialized technical skills can use the drag-and-drop interface to build dashboards, run queries, and generate reports. Ad-hoc analysis allows staff to explore data and test hypotheses independently, reducing reliance on IT and accelerating insight generation. The platform’s role-based security ensures sensitive data is protected while granting appropriate access to departments. This democratization of data fosters a culture of evidence-based decision-making across the city.
Finally, StyleBI supports mobile access, enabling city officials and field staff to monitor KPIs and interact with dashboards on tablets or smartphones. This mobility ensures that critical information is available wherever it is needed, supporting real-time decisions in the field. Alerts and notifications can be configured to inform staff of threshold breaches, such as congestion exceeding safe limits or pollution levels reaching dangerous levels. The combination of real-time data, predictive analytics, and mobile access positions the city to respond dynamically to emerging challenges.