The role of Big Data in transforming the life of Smart Cities inhabitants

With increasing need of urbanization and rising expectations of citizens, government organizations and regulatory bodies are looking for ways to innovate urban planning strategies for smart cities efficiently.  Internet is now moving into everyday object and devices. Among all the cutting edge technologies that enable Internet of Everything (IoE), big data analytics is considered the keystone. Big data analytics is the process of collecting, organizing and analyzing large sets of data to uncover hidden facts, correlations and other insights. Figure below represents the phenomena of Big Data using five Vs.


On one hand big data analytics helps organizations to understand the information contained within the data. On the other hand it helps companies to make more well-versed business decisions. Big data analytics enables data scientists, predictive modelers and other analytics to examine large volumes of business data, as well as other forms of data that may be unused by the conventional Business Intelligence (BI) programs.

A recent research conducted by IDC concluded that until 2020, the digital universes will double every two years. To analyze huge data, big data analytics is typically performed using integrated functions such as specialized software tools and applications for predictive analytics, data mining, text mining, data forecasting and data optimization.

The exponential growth in data depicts an outstanding opportunity for global public sector organizations, specifically government leaders. The data being collected from devices, sensors, and physical objects is used to provide vivid solutions and decision-making capabilities. Consequently, making possible a faster stimuli, safer communities, exceptional efficiency, secure access to services and satisfactory citizen experience.

How to realize smart cities potential through big data analytics tools

In today’s digitalized world, imagine a digital citizen going about their usual daily routine. The most important thing as a government organization or planning body is to make sure comfort of the citizen. Allow individuals to live a purposeful and dignified life.

Like VITAS, they have incorporated innovative healthcare, thereby enabling an integrated client-centric service experience for citizen’s visit. With the advancement in technology and introduction of apps and wearable devices, our digital citizens are able to monitor their own health. They can share their health information with medical professionals, who also have access to the collection of health records of general public. So that they can initiate some preventative measurements before problem occurs and prepare the treatment in advance.

As a consequence of digitization, communities will be able to facilitate the management of data concerning healthcare and other services such as traffic and parking management, security, street lighting, water and waste management and more. It also supports the centralized analytics, to build a more efficient data-driven anticipatory approach. Below, the figure is showing names of some tools often used by Big data Analytics.


Proceeding towards the next stop in our digital community, our citizen will take a bus from a nearby bus stop. The citizen can connect to the free Wi-Fi while riding the bus through any smart phone. They can upload real-time data from physical world to the cloud, helping governing bodies to improve incident response and traffic management.

As an example, our bus-riding digital citizen can announce a traffic incident via social media while other riders may be busy calling authorities and jamming the phone lines. Some modern cities like Rio de Janeiro, have incorporated a system that allows assembling and sharing of important data for a coordinated and effective response. As a result, incident responders can quickly reach and assist those in need while city planners can make proper adjustments to ease traffic flow and resume transport schedules.

Singapore having entitled as the world’s first Smart Nation and a vision to “serve citizens of all ages and companies of all sizes” is planning to establish nationwide broadband networks and wireless hotspots, while incorporating things like sensor-based technology, with the aim to connect people, things, processes and data. Singapore is implementing a digital strategy that ensures mutual public and private benefit.

The city of Oslo in Norway reduced street lighting energy consumption by 62% with the help of smart solution. Moreover, the city of Portland, Oregon, used the same technology to optimize the timing of its traffic signals and was able to eliminate about 157,000 metric tons of CO2 emission in just 6 years.

With a good digital strategy, communities can better respond to local challenges and deliver efficient, secure citizen services with effective end-to-end assistance.

Further Reference

Join our big data analytics course to discover how our digital citizen is able to save time and reduce stress with less traffic and travel time each day and get your IoE questions answered on how to become the next digital community.

To further know about Big Data Application for Smart Cities, Security Challenges, and Technologies, you can join our Smart Cities Essential Courses here.

Big Data Archive

big data

NoSQL Databases

NoSQL databases usually store non-relational type of data on a super large scale and can solve problems which relational  databases can not manage such as  predicting subscriber behavior, indexing the entire Internet, or targeting ads on a large platform namely Facebook.

A list of popular NoSQL databases can be found below:

                                 Types of NoSQL Databases

Hadoop Overview

Hadoop allows distributed processing of large datasets across clusters of computers using comprehensive programming models.

hadoop basics

Hadoop mainly consists of:

(a) Processing/Computation layer (MapReduce),

(b) Storage layer (Hadoop Distributed File System).

haddop basics

MapReduce is a comprehensive parallel programming model for writing distributed applications of large amounts of data (multi-terabyte data-sets), on large clusters of commodity hardware in a fault-tolerant and reliable manner. The MapReduce program runs on Hadoop which is an Apache open-source framework.


5Vs of Big Data

The Structure of Big Data

Big Data consists of huge volume, high velocity, and extensible variety of data. The data in it will be of following three types.

  • Structured data: Relational data.
  • Semi Structured data: XML data.
  • Unstructured data: Word, PDF, Text, Media Logs.

The Applications of Big Data Analytics