Smart cities are interconnected networks of devices that collect, store, share, and communicate data all with an aim of improving efficiencies within the city. The data collected is an important source of information. It is used to design livable and resource-efficient cities for people to live in.
However, understanding the data that is gathered and stored within cities can be difficult. This is because the data often comes from a range of different sources including foot traffic data, traffic data, geospatial data, crime statistics, etc. In order to understand the data that is collected within these cities, we need data analytics. Keep reading below to find out more about smart cities, and how data analytics is used in creating them:
What is Data Analytics?
Understanding data at a deep level is extremely important to building successful businesses. Data analytics is the process by which raw data becomes useable knowledge. Once this process has taken place, the information collected can be acted upon.
Data analytics is essential in business as it helps organizations to optimize their performance. Implementing it into business models means that businesses can help cut costs by finding more efficient ways of doing business. Businesses can also use data analytics to make improved business decisions as well as to keep an eye on consumer trends and satisfaction. This can lead to better products and services.
The Benefits of Data Analytics
Data has the ability to offer a lot of benefits to businesses around the world. However, in order to unlock the value of this data, you need the analytics element. Data analysis gives businesses access to insights that can help them to increase their performance. Not only that, but it can also help them to improve their budgets, their knowledge of their customers, and much more.
As the importance of data analytics increases, it becomes even more important that we understand the benefits of data analytics, and why businesses should implement it. Here are some of the benefits of data analytics:
Improved decision making – businesses can use the insights gained from data analytics to make more informed decisions. Data analytics can eliminate the guesswork from developing products, planning, and marketing campaigns, choosing what content to create, and more. It gives businesses a 360-degree view of their customers, which means that they are able to understand them better, and they are more likely to be able to meet their needs.
More effective marketing – as we mentioned above, data analytics can help you to understand your customers better. Once you understand them better, you will be able to market to them more effectively. Not only that, but data analytics also gives you an insight into how well your marketing campaigns are working. Once you know this information, you’ll be able to fine-tune them for optimal outcomes.
More efficient operations – data analytics can be used to streamline your operations. It can also help you to boost your bottom line and save money too. When you have a better understanding of what your customers want, you waste less time creating products and marketing campaigns that don’t match their needs. This means that less money is wasted in the business. Not only that, but it can also mean that you see improved results in your company.
Improved customer service – once you have an insight into your customers’ wants and needs, you’ll be able to tailor your customer service to meet them. This will help you to create stronger relationships with your customers.
Who is Using Data Analytics?
Data analytics is currently being used by almost every industry. This includes the hospitality and travel industry where turnarounds can be quick. These industries use data analytics to collect customer data and identify any problems. Businesses will use the data to find out where these problems lie and use the information that they have gathered to find a way to fix them.
Another industry that uses data analytics is the retail industry. They use it to ensure that they are meeting the ever-changing demands of their customers. The sports industry also uses data analytics. For example, most premier league stadiums now have cameras installed that track the movements of players. This allows them to see how well their players are performing.
However, these industries aren’t the only ones to be using data analytics. In fact, almost every industry uses data analytics today. Even city leaders have started using data analytics as they try to create smart cities which are better for both the citizens and the environment.
What Are Smart Cities?
Lately, there has been a lot of discussion about smart cities, but what exactly are they? What defines a smart city and makes it different from other cities?
In most cases, a smart city is a city that uses technology to solve city problems and to provide public services. A smart city does things to improve social services, transportation and accessibility, promote sustainability, and give citizens a voice. The main aims of a smart city are to reduce waste, improve policy efficiency, improve economic and social quality, and maximize social inclusion.
While the term ‘smart city’ is still relatively new, the concept of smart cities isn’t. In fact, it dates back to Ancient Roman times. Ancient Roman cities used aspects of this idea, such as using technology to make the lives of citizens living in the city better and easier.
Data Analytics is a Crucial Component of Creating Smart Cities
As we mentioned above, data analytics has proven itself invaluable in almost every industry. One area it has proven to be extremely valuable is in the development of smart cities. In fact, data analytics has an important part to play across all aspects of city operations and public service.
Over the last few years, data analytics has played a crucial role in assisting cities to become zero-carbon, better manage their infrastructure in a sustainable, secure, and cost-effective manner, and improve urban mobility. However, these aren’t the only ways that data analytics has helped cities to become smarter. Here are some of the other ways that data analytics can be used:
Crime prevention – although data analytics won’t be able to prevent all crime from taking place, it can be used to help battle crime. Data analytics can be used to help law enforcement officials identify times and areas where crime is likely to occur. This allows them to deploy police officers to these areas at the right time before any criminal activity takes place. Currently, lots of cities around the world are trying out data analytics for crime prevention and many of them are seeing positive results. So, data analytics can be used to reduce crime in cities.
The change to zero-carbon cities – advances in data analytics can help cities, utilities, and other partners to optimize energy and resource flow to meet their ambitious zero-carbon targets.
City benchmarking – another great way data analytics can be used is for useful insights into the economic performance of cities. This information can then be used to compare one city against another to see how well they are performing.
Asset management – asset management is important for any city. Data analytics enables cities to better monitor and manage a huge range of city infrastructure as well as to collect valuable information about citizens. This includes how people use city assets. The insights collected from this data can be used to improve the public experience in the city. It can also be used to reduce risks and costs in the city too.
Transport – data analytics can be used to make the transport system more efficient, since it can reduce the number of delays and the amount of congestion within a city. However, this isn’t the only way data analytics can be used in this area. In fact, it can also be used to anticipate the demand for transport over a specific period. This would allow transport companies to reduce or ramp up the amount of transport on the roads depending on the predicted demand.
What is Holding Us Back from Creating Smart Cities?
There is huge potential for the better use of data in our cities; however, there are also a number of challenges that need to be addressed by city managers. Some of these challenges are fairly common problems that have for many years plagued data analytics projects, such as ensuring data quality. However, there are also a number of other challenges faced by city managers, including the following:
Data privacy – the development of smart cities is creating vast new data streams that have huge capability to improve city services. However, this is also putting cities at the front of the debate over the use and ownership of data. International and national data privacy regulations have an important role to play in making sure that these smart city innovations can go ahead. Cities in the U.S. need to be as involved in defining this new data environment as they are in managing and planning the physical infrastructure.
Securing data – if smart city development is going to happen, then the relationship between the citizens of a city and their government needs to change. This involves actively shaping the virtual infrastructure of the city and securing the vast amounts of data that are collected. The good news is that data analytics can actually help to protect data. This is because all of the data gathered in cities will be in the hands of a specialist analytics team.
Data integration – Although there are already massive amounts of data in our cities, we are often not using this data correctly. In fact, evidence suggests that most of the data collected in cities isn’t shared for the common good. This includes both public sector and private data. Not sharing information between organizations could be holding us back from creating smart cities that will benefit us all. Smart cities depend on how well an organization can analyze and share data. The ability to share information in real-time is important for all organizations and businesses. This means that in order to make the best use of data available in cities, both the public and private sectors need to share their data effectively.
The skills gap – one of the biggest barriers to smart cities is the lack of data skills. Overseeing and analyzing large amounts of information and creating insights for efficient policymaking or operational improvements requires skills that are in short supply. If we want to use big data effectively for city management, then we need to train more people in data analytics. Many universities in the U.S. are already trying to encourage students to get into data analytics. Courses such as an MA in Digital Marketing and Data Analytics are available 100% online and can be completed in as little as one year. For more information, check this article from Emerson College titled How Data Analytics Can Drive Revenue.
The Future of Smart Cities
Smart cities are now entering an important phase of development, where the main focus is on delivering improvements against key metrics and priority outcomes. This development requires data-centric perspectives and digital innovation to be included in city planning processes and service design.
Ultimately, the value of smart city technology investment is realized through the use of data to support real-time operational control, improve decision making, increase service efficiency and quality and improve engagement with businesses and citizens.
The ability to collect, understand and share real-time data across a range of organizations and services will change the way the urban environment is experienced and managed. However, in order to prepare for this new way of life, cities will need to create a strategy for city data, work with partners to establish data commons that can benefit everyone, and build their analytics capacity.
As you can see, data analytics plays a huge role in smart cities. Data analytics also offers a whole range of opportunities for businesses to develop new solutions and applications that make cities more efficient, sustainable, and healthier for citizens. Without data analytics, we would struggle to understand the data that has been collected and stored, meaning we would be unable to make our cities smarter. This is why data analytics is the key to delivering smart cities.
