Big Data is an advanced technology to work on very large volume of a wide variety of data. This technology is fundamentally different from traditional applications of data, which are mostly processed in batch mode in SQL databases. The key differentiators are much faster processing of massive amounts of data in real time and advanced distributed computing for handling really large datasets. There are also significant differences in data management tools, systems design, and associated business opportunities.
There are many sectors which are continuously working on varied big data applications depending on their requirements. The fast growing industries like healthcare, transportation, retail, commerce, manufacturing, insurance, public safety, business intelligence, aerospace and many others are are utilizing the power of big data now a days.
Healthcare is one of the areas that are focusing on big data as they hope to decrease the amount of data that is being gathered by machines and improve the quality of their data. Data compiled by KPMG for the healthcare sector revealed the specific types of data being gathered for health-related companies.
These data included how much patients visit clinics and how much they can be expected to make payments or pay fees. It also included the data collected by hospitals, how often patients visit each ward, the data generated by residents who are visiting clinics, what type of prescriptions patients take, and so on.
A huge set of data in transport is facing problems related to data distribution and availability, confidentiality and security. Enterprises across the transportation industry suffer from the current data silo problems to the extent that most data is still not analyzed, controlled or stored in a reliable way. This creates a challenge for all enterprises.
With the rise of Big Data applications, many customers and transport organizations are planning to buy data analytics tools and develop new applications, which will improve logistics planning, forecasting and operational management, which will help optimize their data to make better decisions in more accurate and timely ways.
Building a robust data infrastructure for transportation businesses is an emerging trend today. For this, businesses need to move to the cloud and adopt data analytics tools to make the most of their data. Although there are advantages in storing data in the cloud, these advantages aren’t always obvious for different applications.
Different applications of Big Data empowering retail sector too. Processing huge amount of disparate data in real time will enable retailers to identify with increasing confidence in individual shoppers’ patterns, thereby optimizing a store’s inventory, marketing, sales, or purchasing flows to keep up with increasing consumer preferences.
Applying analytics to purchase streams will enable retailers to predict where to install a store’s next sign-up table, what the impulse purchasing trends are for other customers in a specific area, and what other pieces of the customer data will motivate that person to come in for a new style, color, or size of a product.
Marketing executives will also receive significantly more detailed consumer insights by applying analytics to customer data from their loyalty programs, online transaction histories, email preferences, and so on. Applications of big data to pricing, store management, and other processes will give retail personnel the ability to deliver significantly more personalized customer experiences at all levels of the purchase cycle.
Such highly personalized services can be delivered using existing online order management systems. Stores can be modified to offer consumers the opportunity to engage with a knowledgeable customer service rep to discuss desired product features.
Even more so than the introduction of robotics in manufacturing, the application of big data technologies in manufacturing and specifically manufacturing by big tech companies, such as Apple and Google, is spreading awareness of big data in general.
Companies like Google are now involved with developing smart cars & manufacturing systems that share the same sensors and data capture as the smart phones, computers & smart devices that people interact with every day.
But the application of big data in manufacturing applications is not just limited to new applications.
The Big Data concept is used by insurance firms to create new solutions for user information that enhance their experience. Insurance companies are currently struggling to gain valuable customer insights for predicting personal insurance risks, which are especially important for customers with high annual household incomes.
Over the next five years, the nature of big data applications on public safety will radically change, says an analyst at the Big Data Institute at University of California, Berkeley. The information stored in smartphones, notebooks, and desktop computers will become one big source of data that is not only relevant but highly relevant.
This makes the limitations of big data analytics on public safety a thing of the past. Public Safety was/is a challenging and great concern for any government or any safeguarding authority. Up to a certain level of extent this challenge has already been controlled by big data applications.
Let’s take the a few best examples of Big Data Applications on public safety includes:
- Use of high-definition cameras to identify patterns, perhaps learning when to deploy first responders, for instance.
- Regulatory compliance, for instance, is a business requiring a huge data & processes for data lineage management.
- Data collection processes for identifying the cause of injury, for instance, from vehicle accidents.
- Analytic models for pattern detection, including predictive analytics for detecting impairment due to drugs & alcohol.
The concentration of big data applications within aerospace is increasing: aerospace companies are expected to have an increased focus on big data over the next decade. Some of the advanced data analytics and advanced computing technologies that are enhancing the development of the aerospace industry include big data applications in aerospace.
The commercial aviation industry is using big data to further optimize processes and increase operational capabilities. All maintenance activities involve routine, repeatable tasks. However, some aircraft have greater operational requirements.
It is logical that the maintenance of such aircraft require innovative maintenance concepts and systems. By collecting a vast amount of maintenance data and analyzing them, maintenance professionals can predict when these planes are likely to suffer an operational issue before it happens.
This can avoid costly delays. Therefore, with the growing sophistication of maintenance equipment and systems, it is increasingly important that maintenance professionals have access to data that has been verified by expert consultants. Big data is also changing the way air carriers conduct business. Using big data to provide informed predictive insights will improve performance and further enhance the competitiveness of the commercial aviation industry.
Energy & Utilities
Big Data provides the energy sector with a wide range of potential and difficulties. Data from the new energy systems and tools are getting smarter & more advanced day by day. The data generated by energy generation, transmission, distribution, storage & consumption are analyzed with the help of sensors, smart meters and smart grids.
The distributed energy generation system provides cheaper and more flexible energy to customers, which ensures sustainable energy supply. These are the big challenges faced by energy sector today. The energy companies are investing a lot on the automation of their operations.
The automation process of energy management systems is developing faster than it ever expected. Smart Energy Solutions, using big data and analytics, are getting more reliable, powerful and efficient. The utilization of big data on energy services will bring a huge advantage to the energy sector. It will bring a new stream of energy, which will be helpful in lowering the dependency on conventional energy sources.
The most extensive application of Big data in education sector is to enhance teaching. The data analytics platform for education is at the core of the education system. The main objective of Data Analytics tool is to revolutionaries teachers to use them for the betterment of education.
Big data tools also allow teachers to collect, organize and analyze large amounts of student data in a way that makes them more effective educators. This has become a big deal in education because it has been created to focus teachers and students on using data to make decisions about what students need.
Travel & Tourism
Most of the Travel & Tourism sectors are extensively using the concept of big data to develop more personalized travel solutions. The top rated travel partners such as Kayak, Jambu and Skyscanner have great interest in using Big Data to fine tune travel scenarios.
Travel search companies are experimenting with Big Data applications such as predictive analytics, online image tagging and facial recognition. Some hotels also use big data analytics to gather information about your interests, preferences and knowledge of popular travel destinations. While one project may help guide travel planning, another may help you negotiate a better travel deal.
Communication, Media & Entertainment
Big Data applications in the communication, media & entertainment sector are growing rapidly and are expected to have a major impact on our daily lives. Their significance and the kinds of use cases they represent depend on many factors, including the capabilities of the hardware, the innovations coming from other industries, and how they align with emerging technologies.
If we think of applications like the music and movie industries of a decade ago, the data sizes are bigger now, the usage patterns are more diverse, and the sheer volume of data has increased dramatically. Such applications can have a massive impact on the data that companies collect
and how they store and process it. Such data includes things like images, audio, video, medical records, financial data, and weather data, among others. In the end, all of the data generated today is either an order of magnitude smaller or almost imperceptibly smaller than what was collected in the past, but it’s far from being impervious to disruption.
Top Emerging 11 Big Data Applications in 2021
Big data provides a great opportunity to the multiple sectors for reshaping themselves. Predictive analytics is a technique used by the majority of big data applications. In healthcare, big data are expected to drive healthcare processes and increase efficiency. As education is under immense pressure to increase efficiencies in processes, big data is highly likely to provide opportunity for big changes in the multiple sectors.