Big Data is omnipresent. It has penetrated almost every industry and is, in fact, the component that makes data science applications possible. AI, ML, deep learning – all require big data. As individuals and organizations globally continue to generate data on a large scale, big data becomes all the more important in our everyday lives. From online shopping to the shows we watch online, big data impacts everything around us. It has transformed business operations, marketing strategies, product campaigns, etc., for the better.
Why is Big Data significant?
Companies rely on big data for various reasons, such as optimizing business processes, improving operations, enhancing customer service, creating personalized and futuristic marketing campaigns, or even taking other actions to ultimately increase their profits and revenue. Businesses that can use big data effectively enjoy a potentially competitive advantage compared to those that don’t. By leveraging big data, companies can make informed business decisions.
Big data provides valuable insights concerning consumer behavior. Companies can use this information to optimize their marketing, promotions, and advertising to boost customer engagement and lead conversion rates. Historical and real-time data can be processed and analyzed for determining customer preferences and needs. This allows businesses to cater to their target audience promptly.
In this article, we have highlighted eight applications of big data in the real world.
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Real-world applications of big data
The primary aim of big data is to analyze vast volumes of real-time data to help companies make data-driven decisions. This includes tracking web server logs, tapping Internet clickstream data or the space of social media content, and assessing activity reports like text messages from customers, mobile phone calls details, emails, or any other machine data.
Businesses from different domains have started investing in applying big data for daily operations. For this, they have started investing in apps that examine large data sets for uncovering various hidden patterns, unfamiliar correlations, etc., that can be converted into actionable business decisions.
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Here are various ways in which big data is used today:
GPS and mobile maps
Gone are the days of confusing paper road maps. At present, satellite-based GPS technology allows us to navigate through any location in the world in real-time. Once you enter the starting point and your destination, GPS maps will provide you with the shortest route, approximate time to reach your destination, offer audio directions, show the various stops in your way, and much more.
Thanks to big data, developers can continuously improve GPS tracking and mobile mapping thanks to big data. With the introduction of multiple mobile-based apps and smartphones liberalizing telecom grids, the Internet of Things further improves. Since it generates vast volumes of big data, companies can tap into this data to make maps more data-rich. For instance, Google Maps has improved significantly in the past few years due to constant updates and tweaks.
eCommerce platforms now use big data from the moment we begin our search by exposing us to targeted advertisements, going all the way to the product delivery. Big data in online shopping allows businesses to understand buyers’ choices, preferences, and pain points. This is why you get to see targeted ads across multiple online platforms when you search for something online or on a particular site. This is a classic example of extensive data application in the real world.
A buyer’s online profile gives the seller a fraction of the information to optimize their sales. By tracking clicks and enabling the pay-per-click ad facility, the seller can begin to establish a substantially better purchasing profile of his goods.
Governments use big data to plan smart cities and urban centers. Big Data enables urban planners to develop a new understanding of the functioning of cities. One good example of how Big Data can optimize urban planning is transforming public transportation functionality.
Big data makes it possible to automate intelligent meters for efficient energy consumption. Smart meters accumulate data from sensors spread over an urban area. They decide where electricity ebbs and flows are maximum at any given time, just like transportation planners do with people. After this, the energy is further redistributed across the total grid to go to the places which need it the maximum. Although smart meters are an expensive investment in the short run, they will soon revolutionize the energy distribution sector. They shall automatically adjust to ensure efficient distribution and energy redistribution across a given network.
Marketers have always made good use of targeted ads, even before the Internet existed. The only difference between then and now is that previously marketers had minimal data at their disposal. They could only guess what consumers liked based on their radio or TV consumption, or their responses to e-mail surveys, etc. Marketing transitioned dynamically as the online space evolved, further thrusting considerable data reliance.
These days it’s possible to buy or collect massive troves of insightful data that can indicate what customers search for, click on, and prefer. There’s also been an influx of performance-related data that can accurately measure the effectiveness of various marketing campaigns through click baits, impressions, and several other modern algorithmic metrics. These tools are far more nuanced than just sales figures alone.
Crime prevention and prediction
Police departments can rely on high-quality, real-time analytics to offer actionable intelligence that can be used to recognize criminal behavior, perceive crime/incident patterns, and determine potential threats in a specific area. This allows them to proactively make residential and commercial areas secure and safe.
We currently live in an era that runs on information technology. Several financial and taxation management tasks take place through big data technology. Through big data usage, tax departments can effectively collect information related to the taxpayer’s data, adopt efficient management steps to process such information, and even establish a complete tax database.
Big data apps may be used by tax authorities to analyze both unstructured and structured data from disparate sources to pick out suspicious conduct and multiple identities. This helps them determine tax fraud cases.
So far, many financial managers of MSMEs have been rather vague regarding the usage of big data within the taxation spectrum. However, with proper training, this gap can be bridged to pave the way for revolutionary tax-related investigations.
Big Data aids in aggregating real-time visitors facts amassed from road sensors, GPS devices, and video cameras. The capability visitors problems in dense regions may be averted through adjusting public transportation routes in real-time.
These days, developed cities have come up with a smart-traffic decision support mechanism based on big data. The application of big data in traffic control breaks information silos and aids in sharing information across several departments and traffic systems. This intelligent traffic solution gathers all types of information related to traffic through AI sensors. This enables real-time monitoring and controlling of traffic. Additionally, it helps predict traffic trends based on practical data simulation and arithmetical models. Such a data-driven traffic system aims to help decision-makers in this field through scientific, accurate, and reliable information.
In a nutshell
To be shaped into meaningful information, big data needs to go through data integration, quality check, data governance, etc. These steps are essential to ensure that companies use quality data to shape their everyday business operations and decisions. Understanding how big data is applicable in real life helps businesses improve their data analysis operations for further growth and improvement.
As big data applications become more diverse and specialized, organizations of all sizes across industries will start to leverage them to accomplish their goals. This will inevitably create the need for skilled bid data experts who can work with colossal data volumes. If you’re interested in pursuing this field, you can enroll in upGrad’s Advanced Certificate Program in Big Data course. It includes industry-relevant topics, case studies, and live sessions with top mentors to offer learners a comprehensive upskilling experience.
We hope that, as a reader, you were able to benefit from the insights given above.
What are the primary parts of processing big data?
The four major components of processing big data are: Consumption Ingestion Loading Transformation Analysis
What are the three main principles of understanding the usability of Big Data?
The three main principles to understanding the usability of big data are the 3 Vs.: Volume Velocity Variety
Who is responsible for analyzing big data?
Advanced-Data Analysts, Data scientists, or business analysts are responsible for looking into big data analytics and even in the management of a business.
What are some of the finest big data tools?
Some of the best performing big data analyzing tools are: Apache Cassandra Apache Hadoop Tableau