Big Data has been around for quite some time, but the exact term originally surfaced in the early 2000’s. And since then, Big Data has been used to tackle business problems and create new and vast opportunities for consumers. Essentially, Big Data describes a collection of large datasets that traditional data processing softwares simply cannot manage. To describe in further detail, there are three big V’s in Big Data: volume, velocity, and variety.
Refers to the quantity of data, meaning the actual number of volume that needs to be processed. In most cases, this volume of data will be unstructured and will have a high number with low density. This means that the quantities of data can reach to unparalleled proportions. For example, think of Facebook and its datasets on the number of images uploaded online. Remember, the number of users are in the billions. That’s an insanely high volume of data!
This measures the speed at which the data is being generated. Velocity is important for companies to process because without it, the sheer volume of unstructured data alone will create havoc for businesses and organizations. If we stick with our Facebook example, it is noted that nearly 900 million photos are uploaded on a daily basis. Hence, velocity is the factor that processes these datasets and keep Facebook from shutting down.
Big Data is composed of more than just one type of data. In fact, there are hundreds or thousands. For example, photographs, sensor data, tweets, encrypted writing, email messages, etc. are all what make up some datasets. There are usually unstructured and structured data. Variety is the ability to classify these datasets into either of the two categories.
Big Data is used across multiple industries. Especially due to recent digital transformations and new technologies being developed on a daily basis, Big Data is used by companies and firms to drive performances and raise their competitiveness.
Either offline or online, retailers have adopted a data-first strategy to understand their customers’ buying patterns. For example, let’s say you are on the Amazon website and you want to see personally tailored recommendations. Amazon will utilize its own datasets and observe your shopping pattern and collect as much information to come up with a list of products you might be interested in buying.
Beyond helping companies adopt a better platform for investment and payment solutions, financial institutions are utilizing Big Data to detect fraudulent transactions and track the latest trends analyses.
Big Data is transforming the healthcare and medical industry by helping organizations identify better ways to treat patients. The key to prevent any serious illnesses is to understand the patient’s life as much as possible. That way, doctors can pick up any signs at the early stage.
There are countless ways other industries are utilizing Big Data. Others include weather prediction, resource management, computational social science, and smart buildings and cities.
Why Big Data?
From financial services to car manufacturing, healthcare, NGOs, etc., companies of all shapes and sizes can see the power of data. It is increasingly important to take advantage of big data analytics in the supply chain to generate deeper insights. The retail industry brings together a large amount of data in its supply chain and is at different customer touch points in many omni-channel operations.
According to a Softweb Solutions’ survey, retailers using predictive analytics increased sales by 73% compared to retailers who did not use predictive analytics. As a result, retailers use big data solutions through customer analytics to increase profitability and outperform competitors by personalizing in-store and online products.
Large companies are the biggest beneficiaries of Big Data, especially in their early stage of implementations. Why? Because with large companies, they have the resources to go deeper into data analytics and in turn, have a better focus on practical applications and businesses. They also have a greater commitment to budgeting and hiring new talents.
Market size of Big Data
According to COMTEX, during the forecasting period from 2019–2026, Big Data analytics market is anticipated to grow at CAGR 43.2%. Companies are using more methods to analyze data for enhanced efficiency and productivity.
Implementing Big Data technologies and practices into the company’s system is a huge transformational change. In practice, Big Data impacts central functions across the enterprise, from user relationships and product development to operations. With data, companies can be organized to change their mindset, becoming more data-focused, and assembling and acquiring the skills needed to manage data at speed and at scale.
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