Big Data Techniques is a grouping of methods that are used to analyze vast and diverse data sets. The data may be as massive as zettabytes and utilize advanced analytical techniques. It may contain semi-structured, unstructured or structured information. It can come from multiple sources and is produced by a variety of applications.
Every day, customers generate an abundance of data each day when they send emails or use apps, post on social media and react to products or services. They also generate data when they visit a store, speak to a customer representative or make a purchase on the internet. Companies collect all this information as part of their daily operations and use it to increase customer loyalty and expand into new geographic regions or develop new products.
Data is typically delivered in different formats than it was in the past. Data is no longer stored in spreadsheets or databases however, instead it is obtained from wearables, social media, and other platforms for technology. It is typically unstructured videos, images, text and does not have a strict structure. This variety has contributed to putting the “big” in big data.
Velocity is another characteristic of big data. It is the speed at which data is generated and moves around. When you send a message, respond to an Instagram or Facebook post, Facebook or Instagram post, or make a purchase with a credit card, all these actions create data that needs to be processed instantaneously. This speed is what makes huge data difficult to handle.
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