Big Data Techniques is a collection of methods used to analyze large and diverse data sets. The data could be as massive why not find out more as zettabytes. They also incorporate advanced analytical techniques. It can contain semi-structured, a structured, or unstructured information. It may come from a variety of sources and is produced by a wide variety of applications.
Every day, customers generate lots of data when they send emails, use apps, post on social media and respond to services or products. They also produce data if they enter a store or speak with an agent for customer service or make an online purchase. Businesses collect all this data as part of their business and use it to increase customer loyalty or expand into new geographic areas, or create new products.
Data is typically presented in different formats than it was in the past. It is no longer presented in spreadsheets or database files however, it is available through wearable devices, social media and various other technological platforms. It is usually unstructured videos, images, text and has no rigid structure. This type of data has contributed to putting the “big” in big data.
Velocity is the second characteristic of big data. It refers to the speed at which data is generated and moved around. When you send a text message, respond to an Instagram or Facebook post, Facebook or Instagram post or make a credit card purchase the actions all create data that must be processed instantaneously. This speed is what makes large data difficult to manage.