Big Data Techniques is a grouping of methods that are employed to analyze huge and diverse data sets. They incorporate advanced analytic technologies and the data can range from terabytes through Zettabytes in size. It can contain semi-structured, a structured, or unstructured information. It can be produced by a variety of applications and is derived from a variety of sources.
Each day, customers generate many data points when they send emails, use apps, post on social media, and respond to products or services. They also generate data when they walk into a store, talk to a customer service representative or make a purchase online. Companies collect all this information as part of their business and use it to improve customer loyalty as well as expand into new geographical regions or develop new products.
Data is typically presented in different formats than it was in the past. Data is not stored in spreadsheets or databases rather, it is sourced from social media, wearables and other technology platforms. It is usually unstructured text, images and videos and has no rigid structure. This diversity has helped put the “big” into big data.
Velocity is the second feature https://myvirtualdataroom.net/big-data-techniques-that-make-business-processes-more-effective/ of big data and it refers to the speed at which data is generated and moved around. All of these actions, such as sending an SMS or responding to a Facebook, Instagram or credit card purchase, or making a purchase, produce data that must be processed in a flash. This speed is what makes large data difficult to handle.