Big Data Techniques are a group of methods used to analyze large, diverse data sets. They utilize advanced analytic techniques and the data can vary from terabytes to Zettabytes in size. It can contain semi-structured, a structured, or unstructured information. It could come from a variety of sources and is produced by a wide variety of applications.
Every day, customers generate an abundance of data each day when they send emails and apps, make posts on social networks and react to services or products. They also create information when they go into a store, talk to an agent for customer service or make a purchase online. Businesses collect all this data as part of their daily operations and use it to increase customer loyalty and expand into new geographic areas or develop new products.
Data is delivered in a different format. It’s no longer available in spreadsheets or databases however, it is available through wearable devices, social media, and various other technology platforms. It is typically unstructured video, text, and images and doesn’t have a fixed structure. This type of data has contributed to putting the “big” in big data.
Velocity www.myvirtualdataroom.net/fundraising-digitalization-with-online-data-room-software/ is another characteristic of big data. It refers to the speed at which data is created and moved around. When you send a text, 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 instantly. Large amounts of data are difficult to handle because of this speed.