What Are Big Data Techniques?

Big Data Techniques are a collection of techniques employed to analyze large, diverse data sets. They incorporate advanced analytic technologies and the data may vary from terabytes to Zettabytes in size. It can include structured, semistructured and unstructured data. It could come from a variety of sources and is generated by a myriad of applications.

Customers generate a large amount of data every day when they send emails or use apps, interact with social media, and react to services or products. They also generate data when they walk into a store, talk to a customer service representative or make a purchase online. Businesses collect this information in the process of their daily activities and use it to improve customer loyalty and expanding into new geographic areas, or to develop new products.

Data is typically presented in an entirely different format than it was in the past. Data is no longer stored in databases or spreadsheets however, instead it is obtained from social media, wearables, and other platforms for technology. It is usually unstructured texts, images and videos and doesn’t have a fixed structure. This type of data has helped put the “big” in big data.

Another why not find out more characteristic of big-data is speed. This is the speed at which data is created and re-routed. All of these actions such as sending a text message or responding to an Facebook, Instagram or credit card purchase, or making a purchase, produce data that must be processed instantly. It is a challenge to handle due to this speed.