Big Data is a term that refers to the large volume of data, both structured and unstructured, that flood business every day. For an organization to get the most out of this information, it is important that it knows how to identify all its sources. In general, as a concept, it is often said that it is something too big and bulky to be handled by just a common computer.
Big Transaction Data. They are the records of billing, calls, telecommunications, etc. Data that we can find in semi-structured or unstructured formats. It includes business data that refers to customer information, which comes from systems such as CRM; sales inventories; ERP transactional data, etc.
Social networks and web pages. It refers to all the information obtained through web transactions, and the content acquired from social networks such as LinkedIn, Facebook, Twitter, Instagram, etc.
Biometric Is that information that includes retinal scanning, fingerprints, genetic or facial recognition, etc.
Generated by humans. It refers to all the data that humans generate when we call a call center, write emails, electronic documents, voice memos, telecommunications, use of credit or debit cards, etc.
Machine to Machine M2M That is, those technologies that connect to other devices, and use them as sensors or meters, which generate a large volume of data, which needs to be analyzed. For example, when utility companies measure the consumption of water, gas or electricity through smart meters and then obtain data that is normally monitored to better understand certain characteristics such as frequency or voltage.
