Big Data Analytics
Big Data Analytics
Big data is important and has had an impact on how businesses are approaching their business strategy goals. Big data is significant because it takes unstructured data and extracts meaningful information which can be applied to the business strategy. Big data is described by the three V’s, volume, velocity, and variety. Volume refers to the large amounts of data you must process and by having more data it helps to make better predictions. Velocity represents the speed of data that is flowing in and out of databases and how it is hard to manage. Variety portrays the diverse formats that are being used with big data.
There are four types of big data analytics used for businesses to achieve their goals. Prescriptive analytics show you which steps should be taken. Predictive analytics use previous patterns and provide likely situations that can occur based on previous occurrences. Diagnostic analytics look at data from the past to figure out why it happened. Descriptive analytics observe real-time situations based on incoming data to determine what happened.
Big data relates to MIS 2502 Data Analytics in several ways. One way is how big data is used to store and retrieve data in databases like MySQL. Also, big data is used for advanced analytics using R-studio. While using R-Studio, we created decision trees and clusters and used the association rule. An example of how big data is used in practice is if you are a credit card company you can use descriptive analytics. With R-Studio and association rule you can determine the credit risk of individuals and whether to approve them based on their characteristics. Big data is better data and learning how to use this data could gain the competitive edge for businesses to achieve their goals.