Steve joJobsnce said that “people don’t understand what they want until you show it to them.” The data generated today is so huge that it takes to understand the right set of tools to analyze data. Business intelligence and data mining are the most hyped terms now-a-days but a lot of organizations fail to understand the they have to have the right framework to draw insight out of raw and unstructured information.
The data buzz is identified with the speed of data generation or velocity, the enormous data size or volume and accumulation of different types of data, also called as variety. These three Vs form the concept called as data complexity in big data.
What are we getting at?
Where does this enormous amounts of data come from? The answer is always around it. Customer level web behavioral data, textual data, mobile enabled data such as time and location, sensor data and data from social networks such as Facebook and Instagram. The business value of big data technology is undeniable. Taking into consideration the current scenario of data explosion, it has mandated businesses to incorporate technologies such as Hadoop, hive and pig to enhance the analytics and automation processes so that thousands of decisions can be effectively made without any human intervention or corresponding errors. Data science takes into consideration all the aspects of customers flying with a certain airway brand. And in case there is any changes in schedules or delays, the data scientist resolves the issue automatically to decipher disruption and maintain customer satisfaction.
This information age is continually affecting economic age and applying the right implications to analyzing, storing and retrieving information in a structured format, helps business thrive on their profits and illustrate a bright future for big data in the upcoming years.