The word "big data" applies to high-volume, fast-pace and large range digital information stores. Big data research is the technology method which exposes trends, patterns, comparisons or other valuable observations in these large data stores.
Data Analytics is not a new field, since it has been a part of the industry as business intelligence and data mining technology for decades. The technology has significantly improved over the years, enabling it to manage much greater data sizes, to run queries quicker and to execute increasingly advanced algorithms.
Big data analysis allows analysts, researchers and business users faster and better decision-making using data that was previously unusable or inaccessible. Companies and Businesses can use advanced big data analytics techniques such as text analytics, machine learning, data mining, statistics and predictive analytics to gain new visions and insights from the data sources which were previously untapped.
Application can be built to aggregate semi- and unstructured or structured data from touch points your customers have with the company to get a 360-degree view of customer’s behaviour and drive or motivations for better and improved tailored marketing. These data sources can be from social media, IoT devices or sensors, mobile devices, sentiments data from sentiment analysis and calling log data.
For monitoring the transactions in real time, application can proactively recognize the abnormal patterns and behaviours identifying and indicating the fraudulent activity. Companies can predict and mitigate frauds using the big data analytics along with the predictive/prescriptive analytics and with the comparison of historical and transactional data.
BIG DATA ANALYTICS TO DRIVE SUPPLY CHAIN EFFICIENCIES
Big data analytics can be used to determine how products are shipped and reaching their destination. In identifying the inefficiencies and how cost and time can be saved or minimized. IoT device, Sensors, data logs and transactional data can help tracking critical information from the warehouse to the destinations.