Benefits of Big Data in Business
- Data quality has a direct impact on business process efficiency. In purchase to pay process, poor quality vendor data can cause missing purchase contracts or pricing information which can lead to delays in procuring vital goods. Many companies use big data solutions or algorithms to simply do what they have already been doing, so that there is no data loss moreover if we run the algorithm against the data set, the result might be the list of individual who exhibits attributes of fraudulent behavior.
- In order to cash process, incomplete or inaccurate credit limits or pricing information can lead to overall customer service loss or reduce revenue or may increase service cost, with the help of big data technologies and the ability to run various algorithms more quickly, the data can be updated at regular intervals throughout the day.
- The systematic analysis of data or data profiling is used to assess the overall health of the data which leads to proper business decisions in accordance with the present situation because sometimes inaccurate data results in incorrect management, which means business decisions are based on incorrect information. For example, the more one can understand customers’ complex relationships, preferences, and interaction history with the company, the more relevant and timely business outreach.
Benefits of Big Data
As per Oxford English Dictionary, Big Data is “data of a very large size, typically to the extent that its manipulation and management present logistical challenges”. Big Data refers to technologies and initiatives that involve data that is too diverse, fast-changing, or massive for conventional technologies, skills, and infrastructure to address efficiently. But nowadays with the help of new technologies, it is very easy to realize the value of Big data, for example, to identify shopping behavioral trends of customers to improve stockage and pricing of the items. Government processes also get benefits and banking institutions are capturing data on customer interaction to model risk and fraud.