The definition and importance of Big data

Big data is a large amount of data that is received by a business as it serves its customers through its various activities. A business receives both structured as well as unstructured forms of data. Companies such as Amazon, Google process the collected data to improve the effectiveness of its operations. Additionally, the reference to big data in terms of size is relative to the size of the business. However, the value of the data is in the insights that can is gained by analyzing what the customers are expressing (Sharda, Delen, & Turban, 2019). Conventionally, firms conducted telephone interviews to obtain what customers preferred and feedback about the company’s products and services (Big Data: What it is and why it matters, 2020). Investment in new technologies to discover new methods for data analytics, such as big data analytics, offer new sources of information for companies. Therefore, Big data entails the incremental status, availability, and utilization of customer information.

Big data is a resourceful tool in the development of company operations. The value of big data is in how a company can utilize it.  Big data can improve the financial status of the organization by reducing expenditures. Finances that the firm would have used in contracting extra human resources to handle data collection can be used in critical areas to upgrade the technological capacity to analyze big data (Sharda, Delen, & Turban, 2019). The employees of a company can also reduce the amount of time in making decisions through an automated analysis of big data. Big data analytics technology is more efficient than human-based methods (Sharda, Delen, & Turban, 2019). Big data analysis can also improve the process of developing products, and customizing offers for clients. Additionally, big data analytics is used in designing intelligent systems; these assist in smart decision making. As a result of big data analytics, a firm improve its risk management strategy; this will help in preventing financial losses as a result of undervaluing company operations risk

Data veracity

Data analytics is defined using data veracity, variability, and value proposition. The most crucial of the Vs is data veracity. The veracity aspect of big data is an area that has several opportunities as well as potential problems for the company. A firm can obtain a large amount of data through big data analytics; the company leadership must ensure the particular information collected is of good quality and is relevant to the company (Sharda, Delen, & Turban, 2019).

Additionally, the information has to correlate with facts; the information collected and analyzed should be trustworthy and accurate. Big data is complex; there is a need for technology that analyzes and interprets it. There is a need for statistical formulas to ascertain the quality and applications of collected data (Big Data: What it is and why it matters, 2020). Data veracity is essential since a firm cannot implement changes in operations without confirming that the big data is based on credible sources. There is, therefore, a need for Companies to partner with partners who can assist in verifying the credibility of sources of big data.

References

Big Data: What it is and why it matters. (2020). Retrieved from sas.com: https://www.sas.com/en_us/insights/big-data/what-is-big-data.html

Sharda, R., Delen, D., & Turban, E. (2019). Analytics, Data Science, & Artificial Intelligence: Systems for Decision Support (11th Edition). Pearson.