الفهرس 
The Research FrameworkOnly 14 pages are availabe for public view
 |  | from | 165 |  |  |
| | | from | 165 | | |
Abstract
Before the era of the internet, data about customers, vendors, and other data used to be entered by firm employees into the system. In the era of the internet, users’ usage of social media, applications, and exchange emails has arisen a different type of data created by the user community and then at later periods with machine learning, and artificial intelligence, the machines has started to create the data. That was and still a terrifying amount of data around institutions and a true challenge to coop with. That data should be taken into Firms’ consideration if they want to survive in the digital economy existed nowadays. Due to that data characteristics including its volume, velocity, variety, and more other V’s, these data were called ’’Big Data’’. Whatever the size of the data, the most important is how that data could be monetized or processed given the quality of Big Data Analytics to improve firm’s performance. It was obvious that quality problems in our community are still unresolved. The main purpose of the study is to examine the impact of Big Data Analytics Quality (BDAQ) on improving firms’ performance measured by indicators of firm financial and non-financial performance. This study provides substantial insights as it could be beneficial for the firm itself as it can determine firms’ BDAQ level and its relationship with the improvements in performance. A Case Study was carried out and the main field it applied up on is the Commercial International Bank (CIB) in Egypt. The targeted departments and bankers are not about anyone who worked for the bank, but specialized departments and bankers who deal with Big Data Analytics and its Quality were chosen. Accordingly, the study contains recommendations for CIB suggested to improve BDAQ level which in turn will improve bank performance. Key Words: Big Data, Big Data Analytics, Big Data Analytics Quality, Quality, Firm Performance, Financial Performance, Non-financial Performance.