Data Research-Part 2

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Data Data governance has become one of the most critical parts of any organization; government institutions, financial institutions, health sectors, etc. this has led to the need for data management systems. Some organization especially the financial institution has been forced to have a data management tools to manage the complex and bulk financial data. In these firms, the most critical governance goal is to have accurate and reliable data with data accountability and traceability. To have a successful data governance program, there should have a tool-based implementation. Perhaps the most obvious driver for the use of data management systems is the growing transaction volume in numerical data reliance in almost all organizations. Due to this reasons, there needs to be a robust numerical data management system that can store and inspect numerical data in an organization. Financial institutions handle complex numerical data that requires software that can automatically investigate and analyze it. The main solution does inspect numerical data by use of Python raw string. A Regular expression, also known as RE specifies a set of matching strings. They can contain both special or ordinary characters, i.e., “A,” “a” or “0”. With Python, you can concatenate ordinary characters. Given characters will be listed individually by giving two characters and separating them by ‘_.’ For example 0-5 or 0-9. Through its ability to analyze given data, the software offers end-to-end enterprise solutions such as sale force automation (CRM), human resource management, manufacturing, and services support. Overall, Oracle software analyses numerical data and output

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