Today, a lot of companies and governments are keen to provide their critical data, such as open big data on requests for non-emergency municipal services from their Companies. Open big data is a kind of this data. It is necessary to adopt new tools and procedures in order to analyses and turn this data into knowledge due to its nature, which might be organized, semi-structured, or unstructured. The goal of competitive intelligence systems is to build up the tools and software to manage this data stream from data collecting to data analysis to data visualization to results dissemination. We are often reminded that we live in the Information Era, sometimes referred to as the Age of Big data. It shouldn't be a surprise that organizations should employ data-driven decision making to gain a competitive advantage. Big data analysis of these public massive data sets might be advantageous for society. This paper's goal is to provide a framework for the forecasting of big data analytics for service requests in light of the above. The algorithm forecasts what the future demand for these services will be after analyzing vast quantities of historically accessible, publically available data to seek for trends pertaining to service requests. The data should improve as a result of the processing, integrating, and interaction with new data, providing both broader and more in-depth views to aid in the process of making strategic choices. Big Data, which uses resources for processing and storage that are not unreasonably costly and can be put to good use, makes this possible. The numerous facets of big data as well as a framework that might be used to build big data applications.

Big Data Analytics, Big data, Service Requests, Data Visualization