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The work presents ITLingo-Cloud, a multi-organization, multi-workspace collaborative platform enabling rapid environment setup, workspace management, and statistical analysis for technical and business stakeholders. It synchronizes data with templates and reusable libraries, and automates extraction, validation, and document generation, supporting multiple technologies and languages. 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These practices are essential to increase performance, reduce costs and risks of failure, and guarantee the quality of results, keeping the work organized and controlled. ITLingo-Cloud is a multi-organization and multi-workspace collaborative platform to manage and analyze data that can support translating project performance knowledge into improved decision-making. This platform allows users to quickly set up their environment, manage workspaces and technical documentation, and analyze and observe statistics to aid both technical and business decisions. ITLingo-Cloud supports multiple technologies and languages, promotes data synchronization with templates and reusable libraries, as well as automation tasks, namely automatic data extraction, automatic validation, or document automation. The usability of ITLingo-Cloud was recently evaluated with two experiments and discussed with other related approaches.  \nKeywords: ITLingo-Cloud, Data Visualization, Data Analytics, Agile Project Management  \n1. Introduction  \nIT organizations are complex entities that intend to satisfy their customers’ needs and adapt to market competitiveness, aiming to adapt to advancements in technology development. Project management (PM) practices have contributed to increasing the performance of organizations with better control of these processes. The lack of PM practices can bring huge losses to organizations, such as high costs, the product does not fit the needs, or the profit may not compensate the investment, compromising the quality of the product and customer satisfaction [1] . The failure of projects is often due to a lack of communication between stakeholders, poor planning, disregard for requirements engineering practices, and lack of technical documentation [2],[3] .  \nGiving support to companies during the software development process is vital to reducing risks, uncertainties, and costs at different stages and to help meeting the deadlines. Hence, it is crucial to use software tools to support organizations' current activities and particularly support software development life cycles [4] . Since organizations generate data daily, data analysis and visualization techniques are essential to better understand actual and past project performance based on the analyzed data. Challenges such as handling conflicts and dependencies in resource allocation, planning under uncertainty, and facing threats during the execution of a project are frequent. Based on past project data, machine learning techniques can predict possible future undesired situations and recommend preventive  \nData analysis and visualization techniques for project tracking: Experiences with the ITLingo-Cloud Platform 1/19  \nactions [5] . These tools are crucial to help in planning work, maintaining the information available to the stakeholders to reduce inconsistencies through these processes [6] . In this scope, ITLingo is a research initiative that focuses on improving the rigor and consistency of technical documentation [3], promoting the productivity based on reusability of information and templates, and reducing inconsistencies and ambiguities. In the ITLingo project, some templates were developed to specify project plans, user requirements, and user interfaces aspects of software applications, among other business factors (e.g., PSL Excel Template, RSL Excel Template, ASL Excel Template) [3], [7], [8] . ITLingo-Cloud emerged inspired by this research focusing on overcoming the abovementioned situations supporting software deve","cbCaigYMnuadUm8f","https://ap.wps.com/l/cbCaigYMnuadUm8f","pdf",1533021,19,"English","# Introduction\n# Background\n## Data Analysis and Visualization\n## Agile Project Management","[{\"question\":\"Why are data analysis and visualization techniques important in project tracking?\",\"answer\":\"They help decision support by making it easier to understand actual and past project performance from analyzed data, improving control and reducing costs and risks.\"},{\"question\":\"What is ITLingo-Cloud and what does it provide for organizations?\",\"answer\":\"ITLingo-Cloud is a collaborative platform for managing and analyzing data across multiple organizations and workspaces, including setup, workspace management, and statistics for both technical and business decisions.\"},{\"question\":\"How does ITLingo-Cloud support automation and technical documentation?\",\"answer\":\"It supports automation tasks such as automatic data extraction, automatic validation, and document automation, while synchronizing data with templates and reusable libraries to improve rigor and consistency.\"}]","Data analysis and visualization techniques for project tracking - Experiences with the ITLingo-Cloud Platform | PDF",1789158543,7]