## 4 Comparative Analysis
\begin{table}
\begin{tabular}{c c} \hline \hline
**Benefit** & **Description** \\ \hline Automation & Automation reduces manual effort and errors. Further, it enhances the automation of data integration and transformation processes. \\  & The integration of GenAI capabilities into the EGTL model significantly enhances its efficiency, allowing for faster data processing and improved availability for analytics, thereby boosting business intelligence outcomes. By automating the generation of optimized code, GenAI supports the design of well-structured database schemas, ensuring streamlined data flow [13]. \\ Data Quality & Improves data accuracy and consistency. Therefore, it is ensuring that higher-quality data are available for decision making. \\ Scalability in & Facilitates the automated deployment of underlying data storage architectures, by adding or removing structures depending on situation and requirements. It is not limited only to structures but also relates to various system components. \\ Synthetic Data Generation & Generates synthetic data for testing and debugging purposes in pre-production environments. It aids in privacy compliance and robust system testing. \\ Innovation & Facilitates the exploration of new data insights and patterns through advanced analytic capabilities. It stimulates innovation and empowers cooperation between humans and AI through GenAI models [13]. \\ Competitive & Alliance store incorporates DataOps principles: value-working analytics, embracing change, daily interactions, reflections, analytics as a code, and reuse [10]. It provides a strategic advantage by leveraging cutting-edge technology to enhance data operations and insights. \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Benefits of Alliance store (Proposed by this study). is advisable to consistently examine for outliers, and occasionally it is advantageous and suitable to eliminate them [28]. The correct identification of outliers during data collection will affect a product's data quality and thus the quality of information, knowledge, and decisions for the ecosystem's end user. Outliers also support extracting meaningful insights during data mining according to [29]. A central component of the proposed design is the creation of a data lake, which functions as the primary repository for all incoming data. Based on system requirements, the design can be adapted to incorporate the data lake within the Fusion, Staging, or Alliance stores. The data lake is designed to efficiently manage large volumes of diverse data, storing it in its raw, unprocessed state [30]. It can accommodate a wide range of data types, including user inputs, structured database records, and unstructured data from various sources. User interaction with the data lake occurs through an interface provided by specific applications, allowing access via API through the user interface or external tools. The data lake's adaptability and scalability make it an optimal solution for efficiently managing vast amounts of diverse data types, ensuring that valuable information is preserved throughout the entire process. After the data have been collected in the data lake, the next step is to conduct historical analysis, archiving, analysis, exploration, machine learning and advanced analytics alongside data processing. These steps together are necessary to produce simulation data, which will be loaded into a more organized and structured environment--the data warehouse. At this stage, the data are subjected to additional processing and refinement. The data warehouse is specifically built to enhance query performance, enabling efficient retrieval and pre-processing data for data visualization [31]. This phase of the architecture is key in converting data into a structure that is appropriate for more advanced analytical procedures, resulting in a decision-making ecosystem dashboard. The data warehouse is where data begins to acquire a more significant structure, facilitating intricate inquiries, trend analysis, and predictive modeling.