What's included

• Services

  As a data analyst, the client will typically receive the following deliverables: Data Analysis Reports: Comprehensive reports summarizing the findings, insights, and trends discovered through data analysis. These reports are often accompanied by visualizations and explanations of key observations. Dashboard or Visualization Tools: Interactive dashboards or visualization tools (created using tools like Tableau, Power BI, or custom scripts) to allow the client to explore and interact with the data on their own. Data Cleaning and Preprocessing Documentation: Detailed documentation outlining the steps taken to clean and preprocess the data, including any transformations, handling of missing values, and outlier treatment. Modeling and Analysis Code (If applicable): Code and scripts used to perform data modeling, statistical analysis, or any other advanced analytical techniques employed during the project. Data Insights Presentation: A presentation summarizing the key insights derived from the data analysis. This may include visual representations of data trends, patterns, and actionable recommendations. Recommendations and Actionable Insights: Clear, actionable recommendations based on the insights gained from the data analysis. These recommendations are aimed at helping the client make informed business decisions. Raw Data Files (If applicable): Providing the client with the original or cleaned datasets used for analysis, ensuring transparency and allowing for further exploration. Methodology Documentation: Detailed documentation outlining the methodology and approach used for data analysis, including any specific techniques or algorithms applied. Ad Hoc Analysis (If requested): Additional analysis or ad hoc reports that address specific questions or concerns raised by the client during the project. Final Project Summary Report: A comprehensive report summarizing the entire data analysis project, including the objectives, methods, findings, and recommendations. Training or Knowledge Transfer (Optional): If requested, a training session or documentation to help the client understand and use any tools, techniques, or models developed during the project.