What comprises a Data Analysis Process

Question 1

Steps in Data Analysis process

Answer 1

1) Understand the problem.
2) Data Collection.
3) Data Cleaning.
4) EDA.
5) Modeling.
6) Evaluation.
7) Analyze and Interpret results.
8) Derive Actionable recommendations.
9) Communicate the recommendations effectively.
10) Monitor changes made and see if they fit the purpose else make improvements.
11) Document the process.

Question 2

Explain Data Analysis steps in a bit of a detailed way?

Answer 2

1) Clearly define the problem by framing the objectives and understanding the key questions.
2) Data Collection : Gather data from relevant sources such that it is relevant, reliable, and sufficiently detailed to meet the objectives.
3) Data Cleaning : Prepare and clean the data. Remove duplicates, handle missing values, fix inconsistencies, and format the data properly.
4) EDA : Initial investigations using summary statistics, visualizations and correlation analysis. Identify trends, patterns, or anomalies that might exist.
5) Modeling : Selecting the appropriate statistical model based on problem, Training the model, Tuning the model and Making predictions or drawing insights. This is different from the Data Modelling in Databases.
6) Validation and Testing : Evaluate the performance of the model using various metrics. Accuracy, Robustness, Gaps and Errors, Fit, Interpretability, Runtime and Scalability are the most important aspects considered for Model evaluation.
7) Analyze and interpret the model outputs : Translate the results into actionable insights that relate directly to the original business objective.
8) Communicate Findings:
Present results in a clear and understandable way using visualizations and simple, precise language.
9) Provide actionable recommendations.
10) Monitor and Optimize : Continuously monitor the changes made based on your insights and optimize as needed.
11) Document the Process : Document the steps taken, assumptions made, and the methodology used in the analysis.