I am Ivan, a data analyst and front end web developer

1. Data Mining and Preparing (ETL)

Once the objective of the analysis are set. Gather relevant data from various sources, such as databases, spreadsheets, APIs, or external datasets. Ensure data integrity and quality. Clean the data to remove any inconsistencies, errors, or missing values.

Main Tools - Power Query and Python.

2. Exploratory Data Analysis (EDA):

Perform initial exploratory analysis to understand the structure, patterns, and relationships within the data. This may involve summary statistics, data visualization techniques, and correlation analysis to gain insights into the data.

Main Tool - Python

3. Feature Engineering:

Create new features or transform existing ones to enhance the predictive power of the data. This might include feature scaling, normalization, encoding categorical variables, or extracting relevant information. Calculating new parameters to better evaluate data.

Tools - various libraries in Python and DAX in Power BI

4. Model Selection and Building:

Select appropriate statistical or machine learning models based on the nature of the problem and data characteristics. Train the selected models using the prepared data. Understand the type of prediction or classification task you're dealing with (e.g., regression, classification, clustering) and the specific goals and constraints of the problem. Chose different models to compare if no previous research is done about the problem

5. Model Evaluation, Iterate and Refine:

Evaluate the performance of the trained models using suitable metrics and validation techniques.

Iterate on the analysis process, refining models, features, or methodologies based on the evaluation results. This iterative approach helps enhance the accuracy and effectiveness of the analysis.

Cross validation and hyper parameter tunning.

6. Interpretation and Presentation:

Power BI- when the rubber meets the road,

Interpret the findings from the analysis in the context of the original problem or research question. Communicate the insights effectively through visualizations, reports, or presentations tailored to the target audience. Domain knowledge is very important.

Dashboards and Reports.