What's included

• Data Collection

  Extracting data from various sources such as databases, CRM systems, web analytics, APIs, and more. Setting up and maintaining ETL (Extract, Transform, Load) processes.

• Data Cleaning and Preprocessing

  Removing noise and anomalies in the data. Filling in missing values, correcting errors, and standardizing data formats. Normalizing and aggregating data.

• Data Analysis

  Performing statistical and mathematical analyses. Using descriptive statistics to identify key characteristics of the data. Applying correlation and regression analysis to uncover relationships between variables.

• Data Visualization

  Creating charts, graphs, and interactive dashboards to visually represent analysis results. Using visualization tools such as Tableau, Power BI, or Plotly.

• Model Building and Forecasting

  Developing and testing machine learning models to predict future events based on historical data. Evaluating and improving model performance.