• Make a complex data more accessible and understandable• Data types and sources• Visualization Tools and Software• Data Mapping and Geographic Visualization

• Acquiring, collecting, and ingesting large volumes of data from diverse sources• Storing and managing massive datasets efficiently• Identify patterns, trends, and anomalies• Regression analysis, clustering, classification, and deep learning techniques• Addressing ethical issues related to data analytics, including bias, fairness, and responsible AI

•  Descriptive Analytics involves data aggregation, visualization, monitoring of key performance indicators (KPIs), and regular reporting to provide a comprehensive overview of a business's performance against goals, utilizing charts, graphs, and dashboards.

•  Diagnostic analytics - Root cause analysis

• Hypothesis testing 

• Correlation analysis

• Comparative analysis

• Data drill-down

• Data mining.

• Predictive Modeling and Forecasting• Anomaly Detection• Churn Prediction• Supply Chain Optimization• Inventory Optimization