Data & Analytics

Evaluate and improve data quality with comprehensive frameworks for profiling, validation, and monitoring.

Transform data insights into compelling narratives that drive action using proven storytelling frameworks.

Create effective charts and visualizations that communicate insights clearly following best practices in visual design.

Advanced Excel techniques for data analysis including formulas, pivot tables, Power Query, and dashboard creation.

Design C-suite dashboards that communicate business health at a glance with strategic KPIs and clear visual hierarchy.

Systematic EDA techniques to understand data distributions, relationships, and patterns before formal analysis.

Analyze financial data, build financial models, and create reports with key metrics like revenue, margins, and cash flow.

Analyze conversion funnels to identify drop-off points, optimize user flows, and improve conversion rates.

Analyze healthcare data for clinical outcomes, operational efficiency, and population health insights.

Analyze workforce data to improve hiring, retention, performance, and employee engagement decisions.

Design compelling data infographics that communicate complex information visually and memorably.

Design meaningful KPIs and metrics that align with business objectives and drive decision-making.

Apply fundamental machine learning concepts to business problems with clear explanations and practical Python code.

Measure marketing effectiveness, calculate ROI, attribute conversions, and optimize campaigns with data-driven insights.

Create publication-quality visualizations with Matplotlib and Seaborn using advanced customization and styling.

Create interactive Power BI reports and dashboards with DAX measures, data modeling, and advanced visualizations.

Build predictive models to forecast trends, identify risks, and make data-driven predictions about future outcomes.

Analyze product usage data to improve user experience, increase engagement, and drive product decisions.

Master data analysis with Python using Pandas, NumPy, and data manipulation best practices for efficient data processing.

Perform linear and multiple regression analysis to understand relationships between variables and make predictions.

Automate data reports with Python, SQL, and scheduling tools to deliver consistent, timely insights to stakeholders.

Analyze sales performance, pipeline health, and forecast accuracy to optimize revenue operations.

Analyze text data to extract sentiment, opinions, and emotional tone from customer feedback and social media.

Write efficient SQL queries for data analysis including aggregations, window functions, CTEs, and performance optimization.