Advance Data Visualization Course With Python Faridabad

Module 1: Advanced Business Analytics & Excel Power Tools

Data modeling with Power Pivot, automated data cleaning with Power Query (M-code basics), advanced lookup arrays (XLOOKUP, FILTER, UNIQUE), sensitivity analysis, scenario manager, and executive financial modeling dashboards.

Module 2: SQL for Analytics & Data Warehousing

Relational database querying, multi-table joins, subqueries, Common Table Expressions (CTEs), and advanced window functions (ROW_NUMBER, RANK, DENSE_RANK, LAG, LEAD) for customer cohort retention and rolling time-series aggregations.

Module 3: Python for Data Analysis & Exploratory Data Analysis (EDA)

Vectorized computations with NumPy, data transformation and manipulation with Pandas 2.x and Polars, outlier detection, data normalization, handling missing values, and statistical hypothesis testing.

Module 4: Exploratory Data Visualization & Statistical Storytelling

Visual encoding principles, chart selection heuristics, high-resolution visual storytelling with Matplotlib and Seaborn, and interactive drill-down web dashboards with Plotly Express.

Module 5: Power BI Mastery & Enterprise BI Modeling

Star schema architecture, dimensional modeling, writing complex DAX measures (CALCULATE, ALL, FILTER, time intelligence: YoY, MoM, YTD), Power BI Service publishing, row-level security (RLS), and scheduled dataset refreshes.

Module 6: Tableau Desktop & Executive Analytics Dashboards

Connecting to diverse data sources, calculated fields, Level of Detail (LOD) expressions (FIXED, INCLUDE, EXCLUDE), dual-axis visuals, dashboard interactivity (Actions, Tooltips, Parameters), and Tableau Story points.

Module 7: Industry Analytics Capstone Projects & Placement Portfolio

Complete 4 end-to-end commercial analytics projects: E-Commerce Customer Lifetime Value & RFM Segmentation, Healthcare Operations Efficiency Monitor, Omnichannel Retail Margin & Sales Dashboard, and SaaS Churn Analytics Suite.