Hands-On Learning
Learn by doing with 174 practical lessons. Build a professional portfolio with actual datasets from industries like finance, healthcare, and e-commerce.
Career-Ready Skills
Master SQL, Python, Tableau, and Excel. Get certified with skills that employers actively seek and stand out in the competitive data job market.
Flexible Learning Path
38 structured chapters designed for busy professionals. Study anytime, anywhere, and get lifetime access to all course materials and updates.
About the course
Data is Future offers a Professional Certification Program in Data Analysis designed to equip students with industry-ready skills through comprehensive, hands-on training. The course features 38 structured chapters and 174 practical lessons that cover essential tools and techniques including SQL, Python, Excel, and data visualization platforms like Tableau. Students learn at their own pace with lifetime access to all course materials, allowing busy professionals to balance learning with their existing commitments. The curriculum emphasizes real-world application through project-based learning, where students work with actual datasets from various industries to build a professional portfolio. Upon completion, graduates receive an industry-recognized certification and possess the technical expertise employers seek in data analysts. Whether you're a complete beginner looking to break into the data field or a professional aiming to upskill, this program provides the foundation needed to launch or advance your analytics career. The course is available for free enrollment, making quality data education accessible to anyone ready to step into the data-driven future.
About DataisFuture
Data is Future is dedicated to making professional data analytics education accessible to everyone. We provide a comprehensive certification program that transforms beginners into job-ready data analysts through practical, hands-on training. Our curriculum covers essential skills including SQL, Python, Excel, and data visualization, taught through 38 structured chapters and 174 real-world lessons. Founded by industry experts, we believe data literacy is essential in today's digital world. We've designed our self-paced program to fit busy schedules while delivering the quality education and practical experience employers demand. Whether you're changing careers or upskilling, we're here to guide your journey into the world of data analytics.
Curriculum
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1
Excel Fundamentals + Essential Formulas
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Excel interface, ribbon, worksheets
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Cell referencing: Relative, Absolute, Mixed
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Basic formatting & shortcuts
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Essential formulas
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2
Data Cleaning + Professional Data Handling
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Remove Duplicates
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Flash Fill
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Text to Columns
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Data Validation
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Conditional Formatting
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Find & Replace
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Excel tables, sorting, filtering
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3
Lookups, Mapping & Data Relationships
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VLOOKUP
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HLOOKUP
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XLOOKUP
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INDEX + MATCH
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MATCH, OFFSET
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Multi-sheet lookups
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Mapping datasets
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4
Pivot Tables + Data Analysis Models
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Creating Pivot Tables
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Grouping (dates, categories, numbers)
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Calculated fields
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Pivot charts
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Drill-down analysis
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Slicers & timelines
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KPI analysis
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5
Data Visualization + Excel Dashboards
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Charts: Bar, Column, Line, Area, Pie, Donut, Histogram
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KPI Cards
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Dynamic charts
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Slicers + interactive elements
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Dashboard layout design
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6
Project Work
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Sales & Revenue Analytics Dashboard
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7
Introduction to Databases & SQL
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What is a database?
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SQL vs MySQL vs others
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Relational database concepts
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Tables, rows, columns, keys
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8
MySQL Installation & Setup
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Installing MySQL Server
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Using MySQL Workbench
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Creating databases and schemas
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9
Basic SQL Commands
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SELECT, DISTINCT
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ORDER BY, LIMIT
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WHERE filtering
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Operators: IN, BETWEEN, LIKE
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10
SQL Joins
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INNER JOIN
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LEFT JOIN
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RIGHT JOIN
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FULL OUTER JOIN
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CROSS JOIN
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Self JOIN
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11
Advanced Conditions
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AND, OR, NOT
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CASE WHEN expressions
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12
Aggregations
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COUNT, SUM, AVG, MIN, MAX
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GROUP BY
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HAVING
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13
Subqueries
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Subqueries in SELECT
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Subqueries in WHERE
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Subqueries in FROM
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Correlated subqueries
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14
Data Cleaning in SQL
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TRIM, REPLACE
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SUBSTRING
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LOWER, UPPER
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NULL handling
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COALESCE
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15
Window Functions
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OVER
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ROW_NUMBER
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RANK, DENSE_RANK
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LEAD, LAG
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Running totals, moving averages
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16
Table Operations
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CREATE, INSERT, UPDATE, DELETE
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ALTER TABLE
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TRUNCATE
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17
Data Modeling Concepts
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ER diagrams
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1NF, 2NF, 3NF
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Keys & constraints
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18
Views & Temporary Tables
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Creating and using views
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Temporary tables
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CTEs (WITH clause)
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19
MySQL Functions for Analytics
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Date functions: DATEDIFF, DATE_ADD, YEAR, MONTH
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Math: ROUND, CEIL, FLOOR
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String: CONCAT, LPAD, RPAD
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20
Performance Basics
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Indexes
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EXPLAIN query optimization
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21
Importing & Exporting Data
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LOAD DATA INFILE
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Import CSV
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Export results
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Connecting MySQL with Excel/Power BI
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22
Real-World Analytics Scenarios
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Sales analysis
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Retention analysis
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Inventory analysis
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Marketing analytics
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23
Introduction to Business Intelligence & Power BI
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What is BI?
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Power BI ecosystem
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Reports vs Dashboards
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End-to-end BI workflow
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24
Power BI Desktop Interface
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Canvas layout
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Visualization pane
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Filters pane
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Themes & formatting
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25
Getting & Connecting Data
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Excel, CSV, SQL Server, MySQL
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Folder import
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Web data
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Multi-table connections
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26
Power Query
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Remove duplicates
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Split columns
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Merge & append queries
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Unpivot and pivot
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Replace values
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Data type corrections
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Handling nulls
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Group By
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Conditional columns
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Automated refresh
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27
Data Modeling
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Star schema vs Snowflake schema
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Fact & Dimension tables
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Primary keys
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Relationship types
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Cardinality & cross-filter direction
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28
DAX (Data Analysis Expressions)
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Calculated Columns vs Measures
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SUM, AVERAGE, COUNTROWS
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CALCULATE, FILTER
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ALL, ALLEXCEPT
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SUMX, AVERAGEX
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DIVIDE
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Time intelligence
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29
Visualizations
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Bar, Column, Line, Area
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Pie/Donut
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Table/Matrix
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Cards & KPIs
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Funnel, Treemap, Waterfall
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Combo charts
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Scatter plots
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Gauge Charts
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Decomposition Tree & Key Influencer
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Mapping visuals
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30
Slicers, Filters & Drill-through
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Visual, page, report-level filters
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Slicers & sync slicers
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Drill-down hierarchies
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Drill-through pages
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Bookmarks for storytelling
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31
Dashboard Design Principles
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UI/UX rules
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Color psychology
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Consistent layout
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White space usage
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Navigation buttons
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Using containers
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32
Power BI Service
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Publishing reports
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Sharing & permissions
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Workspaces
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Dashboard creation
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Scheduled refresh
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Dataflows
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Gateway setup
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33
Performance Optimization
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Reducing dataset size
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Optimizing relationships
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DAX optimization
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Query folding
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Incremental refresh
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Aggregations
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34
Advanced Analytics Features
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AI visuals
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Forecasting
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Clustering
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Anomaly detection
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Smart Narratives
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35
Exporting & Integration
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Export to PDF/PPT
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Embedding reports
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Power BI + Excel
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Using Python/R
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Real-World Analytics Dashboards
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Sales dashboard
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Marketing performance
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Supply chain dashboard
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37
Project Work
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Supply Chain Analytics Dashboard
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38
Introduction to Python
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What is Python & why use it for data analytics
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Installing Python, Jupyter Notebook, VS Code
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Variables, data types, input/output
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Scripts vs notebooks
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What people are saying
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