Duration: 5 days – 35 hrs
Overview
Welcome to the Discovering Data Analytics using SQL Server Training Course! This intensive program is designed to introduce you to the world of data analytics using SQL Server. Whether you’re new to data analysis or want to enhance your skills, this course will guide you through the process of extracting valuable insights from data using SQL queries, functions, and tools. Through a combination of hands-on exercises, practical examples, and interactive discussions, you’ll learn how to transform raw data into actionable intelligence for better decision-making.
The comprehensive 5-day course outline allows participants to thoroughly explore data analytics, data cleaning, and data visualization using Tibco Spotfire. The combination of theoretical knowledge, hands-on exercises, and final projects will enable participants to create meaningful insights from their data using Spotfire.
Objectives
- Understand the key concepts of data analytics and its role in decision-making.
- Utilize SQL Server for data extraction, transformation, and analysis.
- Write basic to intermediate SQL queries to manipulate and analyze data.
- Apply data visualization techniques to present insights effectively.
- Gain a foundational understanding of data analytics for further exploration.
Audience
- Professionals seeking to enhance their data analysis skills using SQL Server.
- Analysts, managers, and decision-makers aiming to leverage data for insights.
- Individuals interested in mastering SQL for data extraction, manipulation, and analysis.
Pre- requisites
- Basic familiarity with databases and data concepts is recommended.
- No prior experience with SQL Server or data analytics is required.
Course Content
Topic 1: Introduction to Data Analytics and Tibco Spotfire
Morning Session:
- Introduction to Data Analytics and its Importance
- Overview of Tibco Spotfire: Features and Benefits
- Installing and Setting Up Tibco Spotfire
Afternoon Session:
- Connecting to Various Data Sources: Databases, Excel, CSV, etc.
- Data Import and Cleaning Techniques in Spotfire
- Exploring the Spotfire Interface: Navigation and Basic Features
Topic 2: Data Wrangling and Preparation
Morning Session:
- Understanding Data Profiling and Quality Assessment
- Data Transformation and Cleaning in Spotfire
- Handling Missing Values and Duplicates
Afternoon Session:
- Advanced Data Wrangling Techniques: Calculated Columns, Data Transformations
- Creating Hierarchies and Grouping Data
- Hands-on Exercise: Data Cleaning and Transformation in Spotfire
Topic 3: Data Visualization Techniques
Morning Session:
- Principles of Effective Data Visualization
- Creating Basic Visualizations: Bar Charts, Line Charts, Scatter Plots
- Customizing Visualizations: Colors, Labels, Markers
Afternoon Session:
- Interactive Filtering and Linked Visualizations
- Advanced Visualization Types: Treemaps, Heat Maps, Box Plots
- Using Filters and Marking for Dynamic Exploration
Topic 4: Advanced Data Analytics in Spotfire
Morning Session:
- Introduction to Data Relationships and Data Joins in Spotfire
- Implementing Expressions and Aggregations
- Analyzing Time-Series Data: Line Charts, Heat Maps
Afternoon Session:
- Advanced Analytics Functions: Statistical Functions, Rank, Percentile
- Using Over Functions for Windowed Aggregations
- Creating Dynamic Expressions for Interactive Analysis
Topic 5: Geographic and Location Analytics
Morning Session:
- Visualizing Geographic Data: Maps and Geo Charts
- Customizing Maps: Layers, Markers, Regions
- Incorporating Location Analytics and Geocoding
Afternoon Session:
- Creating Interactive Geo Filters and Map Interactions
- Analyzing Spatial Patterns and Trends
- Hands-on Exercise: Creating Comprehensive Geo Visualizations
Topic 6: Dashboard Design and Project Work
Morning Session:
- Designing Interactive Dashboards: Layout and Composition
- Applying Visual Themes and Styles
- Creating Drill-Through Dashboards for Detail Analysis
Afternoon Session:
- Final Project Work Time: Designing Data Analytics Dashboards
- Presentations and Discussion: Showcasing Final Projects
- Best Practices in Data Visualization and Dashboard Design
Topic 7: Advanced Dashboard Features and Conclusion
Morning Session:
- Incorporating Advanced Visualizations: KPIs, Gauges, Advanced Charts
- Adding Dynamic Elements: Action Controls, Text Areas, Lines
Afternoon Session:
- Sharing and Collaborating: Exporting, Publishing, and Sharing Dashboards
- Course Review and Q&A
- Certificate Distribution and Closing Remarks
