Learn Data Analytics with Excel, SQL, & Power BI: Data Cleaning, Visualization, Dashboards & Business Insights
What you will learn
Understand the data analytics lifecycle and apply the problem-solving framework to real-world challenges.
Clean, analyze, and visualize data using Microsoft Excel, including pivot tables and advanced formulas.
Build interactive dashboards in Power BI to communicate insights and track KPIs.
Apply statistical techniques like hypothesis testing and correlation to drive data-informed decisions.
Create a personal portfolio website to showcase your analytics projects and skills to potential employers.
Complete real-world projects and case studies from start to finish, simulating professional data tasks.
Query, filter, and manipulate data using SQL to extract actionable insights from relational databases.
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- Course Overview
- Embark on a transformative journey from data novice to analytics expert with this comprehensive program designed to equip you with practical, in-demand data analysis skills.
- This course demystifies the world of data, guiding you through the entire analytics workflow, from initial data ingestion and preparation to sophisticated interpretation and strategic communication of findings.
- You will develop a robust understanding of how to leverage data to answer critical business questions and drive impactful decision-making.
- The curriculum is structured to build foundational knowledge incrementally, ensuring a solid grasp of core concepts before progressing to more advanced techniques and tools.
- By simulating real-world scenarios, you’ll gain hands-on experience that directly translates to professional environments, preparing you to tackle complex data challenges with confidence.
- The emphasis is on building not just technical proficiency but also the critical thinking and problem-solving abilities essential for success in the data-driven era.
- Requirements / Prerequisites
- A curiosity for understanding patterns and trends within information.
- Basic computer literacy, including file management and internet navigation.
- A willingness to learn and engage with new software and methodologies.
- No prior coding or advanced statistical background is necessary; the course starts with the fundamentals.
- Access to a computer with internet connectivity and the ability to install software.
- Skills Covered / Tools Used
- Data Wrangling & Preparation: Mastering techniques to transform raw, messy data into a clean, usable format for analysis.
- Exploratory Data Analysis (EDA): Discovering patterns, anomalies, and relationships within datasets.
- Data Visualization Principles: Designing effective charts, graphs, and infographics to convey complex information clearly.
- Business Intelligence Reporting: Creating dynamic and insightful reports that empower stakeholders.
- Database Fundamentals: Understanding relational database structures and how to interact with them.
- Microsoft Excel: Proficient use of advanced features for data manipulation, analysis, and charting.
- SQL (Structured Query Language): Extracting, filtering, and transforming data from databases.
- Power BI: Building interactive dashboards and compelling data stories.
- Statistical Concepts: Applying foundational statistical methods to validate findings and draw robust conclusions.
- Portfolio Development: Articulating your analytical journey and showcasing your project successes.
- Benefits / Outcomes
- Become proficient in a sought-after skillset applicable across numerous industries.
- Gain the ability to transform raw data into actionable insights that drive business growth.
- Develop the confidence to present complex data findings in a clear and persuasive manner.
- Build a tangible portfolio of real-world projects to impress potential employers.
- Enhance your problem-solving capabilities and analytical thinking.
- Acquire the skills necessary to contribute meaningfully to data-driven organizations.
- Unlock career opportunities in fields like data analysis, business intelligence, marketing analytics, and more.
- PROS
- Comprehensive Skill Progression: Covers a broad spectrum of analytics tools and techniques, ensuring a well-rounded understanding.
- Practical, Hands-On Application: Focuses on real-world projects and case studies for immediate skill transfer.
- Industry-Relevant Tools: Utilizes widely adopted software like Excel, SQL, and Power BI, maximizing employability.
- Portfolio Building: Directly addresses the need for a professional showcase of acquired skills.
- Accessible for Beginners: Starts from foundational concepts, making it welcoming for those new to data analytics.
- CONS
- Time Commitment: Requires dedicated effort to master the range of tools and concepts presented.
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