Data Analytics for Students

via Coursera

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Overview

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Data sits at the center of every modern business decision, but having data doesn't automatically produce insight. For most students and early-career professionals, the missing piece isn't the data itself, it's a structured way to think about it, question it, and act on it. This course builds that foundation, equipping you with frameworks, tools, and critical thinking skills to work confidently with data. You'll work through a proven five-step problem-solving framework, moving from defining the right business question to delivering data-informed recommendations. You'll practice core analysis techniques in Excel, apply the four foundational stages of analytics, and build dashboards that surface insights at a glance. You'll also map the full range of data sources driving business strategy, from sales and marketing to psychographic and competitive intelligence, sharpening your judgment to select the right source for each decision. By the end of this course, you'll be able to apply a structured analytical framework to real business challenges, evaluate and interpret the data sources that drive meaningful decisions, and communicate findings that influence strategy with clarity and confidence.e.g. This is primarily aimed at first- and second-year undergraduates interested in engineering or science, along with high school students and professionals with an interest in programming.

Syllabus

Evaluating the Role and Limits of Data in Decision-Making

You've got more data at your fingertips than ever before, but raw data without critical judgment is just noise. In this module, you'll examine how businesses extract value from data, identify the pitfalls that make it misleading, and build the critical judgment to balance quantitative evidence with professional intuition.

Defining Problems and Identifying the Right KPIs

You can have all the data in the world and still solve the wrong problem, which is why defining the right question before opening a single spreadsheet is one of the most valuable skills in analytics. In this module, you'll apply the first two steps of a five-step analytical framework: defining business problems with precision and selecting the KPIs that measure what actually matters.

Governing Data and Driving Decisions from Analysis

Your analysis is only as reliable as the data it rests on, and your data is only as reliable as the systems and practices that maintain it. In this module, you'll establish why data governance is the foundation every analysis depends on, apply a structured analytical process to move raw information toward insight, and build the judgment to translate findings into decisive business action.

Applying the Four Stages of Analysis with Excel and Visualization

You don't need to be a data scientist to work powerfully with data, but you do need to know which question you're trying to answer before you start. In this module, you'll map the four stages of analysis to the business questions they're built for, apply Excel's core capabilities to clean and interpret real datasets, and build the visualization skills that turn findings into insights decision-makers can actually act on.

Modeling Data and Building Dashboards for Scalable Reporting

You can have perfectly clean data in five different systems, but until those systems are connected through a shared structure, the analysis they can support is limited to what each one contains on its own. In this module, you'll build data models that combine sources without duplication, design dashboards that surface the right insight at a glance, and develop the infrastructure mindset that makes analytical work repeatable and proactive.

Mapping Your Data Ecosystem and Interpreting Sales and Marketing Data

You can spend hours building a perfect analysis only to realize you missed an entire category of data that would have changed your conclusion. In this module, you'll map your organization's data ecosystem, distinguish between internal and external sources, and develop the skills to interpret the sales and marketing data that drives business decisions.

Leveraging Cost, Psychographic, and Competitive Intelligence Data

You can build a technically perfect analysis and still arrive at the wrong recommendation if you are missing data on what things cost, what your customers actually believe, or what your competitors are doing. In this module, you'll apply cost data to pricing and profitability decisions, interpret psychographic signals to understand what drives customer behavior, and use competitive intelligence to sharpen your organization's strategic positioning.

Conclusion

You have spent this entire course learning not just what data is, but how to think with it, argue from it, and act on it. This final lesson marks the close of the course and opens the door to everything that comes next: continuing to build your analytical skills, staying curious about the data in front of you, and remembering that the value of data has never been in the numbers themselves, but in what you choose to do with them.