Fundamentals of Data Literacy, Critical and Analytical Thinking
The course is designed for anyone who wants to improve their data analysis and visualization skills. As part of the training, it will be possible to gain not only theoretical knowledge, but also to work practically, learning various useful techniques in data preparation, analysis and visualization, working in the MS Excel program. In addition, the acquired knowledge will be able to be applied in the future when working with, for example, Microsoft Power BI, Tableau and other tools.
Jānis Stūris
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Course target
Build a deeper understanding of data utility and management. Gaining hands-on skills in assessing data quality and troubleshooting common problems builds an understanding of how to make data-driven decisions while developing critical thinking.
Audience
The training is intended for company managers, product and service managers, consultants, project managers and those involved in any of the following processes:
- data input;
- correction and transformation of data;
- reporting, data analysis;
- presentation of results;
- viewing analysis results.
At Course Completion you will be able to
- Analyze data (basics in data analysis);
- Assess data quality and prevent common problems;
- Evaluate the results of data analysis and evaluate their objectivity;
- Ask the right questions and support your data-based opinion.
Prerequisites
Basic knowledge of Microsoft Excel is preferred.
Training materials
Training materials prepared by BDA.
Certification Exam
Not intended.
Course outline
- What is data, why do we need it, how can it provide the greatest benefit and what role does data literacy play in it?
- Overview of data acquisition and storage methods;
- Examples of the benefits of using them in different situations;
- Data records and structures – for qualitative data analysis;
- Common problems and how to fix them;
- Data categorization and examples of related analysis results;
- Data visualization and its role in data analysis;
- Basics of critical thinking and the most common problems that prevent obtaining objective results of analysis;
- Common problems in using data visualizations and statistics;
- Basic skills for both the creator of the analysis and the user of the analysis results to prevent problems and misleading conclusions;
- Fundamentals of data analysis and statistics;
- Finding correlations or outliers in data;
- Related practical examples and solutions for preventing problematic situations;
- Understanding of data set distribution and use in data evaluation;
- Finding and correcting various data gaps (e.g. missing or duplicate values, structure not suitable for data analysis).
If you want to get more information about this course, please contact us by phone +371 67505091 or send an e-mail at mrn@bda.lv.
