Welcome to the KajoData Knowledge Base – a place where you can find well-structured and accessible explanations of key technologies used in data analysis. Whether you are just starting your journey or already working in the field, this knowledge base will help you quickly find answers to questions about Excel, SQL, Power BI, Tableau, Python, and Statistics. Each topic is presented in a concise and practical way, with examples that you can immediately apply in your work.
Why should you use this knowledge base? In today’s world, data plays a crucial role in business decision-making, and the ability to analyze it is one of the most sought-after skills in the job market. Here, you will find proven methods, practical tips, and explanations of key concepts that will help you better understand and utilize data in your daily work.
Table of contents
Excel – The Foundation of Data Analysis
Excel is one of the most widely used tools for analysts and businesses. With functions such as VLOOKUP, XLOOKUP, pivot tables, logical formulas, and text functions, Excel allows you to quickly analyze data, create reports, and visualize information. In this section, you will find practical guides on the most important functions and tips for optimizing your work in Excel.
Excel – other functions
SQL – The Language of Databases
SQL (Structured Query Language) is the foundation for analyzing large datasets stored in databases. Here, you will learn the basics of JOINs, data grouping, filtering, nested queries, and window functions, which are essential for effective data processing and analysis. You will also find query examples that you can apply in practice.
SQL – JOIN or UNION
SQL – Time or date operations
SQL – Window functions
SQL – Other operations / key words
Python – A Powerful Tool for Data Analysis
Python is one of the most commonly used tools in data analysis, combining versatility and ease of use. In this section, you will find guides on libraries such as Pandas, NumPy, Matplotlib, and Seaborn, which enable data processing, statistical analysis, and visualization. You will also learn how to use SQLAlchemy to work with databases and automate analyses with scripts. If you’re thinking about advanced data analysis, Python is a must-learn tool!
- soon 🙂
Power BI – Interactive Data Analysis
Power BI is one of the most powerful tools for creating dashboards and reports. In this section, you will learn how to efficiently transform data, create visualizations, and use DAX and Power Query to extract even more insights from your data. This is the perfect tool for professionals who want to present their findings in a clear and dynamic way.
- soon 🙂
Tableau – Advanced Data Visualization
Tableau enables intuitive creation of interactive charts and analyses. In this section, you will find guides on building dashboards, creating calculated fields, using filters, and parameters, allowing you to better interpret and present data in an engaging way.
- soon 🙂
Statistics – The Key to Understanding Data
Statistics is the foundation of any data analysis. In this section, you will find explanations of concepts such as mean, median, standard deviation, statistical tests, and linear regression. Through practical examples, you will see how statistics help in making data-driven decisions and drawing accurate conclusions.
- soon 🙂