Cheatsheets, eBooks, toolkits, and more -- curated to help you master data science and analytics.
eBooksA concise eBook on Top 10 Python Theory Questions is designed for quick interview preparation. It covers the most commonly asked conceptual questions with clear and easy-to-understand answers, helping learners strengthen their fundamentals and revise key Python concepts efficiently.
ToolkitsThe AI engineering roadmap for 2025 is a structured path to help you move from basics to building production-level AI systems. It combines programming, data, machine learning, and deployment skills into a step-by-step journey.
eBooksData cleaning techniques are methods used to identify, correct, and prepare raw data for accurate analysis. Clean data ensures better insights and reliable decision-making, especially when working with tools like Python, SQL, Microsoft Power BI, and Tableau.
eBooksA DAX e-book for Beginners is an introductory guide designed to help users understand and apply Data Analysis Expressions (DAX) in tools like Microsoft Power BI. It typically starts with the basics of DAX, including calculated columns, measures, and the difference between row context and filter context—core concepts required to build accurate calculations. The e-book also covers essential functions such as aggregation (SUM, COUNT), logical functions (IF), and time intelligence functions (TOTALYTD, SAMEPERIODLASTYEAR), enabling users to perform advanced data analysis. Additionally, it explains how DAX works with data models, relationships, and filters, helping beginners understand how to create dynamic and interactive dashboards. Designed for newcomers, this resource simplifies complex concepts with examples and use cases, making it easier to learn DAX step-by-step and apply it in real-world business scenarios.
eBooksCore principles for data visualization define how to present data clearly, accurately, and effectively so users can derive insights quickly. Tools like Tableau and Microsoft Power BI are built around these principles.
eBooksCommon SQL theory questions focus on fundamental concepts that form the base of database understanding. These questions are frequently asked in interviews to test clarity on how relational databases work and how SQL is applied in real-world scenarios. Typical topics include database structure (tables, rows, columns), types of keys (primary, foreign, unique), normalization, indexing, and constraints. Candidates are also expected to understand differences between commands like DDL, DML, DCL, and TCL. Other important areas involve concepts such as joins, subqueries, views, transactions (ACID properties), and differences between DELETE, TRUNCATE, and DROP. These questions help assess conceptual depth rather than just query-writing ability. Overall, this set of theory questions is essential for building a strong SQL foundation and performing well in technical interviews related to data analysis, backend development, and big data roles.
eBooksBig Data SQL Interview Questions & Answers is a focused preparation guide for roles involving large-scale data processing and analytics. It covers advanced SQL concepts used in big data environments, including joins, window functions, indexing, partitioning, and query optimization. The resource also highlights how SQL is applied within big data tools such as Apache Hive and Apache Spark, helping candidates understand real-world data workflows and distributed query execution. Designed for both beginners and experienced professionals, it provides clear, concise answers for commonly asked interview questions, making it ideal for quick revision and strengthening problem-solving skills in data-driven roles.
eBooksScala Big Data Interview Questions is a curated preparation resource focused on Scala-based big data concepts and interview readiness. It covers essential topics such as Scala fundamentals, functional programming, collections, and their application in big data frameworks like Apache Spark. The document includes commonly asked interview questions with concise explanations, helping candidates understand how Scala is used in real-world data processing, transformations, and distributed computing scenarios. Designed for both beginners and experienced professionals, it serves as a quick revision guide to strengthen problem-solving skills and improve confidence for Scala and big data interviews.
CheatsheetsA Microsoft Power BI Cheat Sheet is a quick reference guide that summarizes essential features and tools used for data analysis and visualization. It typically includes key concepts like data loading, Power Query transformations, data modeling, and creating interactive dashboards. It also covers important elements such as DAX formulas, relationships, visualizations, filters, and report publishing, helping users quickly build and manage reports. Designed for both beginners and professionals, it simplifies complex workflows and serves as a handy resource for quick revision and efficient use of Power BI in real-world projects.
Page 1 of 3
