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Structured books help in building a step-by-step understanding of analytics concepts and techniques.
Visualisation methods support better presentation of analytical insights and findings.
Programming tools assist in cleaning and organising large datasets for analysis.
Most business decisions are now taken based on data instead of relying only on observation or experience. Sectors such as media, administration, and marketing are using data to understand trends, plan future activities, and improve performance. This growing importance emphasizes the need to learn the basics of data analytics for those who are planning to build a career in these industries.
However, beginners often find it difficult to understand where to begin, since data analytics involves learning statistics, programming, and interpretation skills at the same time. Online tutorials may provide basic knowledge for short-term learning, but books usually explain concepts in a more organised way. They help develop a better understanding over a longer period of time.
Some books on analytics that you can consider reading as a beginner:
Author: Anil Maheshwari
Price: Rs. 518
Data Analytics Made Accessible explains the basic concepts of data analytics in a simple manner so that learners can understand how data is used in decision-making processes across different organisations. It also includes examples from business environments, which help in connecting theoretical ideas with practical applications in real situations.
Also Read: Top 10 Data Visualization Types to Master in 2026: From Beginner to Expert
Author: Cole Nussbaumer Knaflic
Price: Rs. 2,198
Data analysis is not only about working with numbers but also about presenting the results in a clear and understandable format for decision-makers. Storytelling with Data discusses visualisation methods and explains how charts, graphs, and dashboards can be used to represent complex data in a more meaningful way.
Author: Peter Bruce and Andrew Bruce
Price: Rs. 1,475
Statistics is an important part of analytics work because it helps in understanding patterns and relationships present in datasets. Practical Statistics for Data Scientists introduces probability, sampling, and regression techniques in a practical way, and it connects statistical knowledge with real analytical tasks.
Author: Wes McKinney
Price: Rs. 2,500
Programming skills are often required in data analytics because large datasets need to be cleaned and processed before analysis. Python for Data Analysis introduces Python tools that are commonly used in analytics projects, and it explains how data can be organised and analysed using coding techniques.
Also Read:Best Data Visualization Tools to Tell Stories with Data
Author: Hadley Wickham and Garrett Grolemund
Price: Rs. 1,399
The R programming language is widely used for statistical computing and data visualisation tasks in analytics. R for Data Science explains how datasets can be imported, transformed, and represented through graphical methods while also introducing modelling functions used in analysis.
Author: Dawn Griffiths
Price: Rs. 3,302
Many beginners do not have a strong mathematics background, and this creates difficulty while learning statistical concepts in analytics. Head First Statistics uses interactive examples and visual explanations so that probability and data interpretation can be understood more easily.
As the use of data continues to increase in different industries, the need for basic analytical knowledge is also becoming more noticeable in professional environments. Reading structured learning material helps in understanding statistical reasoning, programming tools, and data visualisation methods gradually.
These books provide an introductory-level understanding of data analytics concepts and practical techniques, and they are suitable for those who are beginning to explore this field.
1. What is the importance of learning data analytics in modern professions?
Data analytics helps organisations identify trends, evaluate performance, and make informed decisions using structured data insights.
2. Is programming knowledge necessary to start learning data analytics?
Basic programming knowledge improves data processing tasks, but beginners can start analytics learning without coding experience.
3. Why are statistics important in data analytics learning?
Statistical methods help in identifying patterns and relationships that exist within structured and unstructured datasets.
4. Can data analytics be useful in non-technical career fields?
Data analytics supports decision-making in marketing, media planning, administration, and other professional domains.
5. How do visualisation tools help in data analytics work?
Visualisation tools convert complex data findings into understandable charts and dashboards for decision-making.
