Pre-requisite knowledge for data analyst course? Importance of mathematics, programming languages, data structures, database management, data visualization, critical thinking, communication skills etc. for data analysts.
To pursue a career as a data analyst, there are certain prerequisites that can help you prepare for a data analyst course. These prerequisites include:
Mathematics | Programming Languages |
Data structures | Database management |
Data visualization | Critical thinking |
Communication skills | etc. |
Table of Contents
Importance of Mathematics for Data Analysts:
Mathematics is required in every field, no matter how much one tries to avoid it – they will still use it in some manner in their life, business, job, profession etc.
Similarly, for data analyst who work with numbers all the time it becomes highly important to find average, to compare numbers, trends and what not. There is no fix requirement of math here, depending on the problem the data analyst improvise to find meaningful information out of raw data.
A strong understanding of mathematics is essential for data analysis. You should have a good understanding of statistics, linear algebra, calculus, and probability theory.
Statistics for regressions analysis, hypothesis testing etc.
Calculus for functions and/or models optimisation,
Probability to understand the likelihood of various outcomes and events in data analysis using bayes theorem, conditional probability etc.
This is not required in every problem, but quite possible in some problem everything got used and in some nothing will be used as the ultimate objective is to solve the problem not using the hi-fi techniques and do complex calculations.
Importance of Programming Languages for Data Analysts:
Programming languages have changed the world forever. Earlier analysing the data was very cumbersome task as one cannot handle millions of rows manually, but with programming languages this has changed forever.
Now, one who knows programming languages like python, statistics package like R or simple query language like SQL, can crunch huge amount of dataset and can bring relevant information useful for business in minutes.
And that is why programming languages are very important for data analysts.
Programming Languages: Familiarity with programming languages such as Python, R, and SQL is essential for data analysis. You should know the basics of coding, including loops, functions, and conditional statements.
Programming language is important for:
- Efficiently analysing large datasets,
- Automating repetitive tasks,
- Creating efficient data visualizations etc.
Some important programming languages for data analyst and some of their importance libraries, functions are:
- Python: NumPy, Pandas, SciPy etc.
- R: ggplot2, dplyr etc.
- SQL: for accessing, filtering, and extracting data from large datasets etc.
Importance of Data Structures for Data Analysts:
Data structure is very important to get cleaned good data seamlessly. Otherwise, one can face various and/or many problems depending how data was managed while storing.
Data Structures: Understanding data structures like arrays, lists, and dictionaries is important for data analysis. It will help you manipulate and organize data efficiently.
Some important reasons why data structure is important for data analyst are:
- For storing data efficiently like has tables are efficient for data retrieval,
- Efficient data retrieval by quickly locating the data in large dataset,
- Efficient data processing for e.g. queues are used in scheduling tasks,
So, all the big commercialised apps that you use deploy state-of-the-art data structures to make sure they app is working fine, opens in seconds and gives correct relevant information to it’s user in realtime.
Importance of Data Visualization for Data Analysts:
Data visualization is the art of presenting data if a beautiful manner i.e.
- Line or Bar Chart: If one wants to see trends then line chart or bar chart are well suited,
- Pie Chart: If one wants to see out of all the sales happened which all channels were involved and out of 100 what is the weightage of each then pie chart is well suited
- Waterfall Chart: If one wants to see increase and/or decrease with time in any metrics.
Like this there are many other kind of charts as well like tile, maps, multiple bars in one figure, multiple axis in one chart and so on.
Data Visualization: You should be familiar with data visualization tools like Tableau, Power BI, and Excel. You should know how to create charts, graphs, and dashboards to present data in a meaningful way.
So, some popular data visualization or BI tools are:
So, learn anyone as this can actually help in solving problems using data.
Importance of Critical Thinking for Data Analysts:
All the easy problems are already solved and only tough/complex ones are remaining.
In your life you will always face such tough situations where you will face problems that are quite complex and in such cases having a critical mind is very helpful.
Ask many question to approach a problem like why this has happened, how this has happened, when it has happened, any way to solve it, what the pros and cons of each step that are available to you now and so on.
Search online and you will see many online articles tells to ask why at least 5 times before coming to any conclusion or reaching to the depth of any problem.
Critical Thinking: Data analysis involves critical thinking and problem-solving skills. You should know how to analyze data and draw insights from it.
So, one you develop the habit of asking these questions and finding answers to these you will notice that your performance as an analyst and your ability to find good insight has really improved very much.
Developing a solid foundation in these areas can help you succeed in a data analyst course and build a successful career in the field.
Other relevant articles:
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- डेटा क्लीन कैसे करते हैं | Data clean kaise karte hain?
- स्क्रैपिंग क्या है – What is Scraping in Hindi
- What is Data Analysis – Attempt for In-depth Understanding
FAQs
Q1. What is the importance of Database Management for Data Analysts
Database Management: Knowledge of database management systems such as MySQL, PostgreSQL, and MongoDB is crucial for data analysts. You should know how to create, read, update, and delete data in a database.
Q2. What is the importance of Communication Skills for Data Analysts:
Communication Skills: Data analysts should be able to communicate their findings effectively to both technical and non-technical audiences. You should know how to write reports, create presentations, and explain complex ideas in simple terms.
Having the knack to talk in a way that someone listens and understand what you saying easily, or writing or presenting in such. away that it becomes very easy for the other person to understand what you are trying to say is a very good skill.
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