Tools to learn to get into an Entry-level analytics job
Introduction
If you’re a beginner in data analytics and are struggling to understand what topics you need to learn to get an entry-level job, then this article is definitely going to help you.
I’ve gone through 250+ job descriptions for various analytics roles in India in the last 1.5 years (data analyst, business analyst, product analyst, business intelligence analyst) and have identified the common skillsets/tools that you need to possess to crack an interview and land your 1st analytics job.
Tool 1: MS-Excel (Google sheets knowledge is a plus)
Excel is one of the most basic yet essential tool to master as a data analyst. Excel by itself is an excellent analytics tool for small size datasets.
Below are the topics one needs to cover while learning Excel to prepare for an analytics job:
👉 Lookups (vlookup, xlookup, hlookup and its use cases)
👉 Pivot tables, Pivot charts
👉 Power Query, Power Pivot
👉 Conditional formatting
👉 Various charts and their formatting
👉 Basic VBA/Macro
👉 Major Excel functions/formulas (text, numeric, logical functions)
Tool 2: SQL (with any one RDBMS tool)
There aren’t many jobs in the analytics field that doesn’t require SQL. Almost all data resides in some form of a relational database. SQL is the programming language which is used to create, store and retrieve data in a relational database.
There are different flavors of SQL based on the RDBMS tool (MySQL, T-SQL, PL-SQL, etc.) and you may learn anyone to begin with. The difference between them may lie in some syntax of functions, but that can be covered easily.
Below are the topics one needs to cover while learning SQL to prepare for an analytics job:
👉 Database fundamentals (primary key, foreign key, relationships, cardinality, etc.)
👉 DDL, DML statements (commonly used ones)
👉 Basic Select queries (single table queries)
👉 Joins (multiple table queries)
👉 Subqueries and CTEs
👉 Window functions (Rank, DenseRank, RowNumber, Lead, Lag)
👉 Views and Stored Procedures
👉 SQL Server/MySQL/PostGreSQL (any one RDBMS)
Tool 3: Power BI / Tableau
Power BI and Tableau are data visualization tools using which you can build interactive dashboards for business users. It’s important to learn either one of these tools as it boosts your data visualization capabilities. You may learn any one of these tools to begin with.
Below are the topics one needs to cover while learning Power BI (equivalent topics in Tableau) to prepare for an analytics job:
👉 Power Query, Power Pivot (data cleaning and modelling)
👉 Basic M-language and Intermediate DAX functions
👉 Filter and row context
👉 Measures and calculated columns
👉 Data modelling basics (with best practices)
👉 Types of charts/visuals (and its use cases)
👉 Bookmarks, Filters/Slicers (for creating buttons/page navigation)
👉 Advanced Tooltips, Drill through feature
👉 Power BI service basics (schedule refresh, license types, workspace roles, etc.)
Tool 4: Python / R
Python and R are scripting languages using which you can conduct data analysis. There are certain functions specifically designed within these languages that would help in data cleaning and visualization. You can easily automate the data analysis using these scripting languages.
Below are the topics one needs to cover while learning Python (equivalent topics in R) to prepare for an analytics job:
👉 Python basic syntax
👉 Python libraries/IDEs (Jupyter notebook)
👉 Pandas
👉 Numpy
👉 Matplotlib
👉 Scikitlearn
Conclusion
Most entry-level jobs require 3 out of the 4 tools mentioned above. You may learn a combination of any 3 of these tools to secure an entry-level role and then upskill on the 4th one after getting a job.
You may choose whichever combination works for you. Do not that Excel and SQL is mandatory in both the combinations.
➡ Excel + SQL + Power BI (or) Tableau
➡ Excel + SQL + Python (or) R
Hope this article helps provide clarity for beginners. Some topics may have been missed here, but I’ve tried to cover the major ones.
Save this article for your future reference. Also, do share it to your friends/colleagues who are planning to get into analytics.
You may find the study materials (free resources) in the featured post on my LinkedIn profile for various analytics tools.
Note: Most of the topics mentioned here are based on the job descriptions in India, but it’d be closely relevant to the job requirements posted in other countries too.
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