Skill1 :The Why and How skill
This refers to the innate curiosity that comes naturally. For instance, remember asking questions back in high school or campus and wondering why you are the only one who raised your hand as other students jeered back at you? That is a valuable skill in Analytics. Simply because the more curious you are about the business problem, the more questions you’ll ask the stakeholder. Clarifies goals and objectives and enhances your data analysis process.
Skill 2: Comprehending data based on context
It’s all about understanding the full picture that the data presents.
The ability to fully grasp the context of your data can make a huge difference in your analysis process.
Skill 3: Breaking down things
Every data analyst needs to hone ‘developing a technical mindset’. Having a technical mindset means tackling each problem methodogically and logically.
An essential part because you can’t just jump into analyzing right after identifying the business problem. To adress the problem, start by breaking the process into smaller manageable pieces of information.
This includes gathering your data and then thoroughly cleaning it before you dive into the core analysis.
Skill 4: Data Design
It can be compared to working on a spreadsheetand then arranging the data neatly to spot patterns and insights. That whole process is called data design. This skill, like many others, grows stronger with practice.
Data Design is an extension of technical mindset.
In this phase, you’re rearranging cells and organizing data, making it easier to discover various patterns.
Skill 5: Data Strategy
Data strategy involves managing not just the data itself but also the people, processes, and tools involved in data analysis.
Think of it as a kind of resource allocation skill. It’s all about choosing the right tools and approaches for the specific business problem at hand.
For example if the business issue calls for a simple dashboard, the Ms. Excel will be the right tool. If it calls something more comprehensive and interactive like data modelling , then Power BI, and tableau are the go-to options.
By harnessing these analytical skills, you’ll find that your understanding of the problems becomes five times clearer and more concise, even before you begin the project.
Therefore, taking a step back to focus on the big picture and applying analytical thinking, as outlined above, is essential for every data analyst.