Your takeaways from this blog
✔️ How does the Skill profile of a Data Analyst look like?
✔️ What capabilities to have as a Data Analyst to become a better problem solver?
Ready to hit the road?
All right, Let's look at some Data Fundamentals which should be clear for a skilled Data Analyst. We'll spend some time reviewing the skills shown in the below image :
Data Types
✔️ Looking at data from the perspective of Facts and Dimensions. Ask any BI Developer, and you'll get them talking about them. What are they after all? Watch this 5 min video to know.
✔️ Having an idea of Derived Facts & Dimensions : Watch here and here.
✔️ Ability to figure out hierarchical dimensions in data : Watch here
✔️ Looking at data as a Statistician. Ability to figure out Nominal, Ordinal, Interval and Ratio data types. Watch this 6 min video
✔️ Ability to identify any spatial data
How does spatial data look like?
It can look like pins over Google Maps :
OR
As maps with boundaries of the geographic entity. In the case below, it is states of US :
- This is how spatial data may look like in an Excel sheet :
Here's an 8 min video talking about spatial data and their applications in the industry : here
✔️ Ability to identify time series data in the business processes :
Here's Dr. Nic's quick 3 min video to help you visualize time series and learn a bit about their properties. No need to go in depth. Just grab core ideas : here
Also, watch this 5 min video giving you a very intuitive understanding of what time series is and why is it different from regular data
Data Structure
✔️ Ability to differentiate between structured, semi-structured and unstructured data
How does structured data look like? Here's an example :
. Watch this video to understand properties of structured or popularly called as tabular data.
How does semi-structured data look like? Here's an example :
This format is particularly called as JSON. Watch this 2 min video to get a working idea of JSON.
- How about unstructured data? Images, Videos, Free text (ex. Facebook comments), music etc. It's ok if you don't know how to work with these. As a Data Analyst you won't work directly with unstructured data.
✔️ Ability to figure out the grain of the data.
Refer this 5 min video to develop a good understanding of granularity of data. Don't get distracted by the term Data Warehouse. Imagine it in the perspective of simple tabular Excel sheet.
Data Profiling
✔️ Ability to perform descriptive statistics on data
Keep in mind that if anyone mentions you to perform data profiling, they are simply asking you to perform descriptive statistics. At the minimum you should be able to create a summary on data as shown here :
Watch this 15 min video to understand how to perform descriptive statistics using the Data Analysis package in Excel.
Ensure that you are already familiar with :
- Measures of central tendency : here
- Measures of dispersion : here
- Measures of shape : Skewness, Kurtosis
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