Yes — it’s not a must have to work as a Data Analyst. In fact, a lot of people come from a non-CS background and succeed in this role!
Let’s look at the pros and cons of having a computer science (CS) degree and this should help you evaluate where you fall:
Pros of having a CS-degree:
- If the data analyst position requires you to have this degree in CS then you qualify! Fortunately this is not that common and usually it says bachelor’s required in cs, business administration or related field so as long as you have bachelors for positions that require it then you should be fine
- you might already have the basic tech skills that are needed for data analysis jobs and the CS degree might be used to validate that.
- you can pick up new tech concepts and tools fast(er) — with the cs background, it’s easier to pick up new concepts & tools — and you need to continuously do that to stay relevant.
Cons of having a CS-degree:
- Not enough business problem solving experience and/or lack depth in business knowledge — so if you have a degree in business then you come ahead! Especially if your background aligns with the role. For example: if you focused on Marketing in your bachelors and the role is focused around marketing analytics then you might have an edge
- I have a CS degree and then I followed it up with a masters from a “business school” — so this is just based on my experience but few CS students (without real world experience) are inclined to focus on “automation” and “bleeding-edge” instead of focusing on what the problem needs. Lot of data analysis doesn’t need to be automated or shouldn’t be automated and not every company needs <<insert the latest tech trend here: big data, deep learning>> — but CS students tend to do that. That’s what they feel most comfortable with so while that doesn’t stop from getting the job, this would impede their growth as a data analyst within the org.
So as you can see even if you don’t have a CS degree, you can still find roles that align with your other skills and in fact, you might be able to come out ahead if you can prove that you have basic quantitative and tech skills needed to get the job done.
Related: Paras Doshi’s answer to How do I prepare myself for a career in Data Analysis?
VIEW QUESTION ON QUORA
It’s a three-step process:
- Figure out where (location) you want to work and who (company) you want to work for.
- Note the “skills” required in job Descriptions at companies in your desired location(s) > find common themes from job descriptions > Pick up those skills if you don’t have them already!
- Start Applying!
- Getting a job is a function of Number of Job Applications and your conversion rate (Offers Received/#of Job Applications). Optimizing # of Job Applications is easy — you just need to apply to as many jobs as you could. To improve conversion rate, you would need to do number of things: clear HR/Culture-fit rounds, clear TECH rounds, create a portfolio of projects to talk about, etc.
- You could also consider applying for internships to get experience. This should help you land full-time roles.
Related Answer: Paras Doshi’s answer to How do I prepare myself to be a data analyst?
VIEW QUESTION ON QUORA
Recapping my social media activities during Jan 1 – Feb 20 2013:
That’s about it for this post.
If we want to read related past posts, here they are:
OCT 3 – OCT 10 2012
OCT 11 – OCT 18 2012
OCT 19 – NOV 11 2012
NOV 12 – DEC 31 2012
Let’s connect and converse on any of these people networks!
Update 1st August: I found this too: UCI MAchine Learning Repository http://archive.ics.uci.edu/ml/
Update 12 Nov 2012: I found this! Link to 400 datasets! http://www.datawrangling.com/some-datasets-available-on-the-web
Update 19 Dec 2012: Lynn Langit has a list here: http://lynnlangit.wordpress.com/public-datasets/
Recently on SQL Server Data Mining Forum, I answered a question about where to find DataSets for Business Intelligence Project.
Apart from Datasets AdventureWorks and Contoso data-sets, there are places where you can download data-sets to play with for your Business Intelligence, Data Mining or Data Analysis Projects.
Here is the List of data-sets that I have collected:
1. KDNuggests: Datasets for Data Mining
2. Quora: Where can I get large datasets open to the public?
3. Windows Azure Data Market
4. National council of Teachers of Mathematics
5. Introduction to Data Science: Data Sets
6. Hilary Mason’s Data-Set Bundle: https://bitly.com/bundles/hmason/1 (Also featured in Quora Link that I shared earlier)
7. And If you can’t find the data-set, ask it here: http://getthedata.org/
Have I missed anything? Do comment! I’ll add the link with due credit.
Technical forums are places where you can sense that there’s a hope for humanity! No kidding. If you think about it, it’s a place where humans help each other out without expecting anything in return (in almost all cases), what I just said is a fact. So now if you agree that forums are a great place, How about contributing? So if you’re not contributing already, here are the five reasons that may prompt you to start contributing:
1. Help someone out.
2. Solve a real-world problem
[Thanks Florin Dumitrescu for pointing this out!]
3. Discover great resources on Inter-webs. This is so because, while answering questions – people drop awesome links in their answers and invariably they are great free resources:
[Thanks Hardik Pandya for pointing this out!]
4. Learn from other super-smart people and Network with them
5. Test (or “Validate”) your technical know-how
And One more:
Earn reputation (Build your Brand, they say)
What do you think? If you are already contributing on technical forums – what motivates you? And if you’re not contributing already – what’s stopping you? And I believe that everyone knows about tons of things which others are interested in. You just need to find a place to share that!
This is one of the GEM i found on Quora. And what is Quora? Well, it’s a QA site. What makes it different? Well, for me it’s Quality of the content and the fact that who’s who of our small world are active on Quora. And people who have followed Quora knows that it tends to throw GEMS at you once in a while. yeah, and this question that “What are common mistakes that new or inexperienced managers make?” followed by a wonderful sequence of discussion is a perfect example to show why you should have an account on Quora. Anywho, Here is the link: http://www.quora.com/Management-Organizational-Leadership/What-are-common-mistakes-that-new-or-inexperienced-managers-make and the rest of the blog post is just me taking notes.
1. Human motivation is NOT tied to economic outcomes
2. Nothing can replace face-to-face interaction in motivation
3. Do not be slow in dealing with performance issues
4. Good managers put the blame on themselves and understand that any failing within the team is a failing of the leader.
5.Good managers attempt to redirect kudos and credit onto their team
6.play fair, open communication, admit to mistakes, praise in public, criticize in private, deflect credit to others, accept blame personally, be accountable, etc.
7.More authority is not associated with expertise, but rather accountability
8. Have enough guts and self-confidence in your own capabilities
Again the link is: http://www.quora.com/Management-Organizational-Leadership/What-are-common-mistakes-that-new-or-inexperienced-managers-make