The lines between analytics and data science can definitely be very blurry. Different companies might call the same position by two different names, but at their core, they do have some differences.
Below is an infographic from the faculty of the Online MS in Analytics at American University. I think the infographic is accurate.
In my opinion, a true data scientist should spend more time creating and programming new algorithms while a business analyst should spend more time applying existing algorithms.
A couple of notes
- Years of Education are not much different, but the academic disciplines are very different. Data Scientists tend to have degrees with more rigorous mathematical training. For me, this is the biggest differentiator.
- It appears financial institutions prefer business analysts while the government and colleges prefers data scientists
- Surprisingly, Business analyst jobs are projected to grow faster than data scientists (27% to 15%), not sure I totally agree with that!
Know Of Other Differences?
Please, Leave a Comment.
Brought to you by American University’s Analytics@American, a masters in business analytics
How about the compensation levels? My impression has been that an analyst generally earns much less than a data scientist.
I think I would agree with you, but unfortunately that data is not included in the infographic. Here is a page that provides some data to go along with your impression. https://datajobs.com/big-data-salary
Not necessarily true. In some cases, there are Business Analysts that are compensated just as high as Data Scientists. The same is true for Data Analysts.
In some cases, yes, but I think on average data scientists are compensated higher. See this post from Dezyre, https://www.dezyre.com/article/difference-between-data-analyst-and-data-scientist/332
“As of 2016, entry level salary for a data analyst ranges from $50,000 to $75,000 and for experienced data analysts it is between $65,000 to %110,000.
The median salary for data scientists is $113,436. Average Data scientist salary in US or Canada is $122K while data science managers leading the data science team at an organization earn an average of $176K.”
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Great post! Your emphasis on the importance of understanding the business context and problem-solving skills in both analytics and data science is spot-on. As you’ve pointed out, the ultimate goal of both fields is to provide insights and solutions that drive business outcomes and impact. Your analysis of the differences in methodology, tools, and skills required for each field is also very useful, as it provides readers with a clear understanding of the unique challenges and opportunities associated with each.
I appreciate your emphasis on the importance of collaboration and cross-functional teamwork in both fields. As you’ve noted, both analytics and data science require input and collaboration from a range of stakeholders, including business leaders, data analysts, and IT professionals. Your recommendations for developing strong communication, teamwork, and project management skills are also very helpful, as these are essential skills for success in both fields.