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Data Science has become a become a big buzzword in the last 5 - 6 years and for the right reasons. The amount of data generated each year is increasing exponentially. Consequently, the need to analyze the burgeoning data lakes and employ it in driving business goals is increasing as well. However, at the same time there are is a segment of detractors in the field, who claim that the cost of using data analysis is more than the return it generates. This may or may not be true depending on your understanding of data analysis, business analytics, and data science.
The data engineering, data science, and business analytics require a good common set of skills at their base. However, they are very different at the professional level. And as you begin to learn and specialize, you need to be aware of the difference and skills you need to pick up. So in this learning path, we would understand some of that difference and cover learning path for the business side of data science.
Data Science is not meant for every organization and at all stages. One of the major reasons, that executives are dissatisfied with Data Science is its over-popularity, high premium tools, less experienced but costly employees and little returns. However, this is mostly the case with organizations that jump directly in using the advanced use cases of data science even for small needs. The road to data science goes via data analysis of daily business requirements that often go missed. Data science is casually used for the entire range of from :
It's not just the industry, even many students who have been entering into the field can have a mismatch in expectations in what they want to learn and what they want to be working on when employed. We can't escape the fact that the whole spectrum of data based skillset is referred to under the Data Science umbrella term.
So while the industry is gradually orienting and aligning job roles with particular data based skillset. We as learners need to be sure as well as to what we want to learn. In order to simplify this for our own Quick-Learners, we have created this learning path for those who want to understand and specialize in the business side of data science or Business Analytics.
For beginners, you can check out one the below Business Analytics courses:
Apart from data analysis, a big part of business analytics is to convey the business insights derived to different internal and external stakeholders. So apart from knowing how to analyze data, one should also develop skills to convey the insights and recommendation. Also most times, a business analyst may not have a very specific business problem. One would need to understand the situation as a whole, come up with assumptions, problem statements, and alternate solutions.
So here are some complementing skills that you'll need to get started in a professional business analytics job:
We hope that this would help you make an informed decision in starting in either business analytics or data science. Let us know in case of any further questions or feedback here, QuickCode team will be here to help you with your learning needs.