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5 Steps To Transition Your Career To Data Science: Step 1 - Identify Your Ideal Job

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These lessons are part of Aryng’s Analytics Academy 2018 series for individuals interested in analytics career. 

If you devour all things analytics, even to the point of setting up Google alerts to help you begin or progress in your analytics career, then you’ll find this five-lesson blog series helpful.

These lessons are part of Aryng’s Analytics series for individuals looking to transition to a career in analytics or who are new to an analytics role. I hope to answer all the questions I have received from readers of my blogBefore we go further, understand your fit to an analytics role by assessing your own analytics aptitude. If you don’t have high analytics aptitude, you won’t have fun being an analyst.

Lesson 1 - Understand the analytics landscape and identify your ideal analytics job

So, what constitutes an analytics job? Is it the same as big data job?

The analytics landscape is fraught with over-hyped and over-used terms, so before we go further, let me briefly clarify some of the terminologies. (This subject is discussed in-depth in my book, “Behind Every Good Decision, so feel free to start there as well.)

Believe it or not, “analytics” is not synonymous with “Big Data” even though these days it is often mentioned in the same breath. Let’s discuss that in a moment.

First, let’s define “analytics” vs. “business intelligence” (BI). Business intelligence and analytics are actually two distinct processes that involve different tools and serve different purposes.

When a user interacts with a system (such as when you check out groceries from your local supermarket), data is produced, collected, cleaned and stored using data solutions including Teradata , Hadoop, and Oracle . Data is then accessed via reports and, increasingly, via graphical dashboards. BI includes all components of the operation, from when data is collected to when it is accessed.

Analytics, on the other hand, is the process performed on data that has been delivered by BI for the purpose of generating insights to drive decisions, actions and, eventually, revenue or other impacts. Data is converted to insights using analytics tools such as SAS , R, and Excel.

Now let’s talk about Big Data. Big Data’s ever-increasing volumes, variety, and velocity (known as the Three Vs) create issues of storage and visualization that make traditional business intelligence systems unstable. Big Data is thus a business intelligence issue, not an analytics issue. Our focus for this lesson, then, must exclude Big Data

What analytics jobs interest you?

Once you know you are interested in analytics, the question is, “What kind of analytics job is right for you?" Get an idea about the analytics jobs out there by typing “Analyst”, “Analytics” or “data scientist” in job forums such as LinkedIn, Icrunchdata.com or Monster. Below are some of the key job titles you will find, mapped to three major job categories. I will discuss differences in these job categories a little later. Note: If the title includes “Analyst” but the job doesn’t require analyzing data, then it is not an analytics job. For example, a “Business Process Analyst” does not have an analytics job and we will not be talking about those careers here.

From the chart above, take, for example, Marketing Analyst. Most jobs with that title fall into the Business Analytics Professional job category. Some of these positions need advanced analytics skills and thus fall under the Predictive Analytics Professional category. Data Scientist, on the other hand, is used very broadly and vaguely with jobs falling under all three categories. Some data scientist job descriptions seem to seek applicants strong in all three areas, which is not a very likely combination. I would recommend ignoring those jobs for now as it could take a lifetime of learning to become that “superhuman” data scientist.

Now, let’s talk about the job categories – Data Analyst, Business Analytics Professional, and Predictive Analytics Professional. Each needs different analytics skillsets, per the table below. For example, a business analytics professional needs strong business analytics skills along with the ability to access data through a GUI-based BI tool and analyze it in a basic analytics tool such as MS Excel. An understanding of basic statistics and, perhaps, testing skills may also be required. Note that, as with any job, these positions need additional skills specific to the industry served and job function.

So which jobs should you aim for? Most professionals with a BI/Data or Engineering background, i.e. those with experience in data structure, Information Management, data architecture, engineering, etc., can transition most easily into a Data Analyst job. If you have a business background—Product Managers, Project Managers, MBAs—consider a Business Analytics job. And if your experience has focused on statistics, operations research, Computer Science or algorithms, a Predictive Analytics professional job may suit you.

As you browse through available jobs, look through the requirements of the position. What skills and tools are listed (expert knowledge of SQL, ability to drive decisions based on analysis, etc.)? Use that information and the table above to identify the appropriate job category. Now, given your background, your own interest and your industry experience, shortlist your dream analytics job title from within the job categories appropriate for you. For example, if you have 5 years’ experience working as a Data Architect within the retail industry, your ideal analytics job category would be within the same industry as a Data Analyst and you can shortlist the titles from within that category.

Congratulations!

You are now one step closer to finding and landing that dream job. My next blog will help you identify your analytics skills gap and job requirements vis a vis your own background.

Meanwhile, if you are ready to start your analytics career transition in 2018, enroll in my FREE 60 minutes masterclass on 5 Steps To Successfully Transition Your Career To Analytics And Data Science. We are live streaming in your time zone.

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