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Instructor: HR managers can also become overwhelmed
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with the amount of data science terms
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and buzzwords flying around.
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This means they sometimes label job positions
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in a misleading way.
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Thus, you can end up confused
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about how to match a job title with a discipline.
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So what are the job positions
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for each of the activities you see on the infographic.
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Data architect and data engineer
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and big data architect and big data engineer respectively
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are crucial titles on the market.
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A person in these roles is regarded
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as a very important part of the entire process
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of solving a data science or a business task.
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A data architect creates databases from scratch.
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They design the way data will be retrieved,
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processed and consumed.
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The tasks of the data engineer step on the work
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of the data architect.
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His primary job responsibility
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is to further process the obtained data
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so that it is ready for analysis.
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So the result of his work
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is something analysts and people in analytics positions
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will heavily rely on: a clean and organized dataset.
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Great.
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In fact, the data in a database is not created once
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and for all.
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You have a certain flow into and from the database.
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And there is a person who handles this control of data.
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Her position is database administrator
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and she mainly works with traditional data.
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Needless to say, administration of big data
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is usually automated.
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Fantastic.
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A BI analyst will do analyses and reporting
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of past historical data.
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What a BI consultant does exactly is vague though.
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BI consultants are often external BI analysts.
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Many firms outsource their data science departments
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as they don't need or want to maintain one.
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BI consultants would be BI analysts
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had they been employed.
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However, their job can be more varied
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as they hop on and off different projects.
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Finally, a BI developer is a person
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who handles more advanced programming tools,
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such as Python and especially SQL
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in order to create analyses specifically designed
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for the company.
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It is the third most frequently encountered job position
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in the BI team of a firm.
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Lovely.
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Now we must say that the remaining terms
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are somehow mixed and the line between the activity
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of one and the other is very thin.
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A person who employs traditional statistical methods
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or unconventional machine learning techniques
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for making predictions
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could still be labeled a data scientist.
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Moreover, even if the last two columns
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are about forecasting future values,
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data analyst is the job title
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for those who prepare more advanced types of analyses
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and do the basic part of the predictions
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of the data science team.
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Finally, a machine learning engineer.
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This job is tough to do but easy to classify.
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It refers to those who are looking for ways
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to apply state-of-the-art computational models
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developed in the field of machine learning
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into solving complex data science and business tasks.
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We hope you enjoyed watching this video.
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Thank you.
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