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A Data Analyst is responsible for evaluating a wide range of data. He or she analyzes it for certain details and develops various concepts on this basis. In addition, the Analyst presents the data to his or her colleagues and superiors and makes it understandable to them. The analyses in this position are usually determined using a so-called data warehouse. This is a central database system that stores certain company data for analysis purposes.
In the morning, the current campaigns and monitoring are first checked. Monitoring is the monitoring of processes. It is an umbrella term for all types of systematic recording (logging), measurement, or observation of a procedure or process using technical aids or other observation systems.
(One function of monitoring is to determine whether an observed procedure or process is taking the desired course and whether certain thresholds are being observed so that otherwise it is possible to intervene in a controlling manner. Monitoring is therefore a special type of logging).
After all clicks, conversions, engagements, and impressions have been analyzed, this is shared and discussed with the team. Then the next task is to optimize current and new campaigns. Here, the “customer glasses” must always be put on to achieve an optimal result for the customer. At least one optimization per day should be the goal. The satisfaction of the customer is the priority here.
In the evening you put all the collected data into Jira, then you can start the next day well prepared.
The Data Analyst and the Data Scientist are two very similar professions. Usually, a Data Scientist formulates the questions for the company, which he wants to answer with his database, himself. He also programs for the company — in contrast to the Data Analyst, who is concerned exclusively with analysis and optimization. Also you give the task to other teams (e.g. from sales or marketing) and seeks a solution to their questions.
In this professional field there are various possibilities to specialize:
If you want to know how to become a data engineer, check out our blogpost How to become a data engineer!
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This post was published on 18. March 2020
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