What is the job of a data engineer? How is it different from the role of a data analyst? What does a data scientist do? Confused? Let us put all the different aspect of data analytics into different buckets and make it all more manageable for you.
If you are looking to migrate to data analytics from any other branch (technical and non-technical), then read this article till the end to comprehend the different choices available for you. Please go through this article even if you belong to the field and are looking for options to upgrade your career and earn some better pay from the area itself. The field of data analytics is a continually changing one, and the roles mentioned here are defined loosely.
Also Read : The Different Data Science Roles in The Industry
There are four significant roles under data analyst responsibilities –
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A data engineer is the one who designs the platform and the structure which gathers and stores all the data from the users such as what item they are buying from an online store and what are the contents of their cart currently as well as on their list. Data engineers ensure that all the data are stored efficiently and are easily retrievable.
Data engineers are adept at working with a range of sources and framing ETL queries to collect data from them quickly. They then organise all the data in databases for the companies and individuals or others to use it from there.
You will need to acquire knowledge of various languages such as Java, Python, C++, SQL, Hadoop, Spark, Ruby, etc. on top of data analytics certification. It should be noted however that there is no need to learn all these languages as the requirement varies from company-to-company.
Being a data engineer provides you with the rare opportunity to work as both a software engineer and a data analyst.
Data analytics role expects you to prepare insights from the available data which directly impacts decisions in businesses. There is direct involvement of data analysts in everyday business activities. A data analyst or business analyst is expected to perform a significant amount of ad hoc analysis every day. For instance, data analysts help an e-commerce’s marketing team to identify the customer segments for the marketing or the ideal time to market any product or the reasons of the failure of the marketing campaign and how to avoid the mistakes in future. A good understanding of business, statistics and data manipulation is thus required in a data analyst.
The languages and tools which are required to be known by a data analyst include SQL, R, Excel and Tableau for some cases.
Every kind of company or organisation in today’s time possess a data visualizer or a business intelligence professional who is/are responsible for creating and presenting weekly insights and chart boards informing the management about the various metrics. The metrics may include the weekly sales of products manufactured by the company, the average time required for the delivery, or the total number of cancellations of orders and the reason for them.
A data scientist is a person who utilises the data in possession of the organisation to design business-oriented learning models and types of machinery.
For instance, data scientists go through all the available data of the company and look at the buying patterns of the consumers, identify the favourite items and more frequent users. Then they design algorithms based on that to automatically recommend the more popular products to frequent buyers with their navigation histories, purchasing histories or other similar parameters.