Role of a Data Engineer
a Data Engineer is to build data pipelines. Data engineers build data pipelines so that the data can be used for below purposes -
- displaying data in the form of chart & graphs on dashboard to get quick insights
- generating reports for management to take decisions
- generating Machine Learning model for businesses to make data-driven decisions.
Data in the current world comes from many sources like web pages, applications' databases, social media, files, videos, images etc. The data is in different formats.
The traditional data which was from application's transactions - that was Structured data as it was schema-based. But along with that we have Semi-structured and huge Unstructred data. So, the data coming from different sources and different types need to be stored accordingly. Data Lake is used to store the data from various sources. But choosing the right Data Lake is also an important task. There are many factors which determine which Data Lake you should consider for given scenario. For example, is the data lake supporting the data type which you are planning to store in it? Also, since the data is increasing in size, is your Data Lake capable enough of handing change in demand, etc.
The traditional data which was from application's transactions - that was Structured data as it was schema-based. But along with that we have Semi-structured and huge Unstructred data. So, the data coming from different sources and different types need to be stored accordingly. Data Lake is used to store the data from various sources. But choosing the right Data Lake is also an important task. There are many factors which determine which Data Lake you should consider for given scenario. For example, is the data lake supporting the data type which you are planning to store in it? Also, since the data is increasing in size, is your Data Lake capable enough of handing change in demand, etc.
The data which comes from these sources can't be used directly as it may contain duplicates, null values, outliers etc. The data needs to cleaned-up before it can be used further for generating reports or Machine Learning models. This process is called Data Wrangling.
Next the data needs to be processed so that it can be used for the purposes mentioned above. Once the data is transformed then it is ready to be used as an input for generating reports or ML models. There are various tools used to display the data in the form of charts & graphs like Tableau, using Python libraries like Scikit, Matplotlib etc.
Since data is generated enormously in today's world which is used to get insights useful for businesses to take decisions, predicting the behavior and there are many more use cases for it, so the role of Data Engineers has definitely become very important now.
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