Before we dive into the role of the data engineer, let's acknowledge that it can be a little confusing when you hear about the various ‘data’ roles that currently exist. So what exactly is a data engineer compared to a data modeler, or a data analyst?
Let's start with perhaps the easiest role to describe: Data Analyst. A Data Analyst uses tools to work with data to answer business questions and derive insights. Data Analysts focus on the usage of data and less on how to collect it and prepare it. (though some data analysts would argue they do it all!)
Data engineering is the building of systems to enable to collection and usage of data. This data is usually made available to data analysts or data scientists who need large data sets to power analytics or train AI models. They need access to large and diverse data sets that come from a multitude of systems, often in different formats and from different technologies.
The role of the Data Engineer to make that data available at the right time, in the right format, and at the right level of quality, making sure data compliance rules are followed.
Data is growth is a big concern for companies who collect vast amounts of data. Storage costs and security are at least two concerns. A Data Engineer will design and implement a storage architecture that provides fast access to data at the least cost that is secure.
As well as the provisioning of data, data engineers are often responsible for data modeling. So what is data modeling?
Data modeling is the structuring of the acquired raw data into meaningful business-relevant shapes so that it can be easily consumed by analytical applications. A data model represents a consistent view of business data and is built to serve the unknown requirements of the business in the future. A data model is fueled by the data pipelines that have been built by the data engineer.
In summary, a Data Engineer prepares data for consumption, so they need to provision data then model it into shape ready for consumption.
Sometimes, the task of data modeling is shared with the data analyst who works closely with the business to answer business questions. A Data Analyst and a Data Engineer work closely together to ensure a complete flow from data generation to analytics.
So now you understand the role of the Data Engineer, how does SAP help you develop skills in that role? And how do you prove to future employers that you have developed those skills?
SAP have you covered on both counts.
SAP recently launched the new role-based certification Data Engineer - SAP HANA. This certification proves you have developed skills in data provisioning and data modeling, using the SAP HANA platform.
To prepare for certification, SAP Learning provides you with two free-of-charge, self-paced courses:
Provisioning Data to SAP HANA and Developing Data Models with SAP HANA
So, if data-plumbing appeals to you, jump in and tap into the growing demand for this skill set.
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