Data and engineering software have a lot in common and work together. While there are many careers in these areas that have some similarities, they also have different areas of expertise that make them distinct.
To manage large quantities of information and data at a scale, companies require experts to manage the task of collecting and preparing it for further analysis. These experts are referred to as data engineers. Data engineers employ programming languages to develop systems that source data transform it into data and make it useful to other specialists in data, such as Data scientists and Business Intelligence (BI) developers.
Data engineers take into consideration the way data is stored encrypted, protected, and stored when designing their pipelines. They may also suggest or implement methods to improve reliability, efficiency, and quality. For instance, they could help integrate data from various systems by adding uniform IDs that allow users to seamlessly combine data.
When their ETL is complete Data engineers typically create applications for analytics to help other people leverage the company’s information. This includes the creation of visualizations to show key data such as trends in customer and employee behavior and product performance, among more. They also manage and create data platforms, which employees can access via APIs or web interfaces like dashboards.
To do this, they must be able to operate different storage and databases. They might, for example employ SQL to query relational databases and a program like Python to create more powerful and flexible ETL processes. Or, they could implement an NoSQL database, such as MongoDB with an approach that is more flexible in relation to documents to managing data.