Data engineers help you make sense of the data your company collects.
One of the most valuable assets a company has today is data. It helps companies learn more about their customers, thus helping them create and market products and services their users will like. Given that, companies are using a wide variety of techniques, such as surveys and email tracking (i.e. tracking sent emails to inform business decisions), to collect customer data.
But all these techniques leave businesses with so much data that they need skilled experts to make sense of it. This is where data engineers come in. Data engineering involves the sourcing, transforming and management of data from various data systems. If the prospect of leveraging customer data for the growth of your business excites you, here is a deeper look at data engineering, the role of data engineers in a company and the importance of hiring them in your startup.
The basics of data engineering
We have previously discussed how big data (large quantities of data) can be classified into structured, unstructured and semi-structured data. Data engineers take all this data and make it easily accessible so that it can be used to predict the future behavior of customers, both in the short and long term. Once the data is understandable, it is passed on to data scientists.
Note that data engineers and data scientists have different skill sets and perform different roles in an organization. Data engineers have a technical background, like computer engineering, and are focused on simplifying data for data scientists. Data scientists, on the other hand, are more business-oriented and are focused on using this simplified data to meet the goals of the company. When you first get your startup up and running, you probably wouldn’t have enough data for a data scientist to go through, and thus, businesses are advised to first hire data engineers and get the proper data channels set up before investing further in big data analysis.
The roles taken on by data engineers
Based on the size of an organization, here are the three different roles that data engineers can take up —
1. Generalist data engineers
Typically working with small teams, generalists tend to have a wide variety of data processing skills without the in-depth knowledge of data systems. This role is a middle point between the skills of data scientists and data engineers. So, a person in this role would not only simplify data but would also be actively involved in analyzing said data as well.
2. Pipeline-centric data engineers
Such data engineers typically get hired by middle-sized companies where the data needs are much more complex than what is typically handled by a generalist. Pipeline-centric data engineers work in collaboration with data scientists. Data engineers performing such roles need to have a greater understanding of data systems and computer science.
3. Database-centric data engineers
Hired mostly by larger companies, database-centric data engineers need to work with data across multiple databases and develop table schema (the connection between different tables of data inside the database).
So, let’s say you start a fashion e-commerce website. When you first begin receiving orders, you will need a generalist to help you record the number of purchases made and use them to forecast what future sales will look like. As you grow into a middle-sized e-commerce company and begin housing more brands on your website, your needs would grow. You would then require a pipeline-centric data engineer to simplify the massive amount of data coming in from the purchases made across the different brands. This simplified data would be used by data scientists to help predict when and where most sales are happening and how to target this niche of customers further.
Finally, if the business grows even more and becomes an international e-commerce website like Amazon or Ali Express, you would have to hire database-centric engineers. These data engineers would write code to ease the movement of data across different databases.
Importance of hiring data engineers
According to a study conducted by the software company Domo Inc, as of 2020, 2.5 quintillion bytes of data is created on a daily basis. What makes this massive quantity of data seem even more unmanageable is the threat of data breaches. Experts at the University of Maryland say that a cybersecurity attack happens once every 39 seconds. Such attacks can cost businesses US$4.35 million on average as well as tarnish their reputation.
Given the rise in technological developments, the amount of data generated would only grow bigger and bigger over time. Thus, to use any of the data generated by your company in a safe and constructive manner you need the skills and expertise of data engineers.
Also read:
- What Is Big Data? How Is It Used in Marketing?
- What is Data Harvesting And How to Prevent It
- Top Five Data Breaches By Tech Giants In Recent Years
Header image courtesy of Freepik
