Have you ever thought about data making the most significant difference that a company will breathe in and out to sustain in the massive competitions? Yes, today, the importance of data is no less than oxygen that every company follows for many reasons. Because if you see and analyze data, you get multiple insights on:
- What does the data try to say?
- How can it help you to grow your business?
- And how can you use data to fill the gaps to maximize your ROI?
- It even conveys a lot about your target audience.
- Their interests and what kind of products they like to purchase
- The hidden patterns that you can use time series analysis to get the upcoming trend in the market.
- And much more
And for the smooth run of the organization, each data science team requires a data engineer, data architect other than data scientists and data analysts. As they have dedicated knowledge and programming skills and application development, and deep knowledge of information technology and management, these people fit the best in their roles.
Therefore, in this blog, we will jump directly to what is the difference between a data engineer and a data architect, what roles they handle, their future opportunities, salary insights, and much more.
What is Data Engineering?
The only key that lies in understanding the term 'data engineering' part is 'engineering.' To break it down, let me ask you a question: what do engineers do?
The answer is, 'An engineer gets into the root cause. He designs and builds a concrete solution to that problem.' The same things a data engineer does, he/she in this position designs and builds different pipelines and transforms data into a single format to collect them in a single database. So that when this data reaches data scientists and end-users, it becomes the most usable stuff present there.
Maybe this looks too simple to you but involves a lot of skills. And that's one reason why prominent data engineers are always in tremendous demand in marketing. And to your surprise, the job role for data engineers will leap to 38% in 2019.
How To Become a Data Engineer?
And to become a data engineer, it's better to belong to the computer science stream from B-tech and have good experience with applied mathematics - statistics and probability. And you have good programming skills handling Python and R languages, experience with big data, and working on real-time projects and internships while getting real-world experience scenarios.
What is Data Architecture?
Data architecture is a set of rules, policies, standards, models that govern and define the type of data collected and how they get used, stored, and integrated into an organization and in its database system. In other words, a complete blueprint for designing a successful and valuable database.
We call the person who practices data architecture a data architect. These professionals translate business requirements for databases into technical requirements by defining data principles and standards. They work with various other teams in the organization that include data miners, engineers, analysts, and scientists. These help to add more security to the database.
The goal of a data architect is to deliver relevant data to the people or audience, or customers who need it. And data architects always make sure the data they provide makes sense to the queries. They even align data collection, storage, and distribution policies with the organization's operational and strategic objectives.
How To Become A Data Architect?
There is no particular course dedicated to this position as it is one of the evolving roles in the data science industry. But you can always gain in-depth knowledge by being in the place of data architects, data scientists, and data engineers as the solution focuses on visualizing and conceptualizing the database frameworks.
Difference Between a Data Engineer and a Data Architect?
The comparison between these two has always been tricky since both positions revolve around the data. The prime difference between the both is data engineers build and maintain the database frameworks, while a data architect visualizes and conceptualizes the database frameworks.
The roles above look so simple to hear or take in. The process involved is too complicated when you get into the root level. Let's break them down for your better understanding.
