Big data is revolutionizing how companies do business all over the world. By analyzing big data, companies can do some interesting things. Organizations can see how a consumer makes a purchase and advertise sales to them based on what people with similar buying habits have purchased. They can track every action that a consumer makes on their website, predict when that consumer will leave, and design an ad to pop up right at that moment.
Needless to say, companies are scrambling to build data systems capable of storing robust amounts of information. To do this, they need to create reliable data management teams. And by using remote talent platforms like Upwork to engage independent professionals, businesses not only save money but also have worldwide access to people with specialized skills.
To hire the right people for your team, you should have at least a basic understanding of the roles you need to fill. The following will give you a functional understanding of two important roles on your data management team.
While data architects and data engineers see their skill sets overlap in some areas, they fulfill specific roles on a data management team. You must know the difference between the two so that you can hire the right person for each job.
What data architects do
In the same way that a construction architect creates the blueprints for a building, a data architect designs the plans for your data framework. Data architects have to pay attention to the big picture of the network. Because of this, they have to master many different data management skills and must have a complex understanding of a wide array of nonrelational databases.
Nonrelational databases are also known as NoSQL databases. SQL stands for “structured query language” and is the primary programming language used in relational databases. In addition to SQL, a data architect should also have an expert-level understanding of other programming languages, like Python, Java, and PHP.
The most basic type of nonrelational database is a key-value model in which information is stored into keys and values. Data architects should be familiar with these types of databases and with several other nonrelational database types, including column store, document, and graph databases.
The data architect is like the manager of a data project and also needs adept communication skills to share their vision with the other members of their team. They have to be able to interact with data engineers and data scientists so that the team can use the database effectively.
When you’re interviewing data architects, be sure to ask what data tools they have experience with, what programming languages they feel most comfortable with, and what data projects they’ve helped in the past. Remember that a data architect will be the head of your data management team and someone you should feel comfortable giving the reins to.
A thorough understanding of client data needs
A data architect must maintain open communication with a client and have a crystal-clear understanding of a company’s informational needs. The data architect has to know what data has to be collected and how it will be used. With this information, the architect can design an appropriate database plan to meet all of a business’s expectations.
Ensure database functionality
A data architect is responsible for maintaining a database’s functionality. They perform quality tests to make sure the database is still operating efficiently and meeting its required purpose. If it isn’t, the architect sets to work updating the database structure.
Train other team members to use the database effectively
To make sure everyone’s on the same page, the data architect is often tasked with teaching the members of the data team to use the database effectively. It’s up to the architect to answer any questions the team may have about the data framework. Data engineers and data scientists will look to the data architect to quickly solve any problems they come across.
Effective communication on why the model works
Company executives need to know that a database will work for them. As their head point of contact, a data architect must create reports demonstrating how their database will perform and why it’s the right model. That’s why data architects need to possess great communication skills in addition to technical ones.
What data engineers do
If a data architect is responsible for the general framework of a database, the data engineer is responsible for building its infrastructure. Data engineers are like skilled construction workers who put together the inside of a building. In the same way that construction teams are responsible for connecting electrical and plumbing lines, a data engineer must connect data pipelines that carry information.
Data engineers do share many of the same technical skills as data architects, and there was a time when most data architects would do their engineering. However, with the rise of application programming interfaces (APIs), data engineers’ and data architects’ work don’t overlap as much as in the past.
APIs allow data engineers to make queries even though they may not know a specific programming language. For example, an API would allow a data engineer to perform a query in a relational or SQL database without using the SQL.
When interviewing data engineers, you may want to analyze whether the worker can focus and understand complex technical concepts quickly. A data engineer doesn’t necessarily need the creativity or people skills that a data architect does. However, they must have a great operational understanding of how databases work and how they can work within them. One strategy you can use is to design a skills test to ensure they can perform the duties required by the project.
My data for the database
Data engineers take the database framework designed by the architect and build its insides. To do this, they must be able to have a solid understanding of an architect’s model. Engineers mine the necessary data for a database. They then make sure data pipelines are connected so information can be accessed as efficiently as possible.
Create reports based on the data
Engineers work with data analysts and scientists. Data scientists will tell data engineers what type of data they need so that the engineer can create a report. The engineer must create their report so that it’s easy for a scientist to understand and evaluate.
Optimize operational processes
Data engineers are always looking for ways to improve data-gathering tasks. With a keen eye, they comb through their operational processes to see if any jobs can be optimized. They then implement changes if anything can be automated.
Build your data management team with Upwork
Now that big data has greatly expanded organizations’ access to information regarding their consumers, the need to put together quality data management teams has become essential.
To build an effective data management team, you need to understand the distinctions between every role involved. Data architects design database frameworks for data engineers to operate within. Later, data analysts and data scientists use the information provided by data engineers to solve complex business problems.
However, finding the right people for your team can be difficult and time-consuming. Remote talent platforms like Upwork provide an efficient and cost-effective way to choose skilled and independent workers from a huge talent pool. With a quality big data management team, you gain the ability to understand and market to your customers with precision. A big data system can ensure that your business is taking every possible advantage to operate at its peak.
