What is DataOps and Why Do Businesses Need It?
Gathering data is essential for businesses across industries. Figuring out how to analyze and use that data is becoming more challenging as companies become increasingly inundated with data.
This is where DataOps can help.
The term DataOps is short for data operations. This emerging field combines the roles of data engineers, data scientists, and DevOps teams to provide necessary processes and tools that data-driven companies can use to make decisions based on the customer data they collect.
Data and analytics teams use the automated, agile, and process-driven methodology of DataOps to improve and speed up their data analytics cycle time. The goal of using DataOps is to streamline an application’s design and development through data and data analytics.
Companies use DataOps to improve how their data is managed, then find ways to implement the improvements in ways that meet the business’s goals and objectives.
DevOps vs. DataOps
Both DataOps and DevOps are based on an Agile framework and have some similarities in how they work. They each rely on engaging with end-users early to address issues and make changes to improve the user’s experience. However, they are not the same thing.
Companies use DevOps to manage and maintain their software. DevOps requires software developers and IT professionals to coordinate in order to create and maintain software and software-related products.
Companies use DataOps to manage and maintain the data they collect from their users and customers. DataOps requires coordination from everyone in an organization who works with data to improve how that data is used to further the company’s objectives.
In addition to being used for data instead of software, the main difference between DataOps and DevOps is that DataOps requires cross-departmental coordination within the entire organization. There is not just one team responsible, as is often the case with DevOps. Further, because data is always changing and evolving, DataOps requires constant attention and testing.
Who Can Benefit from DataOps?
Implementing DataOps is not a decision to be made lightly. Implementation will require several structural and organizational changes. However, many organizations recognize that the benefits of DataOps far outweigh the slight inconveniences and challenges that come from making such a structural change.
Here are a few signs that your organization could benefit from DataOps implementation:
The organization is riddled with data silos
Data analysts are writing duplicate reports and jobs
The data team can’t keep up with all the minor tickets that are coming in
Business users are frustrated with how long it takes them to get their data
Business users have stopped trusting the data they do get because it has many errors
It takes months for data scientists to get the data and resources they need to do their job
If any of the above points sound familiar, it might be time to think about implementing DevOps into your organization.
Although DataOps is an emerging field, it is quickly taking off and becoming a necessity within data-driven organizations that already have, or are seeking to hire, a data engineer and data scientist. There are many DataOps solutions on the market, including open-source DataOps services that can help businesses in all industries improve the speed, accuracy, and analytics of their data.