Over the past several decades, organizations of all sizes have adopted IT technologies to improve operations and competitiveness. Many companies want to build efficient web applications while managing data effectively. To this end, they’ve looked for better approaches in data analysis, software development, and data management.
DevOps manages software development and delivery. DataOps is an end-to-end approach to deliver data products efficiently and effectively. Both work to solve the need to scale software development and delivery.
DataOps methodology includes SQL queries, machine learning models and insights, data pipelines, and more. While DataOps focuses on the use of data in analytics and the flow of data, DevOps focuses on the software development process and product delivery cycle.
Based on agile frameworks, both are designed to accelerate the software development lifecycle. In short, DevOps focuses on software product development, and DataOps reduces the time from data need to data success.
This blog provides an overview of both and highlights their differences.
As a set of practices and tools, DevOps enables the collaboration of IT operations and development teams throughout the entire software development lifecycle. Using automation, DevOps agile methodologies can integrate operations in a seamless workflow. Automation in DevOps includes the build-test-release cycle with continuous integration and development pipelines.
Benefits of DevOps
- Cost savings
- Improved communication and collaboration
- Reduced disaster recovery times
Elements of DevOps
DevOps relies on better utilization of infrastructure resources. With it, developers manage IT infrastructure using a descriptive model of code binaries.
DevOps has many tools at its disposal to perform repetitive and manual tasks automatically with minimal human intervention.
DevOps enables automation, security, and agile development by using continuous development, testing, and deployment.
DataOps methodology consists of tools, practices, and frameworks that focus on enterprise data management. It standardizes technological and cultural changes. DataOps helps businesses reduce data management costs, improve data quality, and enable faster time-to-market. It makes data collection, analysis, and decision-making efficient and effective.
Benefits of DataOps
- Automates analytics processes and manual data collection
- Isolates production data
- Continuously monitors the data pipeline
- Enables controlled data access
- Centralizes and shares data definitions
- Enhances the reusability of the data stack
Differences between DevOps and DataOps
The main difference between DevOps and DataOps is the delivered products. DevOps engineers develop and deliver software. DataOps focuses on data-based application delivery. They also require different skill sets and teams to be successful.
- Collaboration: DevOps involves engineering and development teams. DataOps involves application developers, business users, and IT operations. With DataOps, data is important; with DevOps, the code is important.
- Quality: While both of them have quality components, DevOps is aimed at creating a quality end product, while DataOps ensures that high-quality data enters the process.
- Cycle Times: DevOps focuses on shorter release cycles. DataOps focuses on building a continuous data pipeline.
- Operations: DevOps runs repeatable and similar cycles. DataOps addresses changing data challenges.
- Test data management: DevOps includes test data management during the implementation process. DataOps starts with analytics and then focuses on unlocking value from multiple data sources.
In today’s highly dynamic tech landscape, it’s vital for businesses to rely on software applications that are efficient, scalable, and secure. For this, they must adopt the right models and methodologies.
Both DataOps and DevOps offer competitive advantages through advanced innovation. InApp has been working on both approaches in our software development process for more than a decade. If you have any questions, please contact us.