From DevOps to DataOps
DataOps can be simply stated as “DevOps for data”. It is a set of practices and technologies that integrate the development and operation of data movement architectures into a continuous process. In a world, which demands consumable data immediately but plagued by constant change and data drift, the traditional approach of designing, deploying and operating data pipelines as siloed activities is expensive and risky. In fact, it is a non-starter. DataOps is a methodology that helps organizations combine access to information for the employees that consume data and those that provide them.
To master DataOps, you are required to overcome the organizational and cultural barriers that separate people from data. First and foremost, you need to bring two key audiences together as one team – Data Operators and Data Consumers. DataOps is able to handle modern complexity and change and offers key improvements over traditional approaches. It characterizes collaborative development and implementation of data movement to speed time to value, reduce expenditure, maximize reuse, enforce best practices and reduce defects.
DataOps for Data-driven Applications
DataOps aids data practitioners to continuously deliver quality data to applications and business processes. The end-users of data, like the data analysts and data scientists, work closely with both data engineers and IT Ops in order to deliver continuous data movement. DataOps provides robustness and flexibility by using an iterative approach to design and operate data movement logic. The key to DataOps lies in leveraging the right solutions for the right tasks. You have to make sure that they are powerful and easy to use for both data operators and consumers.
DataOps is a people and process paradigm. It aims to promote repeatability, productivity, agility and self-service, while achieving continuous data science model deployment. It is not just about managing data science-related work that are created to deliver business value but a combination of all of the data-related elements and also, all of the software to run the operations of the business.
DataOps and Cloud
Enterprises are increasingly, investing in various cloud platforms that respond well to different business requirements. You will continue to witness a proliferation of infrastructures, databases and analytic tools that address different functions. There is a mass data movement to the cloud, taking big steps to consolidate analytics-ready data. Organizations face the challenge of bringing all the information together for proper analysis. DataOps provides more flexibility to move and use the data.
Diving into DataOps – The Benefits you reap!
DataOps offers faster time to value when working with data and identification of problems that could lead to delays or errors, if not rectified. Detection of an error at an earlier stage saves you from a bigger problem as you can fix them easily. Stronger security enables you to keep your data secure in an easier manner. With DataOps, organizations are able to fetch the productive aspects of data science in day-to-day operations. It also, provides a collaborative work environment, wherein every employee of an organization can have real-time metrics and goals.
- Enhanced Data Analytics – This one is considered to be one of the most essential deliverables after integrating DataOps. Multi-faceted analytics methods empower data specialists in collecting, processing, classifying and delivering data. It helps to receive valuable feedback and quickly react to ever-changing market demands.
- Provides Real-time Data Insights and Serves as a Means of Real-time Tracker – DataOps is considered to be the data management methodology. It helps in turning raw data material into valuable information. You experience faster, automated delivery of data.
- DataOps Enables Better Operations and Support – Teams can quickly and effectively respond to new requests. DataOps improves efficiency and overall quality through statistical process control (SPC). It improves collaboration among various teams and provides real-time goals for organizations. It also, shortens the time to fix bugs and defects.
- Reduces “Data Friction” and Possesses Data Problem-Solving Capabilities – DataOps reduces “data friction” by overcoming internal barriers to accessing the right data. It predicts disastrous scenarios in advance using data analytics.
- Faster Processing of Data and Better Data Security – DataOps facilitates the DataOps Approach for Agile-based project management. As various teams are getting collaborated and communicating continuously, processing of data at various process stages is done much quicker. Data security professionals also, find it easy to secure data at each process level.
- Improved Resource Output – Better data storage workflow and data analytics lead to smart decision making. If organizations adhere to the fundamentals of DataOps, seamless communication and transparency between the teams help in the performance of each team member and will lead to better resource output.
The Future – What Lies Ahead!
If there is one trend that is impacting all enterprises today, it’s the increasing emphasis on using data to drive value. While DevOps took care of the software to run the operational side of the house, DataOps applies to the data side. The creation of a successful DataOps strategy is critical to the long-term success of every business which has dependency on data. You definitely, need a new culture and a new approach – one that does for data what DevOps did for infrastructure. The goal should be to improve results by bringing together the data supplier with the data consumer and at the same time getting rid of a static data lifecycle.
Let the DataOps journey begin!
By Nairita Goswami
Marcom Specialist, RapidValue