Why one should adopt DataOps?

How technology can create opportunities for everyone, DataOps is a powerful attribute to justify this techno era which is striving to bring about a difference across all enterprises and organizations.
What is DataOps?
As we all know, data is the backbone in all the companies, irrespective of size and industry, across the globe. It is that fuel which keeps these organizations functioning and helps in carrying out everyday operations. To accommodate the thriving needs for data in the current enterprise world, a new practice has emerged – DataOps. DataOps is an agile practice which fuses data and operations’ team within the company to pipeline all the activities surrounding data. This practice brings together the existing DevOps team along with data engineers & data scientists to support all data-driven companies. DataOps can provide the organization with instantaneous statistics and allow all teams to collectively work towards a common goal.
How DataOps came into the picture?
The concept of DevOps, of collaborating development and operations, gave birth to DataOps which works in a similar manner. With the ability to collaborate, DataOps streamlines all the intertwined activities in the system by connecting the teams such as data engineers, data analysts and data scientists, responsible for handling data with the rest of the organization. This helps to create a collaborative work environment to have day-to-day based real-time metrics and assistance in achieving the collective goal.
What benefits can DataOps give to the organizations?
DataOps comes with numerous advantages:

• Generates real-time data insights
• Ameliorates collaboration among stakeholder teams in the organization
• Qualifies teams to respond to new requests quickly and effectively
• Fosters better operations and support
• Provides real-time goals and its analysis for organizations
• Predicts erroneous scenarios in advance to avoid such situations
• Boosts efficiency and quality in the overall system through Statistical Process Control (SPC)
• Ensures fast rectification of bugs
• Helps the organizations to make progress exponentially

What are the Pre-requisites to adapt DataOps successfully?
While most companies today are pegging away to pull off their goals, but they are being found deficient in getting accurate, detailed and compiled information about their services, methods, processes, products, employee records, customers and potential market. The following are some basic pre-requisites:

• The company should have a common global data view which expounds the data journey in the organization.
• The work must be structurally allotted to teams capable of doing a task (as DataOps fosters systematic team collaboration)
• There should be decentralization of data within enterprises to encourage self-service model for data solutions and services and better collaboration & productivity

How DataOps adds value to the enterprises?
DataOps benefits all the companies and organizations irrespective whether they are data-centric or not. The reason being its agile methodology which is predominantly meant for developing and deploying data-intensive applications & solutions and serves as the best means of providing real-time tracking of the enterprise.

• DataOps aligns data management objectives in application development, support and other day-to-day operations.
• DataOps help enterprises to cope up with the slow data operations and alleviate the risk of data silos.

By incorporating DataOps in enterprises, companies will certainly have enriched analytics with accurate insights and will progress towards seeing a positive return on investment. Thus, in a true sense, DataOps is certainly going to be the next big thing for the data-centric businesses.
To know more about DataOps, feel free to reach out to us.
Reference links:
https://medium.com/data-ops/forward-thinking-companies-are-begging-to-adopt-dataops-732d10b19fe9
http://techgenix.com/dataops/
https://tdwi.org/articles/2019/02/12/ba-all-adopting-agility-for-dataops.aspx
 
 

• DataOps
• DevOps
• Digital Transformation