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Creating a Successful DataOps
Framework for Your Business
The current pandemic has pointed out that businesses must be prepared to face unexpected
challenges. It has also made it very evident that businesses must be equipped with the best
technologies and ideas that can help them sustain themselves during these challenging times.
As data is universally important and has a major role in decision-making and other business
operations, a strong data-driven culture has become extremely important for business
organisations.
This calls for a successful and efficient DataOps framework. Let us explore more about this
emerging methodology.
DataOps: What Is It?
The concept is quite similar to DevOps, which brings together Development and Operational
processes. Similarly, DataOps refers to improved data management by bringing together
different teams like data scientists, DevOps practitioners as well as data engineers.
The fact that data architecture is quite complex cannot be ignored. An enormous volume of data
needs to be collected, analysed, organised, aggregated, and even cleaned repeatedly. It
becomes quite challenging and consumes a good deal of time as well as effort.
As a result, a structured process can be drafted that helps in better decision-making. Also, data
compliance can be ensured, and data analytics challenges can be resolved.
A structured framework and collaboration between teams can help standardise these
processes, which will also improve productivity.
A Successful DataOps Framework
The three main components of data pipelines are :
● Data Ingestion
● Data Engineering
● Data Analytics
With DataOps, these components can be integrated for efficient processing. As a result,
complex and hybrid data architectures can also be managed efficiently through a unified model.
DataOps for Business
For successful data analysis, data operations, processing and data compliance, it is important
for businesses to invest in technology and processes. Some of the important components that
can help in creating a successful framework for DataOps are:
Technology and Process
● For effective technology architecture, Cloud First is vital. It helps in reducing the project
duration and can also scale out easily.
● Another important approach is introducing automation in the data infrastructure. Manual
approaches are prone to errors and are not efficient. In the current times, automated
procedures are quite important and also economical.
It is a better idea to combine different platforms and explore the latest technologies. With the
rapid technology change, optimising the data framework and tools should be implemented to
create the best solutions.
● A clear data lineage has its own merits. It helps in debugging issues easily. So,
incorporating this concept is beneficial too. Besides, there must be provision for
bi-directional data flow. It can help in collecting valuable feedback from the customers,
and data issues can be resolved as well.
● Technology infrastructure also has an important role to play in the DataOps framework.
Storage and computing, data management and utilisation, all these operations need
platforms. Data security requirements must also be accommodated.
Also Read: Best Practices For A Successful Software Release Management
3 Proven Benefits Of the DataOps
Framework
End-to-end efficient data management
Agile software to curate, store, govern, manage, assign, and provision data ensure connected
and optimised data flow at each stage of the data lifecycle—throughout the supply chain.
Secure and compliant data
Automation, customisable data quality, masking, tokenisation, etc., keeps your data protected
and compliance-verified at every step of its journey.
Lower data costs
Offer stakeholders self-service access, thus making data easily accessible and enabling easy
selection and data provisioning to any destination. Such streamlined workflows ensure IT
dependency reduction, rapid analytic outcomes, and data costs reduction.
Organisation
● The organisational structure needs to be designed systematically with well-defined roles
and responsibilities for each team.
● Offering specialised training to upskill the employees is very important. The key idea is to
introduce flexibility and adaptability and accommodate changes as per the business
requirements.
Conclusion
Businesses cannot continue with the traditional process of data mastering. These are
exhaustive and time-consuming. Besides, the scope is also limited.
The current market requirements call for agile data mastering that helps deliver values quickly
and easily. This is also a collaborative approach as it is technology-driven. So a well-planned
DataOps framework relies on technology and a flexible organisational structure.
Contact Us
Company Name: Enov8
Address: Level 2, 389 George St, Sydney 2000 NSW Australia
Phone(s) : +61 2 8916 6391
Fax : +61 2 9437 4214
Email id: enquiries@enov8.com
Website: https://www.enov8.com/

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Creating a Successful DataOps Framework for Your Business.pdf

  • 1. Creating a Successful DataOps Framework for Your Business The current pandemic has pointed out that businesses must be prepared to face unexpected challenges. It has also made it very evident that businesses must be equipped with the best technologies and ideas that can help them sustain themselves during these challenging times. As data is universally important and has a major role in decision-making and other business operations, a strong data-driven culture has become extremely important for business organisations. This calls for a successful and efficient DataOps framework. Let us explore more about this emerging methodology. DataOps: What Is It? The concept is quite similar to DevOps, which brings together Development and Operational processes. Similarly, DataOps refers to improved data management by bringing together different teams like data scientists, DevOps practitioners as well as data engineers. The fact that data architecture is quite complex cannot be ignored. An enormous volume of data needs to be collected, analysed, organised, aggregated, and even cleaned repeatedly. It becomes quite challenging and consumes a good deal of time as well as effort.
  • 2. As a result, a structured process can be drafted that helps in better decision-making. Also, data compliance can be ensured, and data analytics challenges can be resolved. A structured framework and collaboration between teams can help standardise these processes, which will also improve productivity. A Successful DataOps Framework The three main components of data pipelines are : ● Data Ingestion ● Data Engineering ● Data Analytics With DataOps, these components can be integrated for efficient processing. As a result, complex and hybrid data architectures can also be managed efficiently through a unified model. DataOps for Business For successful data analysis, data operations, processing and data compliance, it is important for businesses to invest in technology and processes. Some of the important components that can help in creating a successful framework for DataOps are: Technology and Process ● For effective technology architecture, Cloud First is vital. It helps in reducing the project duration and can also scale out easily. ● Another important approach is introducing automation in the data infrastructure. Manual approaches are prone to errors and are not efficient. In the current times, automated procedures are quite important and also economical. It is a better idea to combine different platforms and explore the latest technologies. With the rapid technology change, optimising the data framework and tools should be implemented to create the best solutions. ● A clear data lineage has its own merits. It helps in debugging issues easily. So, incorporating this concept is beneficial too. Besides, there must be provision for bi-directional data flow. It can help in collecting valuable feedback from the customers, and data issues can be resolved as well. ● Technology infrastructure also has an important role to play in the DataOps framework. Storage and computing, data management and utilisation, all these operations need platforms. Data security requirements must also be accommodated.
  • 3. Also Read: Best Practices For A Successful Software Release Management 3 Proven Benefits Of the DataOps Framework End-to-end efficient data management Agile software to curate, store, govern, manage, assign, and provision data ensure connected and optimised data flow at each stage of the data lifecycle—throughout the supply chain. Secure and compliant data Automation, customisable data quality, masking, tokenisation, etc., keeps your data protected and compliance-verified at every step of its journey. Lower data costs Offer stakeholders self-service access, thus making data easily accessible and enabling easy selection and data provisioning to any destination. Such streamlined workflows ensure IT dependency reduction, rapid analytic outcomes, and data costs reduction. Organisation ● The organisational structure needs to be designed systematically with well-defined roles and responsibilities for each team. ● Offering specialised training to upskill the employees is very important. The key idea is to introduce flexibility and adaptability and accommodate changes as per the business requirements. Conclusion Businesses cannot continue with the traditional process of data mastering. These are exhaustive and time-consuming. Besides, the scope is also limited. The current market requirements call for agile data mastering that helps deliver values quickly and easily. This is also a collaborative approach as it is technology-driven. So a well-planned DataOps framework relies on technology and a flexible organisational structure.
  • 4. Contact Us Company Name: Enov8 Address: Level 2, 389 George St, Sydney 2000 NSW Australia Phone(s) : +61 2 8916 6391 Fax : +61 2 9437 4214 Email id: enquiries@enov8.com Website: https://www.enov8.com/