Data, which is important in helping organisation getting better insights in making informed decision, finding solution to problems and improve innovation is growing everyday. According to European Commission 2020, it has been estimated that the global amount of data will surpass 180 zettabytes by the year 2025. Additionally, with digital transformation and implementation various new technologies related to internet, the amount of data being generated are increasing rapidly, making the need for organisations to apply a more agile approach in managing those more data crucial than ever. Hence, the adoption of DataOps practice. While DataOps is beneficial in enhancing work efficiency, simplify cloud migration, produces higher quality data and much more, there are many challenges that come along with it. Therefore, how can organisation establish a successful DataOps practice?
At its core, DataOps is an modern approach to data management that focuses on improving coordination between data science and operations, making it a valuable practice in organisation. However, in order to unlock the benefits of DataOps, its implementation should be focused on people, process and technology.
1. People and DataOps
Different stakeholders (IT, analytics and business teams) have different data analytics goals and working cultures. Organisation needs to establish a DataOps mindset into each team to make DataOps practice work. In other words each team need to develop their working culture into a culture of collaboration. Without this mindset, consistency in DataOps practice cannot be achieved thus hindering the success of its implementation.
2. Process and DataOps
When adopting DataOps into organisational practice, it also basically means the need to audit the existing processes as well to standardise them to reduce variability. However, as DataOps involves different processes and technologies, these changes need to be done in small steps to ensure that the ongoing processes will not be disrupted by the new structures.
3. Technologies and DataOps
The rise of new practices brings about the introduction of number of technologies from different companies. Organisation needs to opt for the right tool to ensure successful DataOps practice in long term. Thus the opted technologies should give access to multiple data sources, helps enhance collaboration between teams, support rapid and multiple changes, enable benchmarking (AI, ML, and DL models) offers assistance in managing and deploying data infrastructure, monitoring and testing of data management processes, data governance and so much more.
All in all, establishing a successful DataOps practice cannot be done overnight. Instead, it requires the amalgamation of collaborations among the teams, step by step implementation and the right adoption of technology.
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