Company-generated data is growing exponentially, and businesses are increasingly trying to understand how DataOps processes can be applied to manage and derive value from this data and ingrain it into company culture. Gartner defines DataOps as a collaborative data management practice focused on improving the communication, integration and automation of data flows between data managers and data consumers across an organisation.
There is still a long way to go until all businesses are aware of the best practices for improving data quality and data management, and significant changes in culture must take place within organisations for DataOps to succeed. The cultural shift that needs to be made is embracing the idea that DataOps is a continuous process and as such acts as a catalyst for organisational transformation by promoting agility and embracing change.
As it stands, many businesses need to change how people collaborate around data and how data is utilised within an organisation. The creation of data pipelines and products must become a collaborative endeavour with a united understanding of the value proposition the data brings. Below, we consider the five steps C-suite leaders can take to foment such a cultural transformation and foster success.
1. Embrace that DataOps as a continuous process
For DataOps to be effective, the organisation’s leadership must completely dismantle traditional and established areas of data analytics, and entirely restructure the process. They must create a culture whereby everyone buys into the use of data to make business decisions, and the organisational structure must promote a data-driven culture of continuous change and the ability to manage this change.
The number one impediment to effective data management across organisations is the lack of speed to implement, change and distribute data across the organisation. This lack of speed has led to teams and departments going it alone to make up for this.
Businesses tend to view technology teams as constructing a house that we can walk away from, and when people move in, the technology teams have no further role to play. However, DataOps is like a river; customers send questions down this river, and teams need to constantly flow with this river. Put simply, DataOps is a continuous process, not something that can be built and walked away from. The shift in culture that needs to be made involves embracing the fact that DataOps is a continuous process and as such, is not a one hit wonder.
The data journey: It’s only the beginning for digital transformation — Big Data LDN
2. Back up decisions using data
Organisations must move towards a mindset in which data is placed at the heart of decision-making. It should be at the forefront of the mind for all employees, from those who use data in their jobs, to those who analyse data, and those who are charged with the management and maintenance of data and the platforms that process the data.
It is also important to ensure your company empowers everyone to take the initiative and offer their opinions freely, backed up by the data. This will mean that the best ideas naturally gravitate to the top, enabling you to remain competitive even in the most fast-moving markets. By necessity, management will naturally relinquish some oversight control in favour of building more decision-making processes based on data throughout the business.
3. Remove Data silos
All of the data in the world will be of no use if that data is inaccessible to the people who need it to make good business decisions. Companies must create a culture whereby they remove organisational boundaries that have crystalised over time, and have resulted in data silos that prevent data insights from flowing freely. Companies must move from hoarding data to sharing data, and this requires governance, access control, and security. Teams who work from numerous different organisational structures need to coordinate.
You must also ensure employees have access to the most accurate data at any given moment. Teams must be able to see and understand the data that affects their work, so they can access the bigger picture.
How to break down team and department silos for digital transformation
4. Be bold and be brave
Implementing effective DataOps is also about having a braver mindset embedded in your company culture. There are commonly two broad poles of organisation types. Firstly, there are those (usually larger) businesses that are afraid of making changes for fear of significantly impacting the current state of play. These businesses don’t want to make a mistake, and they also don’t want to make a lot of changes. Consequently, they tend to put in place a lot of rules and regulations, making change a slow process.
At the other polar opposite are smaller organisations that often have individuals who try to do everything themselves, work fast and cut corners. These businesses often end up with a big mess that they regret. However, there are methods, software and processes that can help them grow fast and not risk making mistakes; companies can thrive and not live in fear of errors.
Many businesses fear the risk that comes from making changes, but there is no other way to move forward to a more productive and effective future. Any failure encountered along the way should instead be viewed as an opportunity for improvement. Businesses need to move towards a bolder mindset and a new way of doing things by shifting away from past routine and legacy processes.
Fortunately, DataOps can help organisations break out of the cycle of caution and heroism that is impacting their ability to be successful. DataOps provides the structure and methodology to enable organisations to confidently and simultaneously move fast and reduce errors.
5. Invest in the right data tools and advice
If data cannot be applied to business problems, it is not providing enough use. Investing in data process tools is therefore key to ensure your teams can access, share and analyse data. In general, DataOps is not a single tool you can purchase and forget. Fundamentally, any DataOps solution should improve your ability to collaborate, as well as to orchestrate data pipelines, automate testing and monitoring, and speed new feature deployment. If you have the time and resources, you can implement and manage a DataOps program yourself by using many of the different tools available for orchestration, environment creation, deployment, etc. For speed and agility, you can also invest in an all-in-one DataOps platform.
Make sure you’re investing in suitable training in using these tools. For example, technology platforms exist that can help you orchestrate your multi-environment data pipelines, from data access to value delivery, while the advice of external experts can be helpful when trying to ensure a seamless transition to a successful DataOps culture.
DataOps: getting data right for DevOps
By focusing on the ecosystem for your data — the processes, the teams and the technology — you can foster an effective DataOps culture that maximises data value and promotes harmony between your disparate teams. Above all, embracing the idea of DataOps as a continuous process, and one that all parts of a business — and all staff — must be on board with, will be key to a successful business future.
