DataOps has become a bit of a buzzword in the tech space, but unless you are already familiar with what it involves, you might not appreciate the advantages it offers in a business context.
Here is a look at the 5 key ways that DataOps can benefit your organization so that you are better prepared to embrace it when the time comes.
Enhanced interdisciplinary collaboration
As outlined in this guide, one of the main aims of DataOps is to streamline the way that data is captured and made accessible to all members of a business. This means that the information you gather is not just applicable to those who are already specialists in this field, but to individuals and teams across every department regardless of their background and experience levels.
In turn, this means that workers can communicate and collaborate more effectively and efficiently on a whole range of projects, while also making sure that data is at the heart of what they achieve together. If it currently feels like teams are pulling in different directions, it could be sensible to embrace DataOps sooner rather than later.
Eliminating human error
A well-implemented DataOps practice should be used to automate many of the commonplace and previously labor-intensive processes which your business uses to collate and analyze data.
This is not just advantageous from a collaboration perspective, but also in terms of improving the consistency of these processes and thus reducing the likelihood that human error will arise to create chaos further down the line.
That is not to say that DataOps is problematic from a staffing perspective; human workers still have a lot to offer and will actually be able to work well in conjunction with automated systems, rather than being rendered redundant by them. It is this symbiotic relationship that further makes DataOps recommendable to modern businesses of various sizes.
Adapting to change
Businesses need to be adaptable and agile if they want to survive, particularly during periods of uncertainty and increased volatility. This needs to be reflected in their data practices, and of course, DataOps is central to ensuring this.
This is not simply about being ready to implement changes on the fly, but more importantly about ensuring that when shifts are suggested, they can be thoroughly tested and put through their paces to determine whether they are worth pursuing.
Ideally, it would be possible for businesses to extract actionable insights from data immediately, rather than having to wait for extensive processing and analysis to get access to this empowering information. DataOps brings organizations closer to achieving this, and by making insights available almost in real-time, delays are dramatically reduced.
Significantly this can also scale effectively as data volumes increase, rather than being overwhelmed by sudden spikes. In industries where every second count, this will clearly be a major selling point.
Ultimately, DataOps is a crucial cog in the broader machine of modern business, giving data scientists and decision-makers the tools they need to pursue the most innovative avenues, rather than being hamstrung by the systems and processes on which they rely.
If anything, the reason that so much innovation is being seen in the commercial sector today is the growing interest in and adoption of DataOps practices.
Today, data is seen as incredibly valuable to businesses in every industry, and yet there are still a lot of organizations that are either not unleashing its true potential, or are missing out on opportunities entirely because it is ignored or underutilized.
DataOps seeks to deliver a multi-pronged strategy to address this. While there are certainly some obstacles to overcome for those that choose to adopt it, including issues relating to a lack of skills in this arena, the long-term benefits are more than enough to justify the investment and effort involved. It is also one of several innovative technologies that businesses should consider essential in the modern era.