Data is the invaluable component binding the ‘fourth industrial revolution’. It functions as the gateway for enterprises to modernise and transform.
Alongside this comes the need for data to become a real-time resource, rapidly accessible to users in a self-service format, to be consumed as insights. The fresher the data, the more value it has, making it vital for companies to move away from static stockpiles of data if they are to adjust to drastically changing and dynamic market forces.
With the advantages that data-driven decision-making provides, it is essential to understand how companies can look to integrate it. In order to do this, we need to strip back the technical jargon to facilitate a cultural transition across an organisation.
As a result of this ‘cultural change’, a DataOps driven approach will permeate each aspect of a company’s interactions, from top line strategy to customer service. DataOps is the answer to enabling data agility, while business intelligence is the answer to data accessibility.
But what do we mean by this?
DataOps provides the automated and secure management of data by aligning the people, processes, and technology of a business. This unifies the gap between those demanding data and those providing it, thus the obstacle of ‘data friction’ is bypassed throughout the data lifecycle.
Below are three key steps to bear in mind when looking to unlock the full potential of DataOps.
1: True value emerges from business engagement
The integration of a new data project should not play second fiddle to the availability of a novel tool or platform simply for IT’s technical ease. The advantages such tools provide may address a specific need, yet it fails to reap organisation wide benefits. The functional goals of IT are not unimportant, however a long term perspective on wide benefits needs to be maintained, where the rewards manifest across different facets of an organisation, whether that be in finance, sales or HR.
In order to achieve business engagement, awareness must be generated as to what DataOps brings to the table. It is only by doing so that a company can begin to understand where data directly impacts the working lives of their staff, and therefore begin to build this ‘cultural change’. The input of envisaged assistance or change coming from staff highlights priority use cases, thereby identifying the highest impact challenges within the value chain of an organisation. Staff inclusion, perhaps through voting for important issues or opportunities is a vital gauge of how DataOps is assisting, forging a crucial symbiosis between data and workers.
With this, we’re given a well-represented view of the questions to be answered, their priority and potential impact if solved correctly. With impact comes business justification for funding and true innovation and transformation follows.
2: Start small, then expand
With the priority issues raised, the next step is for companies to start thinking about how best to address them.
Efficiency is key in order to save costs with a fast impact. It is not necessary to invest heavily in infrastructure, nor attempt to ingest every dataset to solve every problem on day one. Building the foundations requires cost effective, small problem targeting. This initiates a trickle-down effect, whereby solutions can be re-used for the second, third or fourth problem.
The minimum viable product looks to lower costs, obtain data sets quickly from production data and is easily transferable. Additionally it must be secure, in order to repeat, test and validate data before visualising it.
DataOps not only addresses security risks through data obfuscation and masking, it also provides data virtualisation capabilities with minimal effort.
3: Feedback, then rework
A business intelligence dashboard powered by obfuscated and validated production data should not be left as it is. DataOps requires ‘socialisation’; the process of validating the changes implemented by utilising staff feedback. The constructive feedback provided generates a feedback loop, a dynamic process in which solutions are tweaked until a perfect resolution is found for customers and staff alike.
Transparency is of the utmost importance; consumers must be informed throughout the development processes. Their input is the ‘real’ test, which should not be replaced by technological or pipeline results or findings. To create a system of constant improvements to an already functioning implementation, organisations should look to utilise feedback registers to store inputs and maintain the dynamism that DataOps provides to processes.
DataOps has the power to bring people and technology together to eliminate data friction as a barrier to innovation.
Get your questions and engagement from the business, start small, reduce your time to market by using market-leading tools and socialise for rapid feedback loops. Your people are the greatest asset available to any data project and should be used as much as possible.
With the above steps in mind, businesses can kickstart their journey towards DataOps.
Benjamin Ross, Delphix
Image source: Shutterstock/BeeBright