How DataOps Can Accelerate Your Data Journey
The potential for data to transform organizations is huge, but the ability to achieve this potential is continually threatened by the inherent vastness of data and the ever-increasing needs of data consumers. Many organizations are trying unsuccessfully to address the need to better organize and streamline data through technology alone. This approach silos the data issue within IT, cutting off large portions of the company that could help create and drive an integrated strategy. There is a real need for a new methodology that brings modern technology, new processes and the teams working and using data together, and that’s DataOps.
Is Business Transforming At The Speed Of Data?
In November 2018 IDC stated, “By 2020, 80% of enterprises will create data management and monetization capabilities, thus enhancing enterprise functions, strengthening competitiveness and creating new sources of revenue.”
This sounds great in theory, but in practice, there are many operational hurdles to reaching this nirvana. Some are entrenched processes, some are cultural in nature and some are technology gaps. And while there are three main areas where we see data projects stall — talent, process and technology — thankfully with a strong DataOps strategy, organizations can create proper alignment and solutions across all three.
DataOps brings together IT data owners, database administrators, data engineers and data consumers across the business in a cross-functional workstream to interact on needs, dependencies, limits and goals. Bringing these worlds together and breaking down silos streamlines the common push-pull cycle of one-off requests, denials and workarounds — and gets all invested parties on the same page.
Let’s take a look at the three different areas that contribute to DataOps:
It’s ironic that companies looking into DataOps in an effort to streamline data volumes and workloads first need to get more data. It’s crucial for the DataOps team to execute a representative survey on their talent pool and how employees truly leverage data in their roles. This prioritizes where data is most useful and identifies the gaps where data could be immediately valuable. This helps the DataOps team design a process for data destinations and identify “missing” data that could be created or acquired through a third-party source or partners. This phase must also include an initial company-wide data literacy assessment. This is important, as it will allow DataOps teams to benchmark where there are additional training needs and program investments that will help in the next two areas.
Enabling more of the organization with data sounds so logical that people may wonder why it hasn’t happened yet. But IT has rightly resisted doing so in the past based on a variety of real-world concerns, like privacy and IP, security, regulations and governance. Through DataOps, IT can clearly explain why current limits are in place, all while gathering valuable input and context, which can lead to agreements with various departments on how to evolve their access to and daily use of data. Having at least one executive involved in your DataOps initiative ensures the group knows the organization takes this new effort seriously. Additionally, that top-down support will empower the DataOps team to move the organization in the right direction. This alignment helps IT become more comfortable in rolling out processes to democratize data, which should certainly include training. An essential success factor here is having the ability to use common language around data. This is where having an established data literacy initiative or kicking off an initial program for those in DataOps will ensure those involved have the necessary training to understand and leverage data effectively.
This is the most direct way a DataOps initiative will help your organization, and it is mainly driven by IT.
