With greater automation and more robust cloud services, today’s data professionals are seeing their roles elevated, working more closely with their businesses to deliver data-driven capabilities. At the same time, they, too, are feeling the effects of “The Great Resignation,” reporting higher-than-usual turnover and increased pressure on overworked staffs.
These are among the takeaways of a recent survey of 213 data professionals, conducted by Unisphere Research, a division of Information Today, Inc., in partnership with Quest. The survey found that data management roles continue to shift toward higher-level tasks and shift away from rote, mundane activities. There is also a more intense emphasis on security. At the same time, automation and collaboration initiatives, such as DevOps and DataOps, are still just getting off the ground.
Business leaders are looking to database managers or professionals to guide their sought-after evolution to data-driven enterprises. As enterprises shift their database operations to cloud providers, as well as automate low-level tasks, these professionals are seeing their roles elevated to either work more closely with the business or focus on next-generation analytics.
Rate how the scope of your job has evolved over the past 3 years.
I SPEND MORE TIME ON:
- Data security
- Data analytics
- Maintaining data quality/consistency
- Identifying/approving cloud-based resources
- Consulting with line of business teams
I SPEND LESS TIME ON:
Provisioning hardware/software
Assuring uptime/performance
Identifying/approving cloud-based resources
The leading areas in which data professionals are focusing their skills include the following:
Security: Essential to data-driven enterprises, data security has seen more of a shift, with 67% spending more of their time here than anywhere else.
Analytics: A data-driven organization is built on analytics, from business intelligence to AI. Accordingly, 60% of respondents report spending more time in this area. Another 60% are focusing on data quality, the bedrock of data-driven organizations.
Cloud: With cloud being front and center for many organizations, 57% of respondents say they have shifted their responsibilities in this direction.
Business engagement: Significantly, 56% of data managers and professionals report spending more time consulting with the business.
Areas seeing reduced emphasis in data professionals’ jobs involve the provisioning of hardware or software, and ensuring uptime and performance.
Data professions have not been immune to the “Great Resignation,” the survey also found. A majority reported unusually elevated levels of attrition within their ranks, and noted that turnover has been acute among data staffs at enterprises over the past year. In addition, 51% said turnover among data management teams (including DBAs, data engineers and data architects) has been “above the usual average.” More than one in five, 21%, reported that turnover has been “troublesome” or “high.”
What has been the rate of turnover among your data management teams (including DBAs, data engineers, data architects) over the past year?
High, more than half of staff has left 5%
Troublesome, many staff members have left 16%
Above the usual average 30%
About average or relatively unchanged 24%
Below average, more staff members sticking around 19%
Don’t know/not sure 6%
Will DevOps and other methodologies, including DataOps or MLOps, help relieve critical skills requirements with greater collaboration and automation? A majority of enterprises do not yet have these processes in place, though interest is running high.
While DevOps is a popular methodology intended to increase both collaboration between teams and automation of software delivery, it is still on the drawing boards of many enterprises. About 42% of respondents currently actively engage DevOps, while 37% say this approach is still under consideration.
There are tangible benefits being seen as a result of DevOps efforts. These include greater operations productivity, followed by faster delivery time to market.
Other “Ops”—DataOps, MLOps, and AIOps—also focus on more efficient delivery of data to their destinations, via automated approaches and greater collaboration. Most enterprises are just starting to explore the efficacy of these additional methodologies which are intended to improve the delivery of data and software to their users, the survey found. Slightly more than 25% of enterprises have engaged other forms of Ops methodologies to enhance data-driven functions. A majority working with these methodologies report faster delivery or time to market, along with greater operations productivity. The occurrence of fewer errors/software issues was also seen as a tangible benefit by a majority of respondents.
The world is changing, and database roles are changing with it. As this survey shows, data professionals—administrators, engineers, and analysts—are seeing their roles elevated, and they are working more closely with the businesses than ever to deliver data-driven capabilities.