Modern businesses make decisions based on data that’s been carefully collected, extracted, formatted, and analyzed. Data powers competitiveness, brings new products to the marketplace, and improves the customer experience. The use cases are nearly endless, but there’s a catch: Working with all that data is becoming increasingly complex.
In the latest “SolarWinds Query Report,” 69% of tech pro respondents said they’ve experienced increased database management complexity, primarily because of the transition to remote and hybrid work.
Signs point to the distributed workforce as an ongoing reality since 80% of tech pro respondents said their organizations had expanded work-from-home policies during the last year, and 67% of those same organizations plan to keep those policies for the long term, according to a study by 451 Research. Additionally, according to a study by Accenture, 83% of employees say a hybrid work model is the best option.
Further adding to complexity, we’re generating an ever-increasing amount of raw data, and tech pros are struggling to process it. While not all of the information will end up in databases, IDC has predicted that we’ll collect 463 exabytes of data each day by 2025.
Additionally, while companies once deployed only a handful of databases, now tech pros work with more than 300 databases in their organization’s environment, both on-prem and in the cloud. Open source platforms are also on the rise. According to the SolarWinds report, 43% of tech pro respondents are currently running MySQL or MariaDB. Another 18% said they plan to adopt MySQL, MariaDB, or other open source database platforms in the next 3 years.
The Rise of DataOps
To counteract these and other complicating factors, there is rising demand for DataOps. Similar to DevOps, DataOps is more of an organizational process than a set of tools. It combines software development with IT operations—and, when the two disciplines are combined, DataOps can improve software engineering and deployment.
DataOps works by breaking down the artificial divisions between the different data-oriented disciplines so data engineers can collaborate with data analysts and data scientists. DataOps takes a cooperative approach to data management. It focuses on improving access to data and shortening the lifecycle between data acquisition and analysis. As a result, data engineers escape from firefighting mode. They are no longer reacting to a high level of disasters and failures.
With DataOps, tech pros can build a modern data integration system that provides resilience and flexibility at scale. They can work toward having a comprehensive map of all their data movement and data processing jobs. Once this map is in place, engineers can understand precisely what’s going wrong and not affect downstream projects during the repair process.
The benefits of having a DataOps strategy in place are wide-ranging. Tech pros can deliver functional benefits, including increased efficiency and productivity, reduced manual effort, automated data management processes, and faster access to actionable business intelligence and decision making.
As tech pros deliver policy-driven control and configuration, in turn, data users get access to the information they need. But tech pros maintain control; they can limit or manage access and assign privileges to individual users.
There are many advantages, but full implementation of DataOps is often hindered by the usual suspects: lack of training, budget, and buy-in from leadership. Despite these hurdles, DataOps is growing in popularity—and tech pros will need to upskill. We are in a field where we must constantly think about what to do next—our next pivot. The pivots can be slight, but they need to be in the direction of opportunity.
Automate and Monitor
Tech pros must ensure they cover all their bases, especially in the areas of security and compliance (and, where applicable, cost and licensing). The new generation of legal compliance laws will hurt you if your company doesn’t comply. Learning more about cost considerations will allow you to do more with less and gain buy-in from the senior team.
When appropriately implemented, automation and monitoring solutions can improve overall performance and eventually lead to reduced costs. They can help free up your time by allowing you to focus on more proactive database performance management. Monitoring tools can run in the background while you focus on tasks that add value to the business. This can give you the time to upskill and innovate.
Ultimately, database management isn’t going to get any less complex. But if we strive to adopt DataOps and remember the basics, aided by automation and monitoring, we can help to make our working lives as database managers much simpler.