Data processing engineers are professionals who can assist organizations with many design, deployment, and maintenance tasks. If you're collecting, storing, or analyzing large chunks of data, engineering is critical to your success. Here are five times to bring in engineers to assist you with data processing issues.

New Design 

There is no better time to get things right than before you've committed to a particular architecture. Data processing engineers can provide guidance regarding the available hardware and software. If you have questions about the relative advantages of bare-metal, cloud, and hybrid deployments, they can explain the options on the market today. Likewise, they can design a robust enough architecture to ensure your setup will function well for years to come.

Optimization

Especially if you haven't tweaked a system for a while, it might not run optimally. This doesn't mean it's going to fail, but you may be overpaying for processing and transfer time just to keep the system afloat. Engineers can assess the current state of the system and devise ways to optimize it. This may include hardware and software upgrades. They might also recommend specific settings to avoid redundancies and heavy loads.

Troubleshooting

Now the data processing system has broken. You probably need help troubleshooting it, especially if you need to get it up and running as quickly as possible. Worse, the folks who originally designed and deployed the system may have moved on. They also may not have left behind the necessary institutional knowledge to fix the system, especially in a full failure.

Fortunately, data processing engineers like complex challenges and think fast. They can assess the architecture, study the operating logs, and propose a solution within a reasonable time.

Coping with High Demand

Companies are increasingly seeing periods of high demand. Especially if you don't want to drop lots of money on additional hardware, you may want to explore alternative solutions. For example, data processing engineers often recommend cloud-based solutions for bursting data to customers. This provides a highly scalable way to cache data without breaking the bank, and you can easily retire the excess resources when demand declines, too.

Exploring Technologies

Many businesses are also rapidly exploring emerging technologies. Data processing supports a host of solutions, including AI and ML tools, IoT devices, and pattern detection. If you need someone to provide a solid knowledge base as your organization plows new fields, you'll probably want at least a few data processing engineers around to advise you.