Five Ways Data Engineers Can Apply AI To Improve Financial Results

As a data engineer in today’s data-driven competitive environment, you should feel good that your hard work is essential and delivers significant business value. But is your business value recognized? And if not, how can you make sure that it is?

Your Value is not Always Recognized

Despite your job security and compensation, like many data engineers, your hard work may go unnoticed or seem undervalued. There are many reasons why this may happen:

• ROIs are only used to justify investment decisions and allocate resources. Few ever measure actual impact after the fact.

• Your data engineering work is developed and implemented with specialized data management tools. Your business colleagues only value business applications, not the tools that enable them.

• In addition, few ever see or measure your ongoing work to optimize, fine-tune, secure, and maintain the data products that are the lifeblood of your digital business.

Everyone deserves a little recognition. And given all that you do as a data engineer, you deserve more credit than most. So what about you? Do you feel valued? Or are you just fairly compensated?

If the latter, read on to see what you can do to change that.

Where Data Engineers Can Add Value

As an engineer, you know the best way to prove anything is to show that it works. The same is true when proving your value.

For data engineers who use AI to optimize warehouse costs and improve query performance, proving your value is relatively easy to do. Here are five ways AI-driven warehouse optimization and query acceleration help:

• Deliver Business Value Sooner:  AI can lessen the time spent on performance optimization, a critical step repeated across design, development, testing, and deployment. This results in a faster overall time-to-solution so your business can realize your solution’s value sooner.  A project such as a new recommendation engine might generate an additional $1 million in revenue per month. If AI helped you accelerate the project by two months, then you can get credit for an additional $2 million in revenue.

• Increase Data Engineering Productivity: AI can assist with performance engineering and cost management efforts, person-hours you can reallocate to other areas.

• Empower Your Business Analysts: If your organization is like most, you and your fellow data engineers have more work than you have time. Addressing this backlog is far easier if you can deploy AI to automatically empower business analysts to solve many of their performance problems instead of relying on your data engineering team. This empowerment reduces distractions, leaving more time for other valuable data engineering work.

• Lower the Cost of Maintaining Existing Data Products: More than 80% of data engineering time often goes to support existing data products. And as these assets age, the data engineers who built them turnover. The data engineers who follow lack the original engineers’ detailed knowledge. AI not only knows and optimizes the as-built data, queries, and models, but it also automatically learns and reacts appropriately to any changes in the future. Hence, performance SLAs remain high both today and tomorrow.

• Reduce Cloud Computing Costs: In today’s cloud-based environments, your organization pays for its computing power and storage by the drink. Poorly performing queries on one hand and unused resources on the other consume extra computing and, therefore, increase costs. As a data engineer, you can use AI to both optimize your queries and fine-tune your warehouse configuration automatically, significantly reducing your organization’s monthly cloud data warehousing bill.

Now is the Time to Show your Financial Impact

As you can see, AI-driven warehouse optimization and query acceleration provide five different ways a data engineer can impact the bottom line. That’s great news for your organization–and better news for you when the time comes for raises, bonuses, and promotions.