Engineers of all types covet automation projects because, well, it’s the epitome of data engineering. Cloud experts, data experts, software engineers, back-end developers – you name it – we love it.
When given the opportunity to explore a database, automate a data pipeline or process, or do a systems overhaul…I’m telling you, our team is eager to contribute. We love it, and you should too.
Our love for data automation projects is almost equivalent to how much organizations need them. Because somewhere in some data swamp their data is just sitting. Leaders might try to overlay a solution to get some coherency and it fails. Or stakeholders pay big money for a holistic enterprise Snowflake implementation which falls flat on its face.
Investment fails. Now they need to automate.
What’s so exciting about data automation
Typically, data automation projects begin with a deep dive into your business where we discover ways to reduce manual data entry. This could mean the automation of a specific process or an entire overhaul of your systems. Then, we think about why patterns exist and what value they can bring to your employees and customers. This often sparks inspiration and leads to other helpful resources, like a new dashboard to make your teams happier and more efficient.
Automation prevents errors and frees people from doing manual, repetitive, time-consuming tasks that consume their day-to-day responsibilities. It gives employees a tool they trust to take care of those processes so they can focus on adding value, thinking outside the box, and reaching their full potential.
Automation also yields creativity. It gives your people more time to focus on innovation and pursuing the outcomes that really matter.
As a data engineer, I love these projects because I love to solve problems. No two businesses are the same, so no two problems are the same. I love collaborating with my team to extract the commonalities and identify and understand the best place to start.
What kind of business problems are we talking about?
An outdoor company whose business picks up around springtime and in the fall may be interested in understanding trends of what people buy during those seasons so that they can have the right amount of inventory at exactly the right time. You know that your data could give you a full picture, but you don’t know where to start. This is where you can tap into a solution that can scale with user traffic.
An insurance company may be interested in extracting insights from the millions of records worth of claims data that they generate. When combined with business intelligence tools, your business could begin to process claims faster and at a lower cost, identify trends impacting claims outcomes, and confirm or complement a claim adjuster’s intuition. Data automation is a requirement for building trustworthy insights.
A small business without any existing data infrastructure may want to prepare for future growth. We might recommend what people call a low code or no code solution. Something out-of-the-box to do most of the work for you. Or something you can add simple code to and manipulate to get the results you’re looking for.
The value of data automation
There’s a solution for everyone. The right solution varies depending on size, resources, and business goals; but the value is consistent across the board…
Save time. Reduce errors. Reduce costs.
Ask me about the engineers at SingleStone and how we’ve helped companies accelerate data-driven decisions and key business insights by structuring, revealing, and displaying vital data. Send me a message, I’d love to hear more about your business and share how our approach to data could help.
And, if you’re curious about what data automation looks like in practice, from discovery to transformation to automation to ongoing governance, subscribe to our newsletter so you don’t miss my next article.