Machine learning in your database development project
When thinking about machine learning in your database development project, where do the efficiencies lie? How can you use AI and ML to speed up dev time, cut costs and end up with an end product that more closely matches your SOW? We’ll explain in this quick read.
What do we mean by machine learning in database development?
While we have talked about how technologies like AI and machine learning help us create code and finish development projects faster; today we’re focusing on the client side. How can machine learning in database development make your custom database smarter and more efficient? Why should you insist on harnessing these innovations in your next project? According to CCTB, “Machine learning has equipped businesses to make robust models that can [analyse] complex data and offer accurate results in [real-time]. Database development has been [revolutionised] by this Artificial Intelligence (AI) technology that offers affordable data storage and more powerful processing. It also helps build better models and strategies that can have a positive long-term impact on a company. If a business wants to do well in the rapidly transforming market, filled with new techniques and technologies, then it must implement machine learning in databases.”
Benefits of machine learning in your database development project
While the niche benefits of adding machine learning to your database development project could get very granular, the topline headlines are around efficiency, insights and simplification.
Efficiency
When you combine a data scientist with the power of modern computing, you can get cleaner, more streamlined and well-managed data. You’ll have some rigour around how data is collected and handled, plus you’ll need fewer people on board to manipulate it into insights. You’ll also prevent annoying data issues by suggesting survey question formats, cleansing data on input or validating personal info with publicly available sources. The result is a tidy database where you can trust the insights you glean.
Insights
That brings us to the next benefit, advanced insights. AI and ML are very good at picking out patterns within vast data sets. That means you can do more advanced data analytics tasks faster like propensity modelling, lookalike marketing, churn indicators and more. You’ll know how people interact with your business, why and how they feel about it when they do. This allows you to get more detailed with your loyalty marketing, churn reduction and other internal activities.
Simplification
By putting the data where your teams need it, you’ll not only arm them with insights but you’re making the process of actioning them easier. Let’s take email marketing, if your loyalty database responds best to comms sent on a Tuesday evening but your VIP database prefers weekend comms in the morning; you can have those insights streamed right into your email-sending tool so your marketing team is reminded of peak sending times on scheduling. And, when you’re using ML and AI, those insights aren’t static. If it changes, you’ll be able to feed those trends in too.
If you want faster, cleaner and more insight-driven business intelligence, it’s probably time to look at your database. Why not get in touch today? We can help you leverage machine learning in your database development project to gain process efficiencies and cut costs.
