How to Use Machine Learning and Other Technology to Make the Most of Your Data

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If your company isn’t treating data like an asset, you could be missing out on a major growth opportunity.

That’s according to Swami Sivasubramanian, vice president of Amazon Machine Learning. Sivasubramanian was speaking during a keynote conversation on data and machine learning Wednesday at AWS re:Invent, a conference for business owners and other technical decision-makers hosted by Amazon Web Services in Las Vegas.

Sivasubramanian says there are three things companies can do to make the most of their data. Here’s his advice.

1. Modernize your data infrastructure.

Too many companies still treat their data like it’s the 1990s when they should be implementing a modern data strategy, according to Sivasubramanian. This applies to both storing your data and “putting your data to work,” he says. In many cases, hiring an outside company to manage your database for you can save resources and help ensure your operations run smoothly. Sivasubramanian adds that a cloud-based solution will help ensure that your company’s data–even the most obscure, infrequently used bits–can be easily accessed by your teams that need it.

Applying modern solutions like machine learning to your database can also help you detect problems faster. For example, an application slowdown that might otherwise go undetected for days can be identified and diagnosed quickly with machine learning. It can also provide suggestions for fixing problems with your data, which can be time consuming and costly if you’re still doing so manually.

2. Unify your data.

It’s important to have what Sivasubramanian refers to as a “single source of truth” about your business. Ensuring that your teams are all looking at the same data can help your company make the most of it. Of course, this doesn’t mean every team should have access to every piece of data; different teams can and should have different permissions and levels of access. What’s important is that this data is consistently reported and recorded.

“Opportunities to transform your business with data exist all along the value chain,” says Sivasubramanian. “But creating such a solution requires companies to have a full picture and a single view of their customers and their business.”

3. Find innovative uses for your data.

Applying insights to your data can help you improve existing operations or build entirely new ones. Sivasubramanian points to several AWS customers that have benefited from applying machine learning and analytics to their data. Tyson Foods has used cameras armed with computer vision to identify ways to reduce waste by cutting down on packaging. And Pinterest has used natural language processing to create more accurate search engines that allow employees to find the information they need faster.

“Machine learning is improving customer experiences, creating more efficiencies, and spurring completely new innovations,” says Sivasubramanian. “And having the right data strategy is the key to these innovations.”