Do you save every email, just in case you need something from it one day? Your inbox is essentially a large lake of water and you just need to get to those buried sunglasses, GoPro, and diamond ring you dropped over the years. Data lakes form when massive amounts of data come in and are stored until you have enough data, that you find what you are looking for. Some may think this is a useful security measure, but that’s not always true.

In some cases, it can be difficult to get the data you are looking for among the other unnecessary data. Collecting data from a data lake can be a daunting task and one that is time-consuming and meticulous. When trying to discover valuable data, you can get stuck on unimportant items— completely missing anything valuable.

It’s not always worth diving deep into these data lakes to fish out the most important information, especially when there’s really only enough time to scrape the surface. When the lake is so deep and dense with data, it takes time to filter out the clutter to determine what is useful or what can be disregarded. Most organizations lack observability around the mass amounts of data stored.

There are now solutions like our Classify360 solution that utilizes machine learning to extract the value of the data lake; these automated processes relieves humans of doing this exhausting job. This type of technology allows organizations to easily audit, gather intelligence on, and take action with their data, all in a fraction of the time, reducing storage costs while also achieving compliance.

Ultimately, draining the lake is the end goal. We’re able to remove filtering challenges and focus on tools that remove unnecessary data, allowing us to focus on what’s most important directly at the edge. With the help of AI-enabled filtering, we’re able to ensure that all relevant and actionable data is pulled to the surface, leaving irrelevant data behind, therefore diminishing the lake – and making it easier to find that diamond ring shining through the depths.