The issue of “data silos” is one that I’d be willing to bet almost all modern IT organizations struggle with. Normally, an organization will have a finance department, marketing department, sales department, accounting department, and an HR department (to name a few). In an ideal world, all those departments would speak to one another. Unfortunately, in many cases this isn’t true.

What ends up happening is what we call data silos. This means that data is scattered every which way making it difficult to efficiently and effectively communicate and complete everyday tasks. There are many reasons that data silos exist such as structural problems(an application built specifically for a certain department), political problems(not wanting to share data between departments), or concerns with latency if an organization has data centers all around the country/world. Note that these are just a few examples as there are many more reason why data silos exists.

In many cases, data silos cause wasted resources and inhibit productivity throughout your organization. On top of the frustration, and inefficiencies it causes, storage costs money so housing an excess amount of unneeded data can result in a pretty hefty unnecessary expense. This is an extremely relevant issue that companies need to deal with. The good news is, there's a solution.

In order to mitigate the problem of data silos, AWS makes it easy to create Data Lakes on Amazon S3. A data lake allows you to store unlimited amounts of structured and unstructured data in a centralized repository hopefully resulting in increased efficiency, collaboration and more fluidity throughout your organization. According to AWS, most companies only analyze about 12% of their data. Additionally, many organizations invest money in gaining insights that they already have since their data is siloed, and they do not even know that they have it. By having all your data in a centralized location, it makes organizational communication more effective, saves money, and gives leadership a better idea of what’s going on throughout the entire company.

Building a data lake on Amazon S3 is cost effective, extremely durable, easily scalable, and works seamlessly with analytics and machine learning services.

Is this something that interests you? Want to learn more? Let’s connect to discuss how we can help as we have a ton of experience in this space. Please feel free to send us a note at info@aritex.io and we can find some time to have a conversation.

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