Tile Shop

Eric Pawlowski serves as the Director of Infrastructure and Cyber Security at The Tile Shop. He leads cloud modernization and digital transformation projects, overseeing secure migrations to Microsoft Azure. His efforts focus on automation, operational efficiency, and implementing advanced security practices, helping the company embrace innovation and resilience in its IT landscape.

Data, if you are a retailer, you probably have more data than you know what to do with. We have it from many sources, including Sales data, Inventory data, store traffic data, search data from Google, Point of Sale data, as well as a plethora of data about our customers behavior from our individual websites. Couple that with industry trend data, and there is more than data that we most likely can consume. These data sets most likely live on a variety of different platforms and have several varying sources. Wouldn’t it be nice to have all this data aggregated into one place where you can make the best use of it all? I think that is a goal out there in the retail world, and many would love to put that data to use to drive customers into their establishments, drive sales, and revenues.

The data that each retailer has should be highly valued and put to the best possible use. If you were aware of high inventory levels of items, or items that have been on the shelf for extended periods of time, it might make sense to put them on clearance. If you knew the latest trends before they hit your city, you can preorder the hottest items and be the first to sell them. If you were able to track your customers’ movements throughout your retail space, you could strategically place items as your customers move about your stores.

 ​At the beginning of the AI revolution a few years ago, it was hard to see how to monetize AI, but that picture is becoming very clear. Those that embrace it, and put it to work from them, will most likely succeed at a high rate 

How do we make this possible? There are several tech companies that specialize in putting all the data together for you, in proprietary applications and databases, and for major fees, of course. Major ERP systems will give you insights into the data that lives on their platforms, but that will leave out several other sources. The answer has been around for a while, and that is to aggregate into a data lake. The problem is the data comes in all different formats, and it is hard to get into one data lake. I had been introduced to the concept of fabric and data lake recently, and I was fortunate enough to present at a rather large ERP user conference with the product owner of one such tool. The idea of extracting data from proprietary platforms, using simple extraction tools, and SQL tables was what many organizations have been looking for. No longer would I be held hostage by our transactional ERP platform, using their expensive tools to get my data. This could be used for many other platforms as well, most of which are already available in the many different marketplaces of our cloud providers. Soon extraction tools and programs will exist for every database, ERP system, web platform, etc. available. They will be ready to consume in the same manner we consume all of our cloud applications and tools.

Now once you have all your data in your data lake, it is for you to put it to work. This is the brilliance of this is now you can use tools that are mainstream, that we most likely have been using for years. Tools like Excel, SQL, PowerBI, tools that don’t need specialized training for, or six figure statements of work from data consulting vendors. You can all take the raw data, and move it through the different medallion stages (bronze, silver, gold), so that you can report on all of your data, having one consistent set of data, showing all of the relationships that exist between each varying set of data. This is highly valuable for organization-wide reporting and predictive analytics. Predictive analysis being the key here, to drive current and future business decisions. Allowing you to see trends more easily, and to find opportunities sooner than you have before.

The side effect of having your data in a data lake is now it is in a format that Artificial Intelligence can be applied to it. Generative AI to help create marketing campaigns, predictive intelligence to help drive critical business decisions quicker than ever before, and eventually Agentic AI to make your business respond quickly to your customers, faster than ever before, helping those customers with their questions and needs instantaneously. We all know that AI is coming, and that eventually we will need to embrace it, or we will be left behind. At the beginning of the AI revolution a few years ago, it was hard to see how to monetize AI, but that picture is becoming very clear. Those that embrace it, and put it to work from them, will most likely succeed at a high rate. There are many steps to reach this point, but the first is corralling all of your data and putting it in a format that not only allows you to get the reporting you need to make critical business decisions, but also to take advantage of all the wonderful AI tools that will be at your fingertips for many years to come.