The Holy Grail of Data Democratization—And How AI Can Make It Reality 

Data democratization is a persistent dream: The goal of every person in an organization being able to access the data they need when they need it, analyze that data, gain insights, and take appropriate action. Data democratization, if it could be achieved, has the potential to sharply improve organizational performance. However, like the legendary Holy Grail that King Arthur sought in vain, this particular grail is also stubbornly elusive (and hasn’t even generated any good stories or Monty Python movies). 

There are several reasons why data democratization is hard. 

Data Silos—Organizational data is stored in a large variety of different locations, formats, and technologies. Finding data is a scavenger hunt that can easily eat up 1.5-2 hours per day, or the equivalent of one full workday each week.  

Data Literacy—Having data is only the first step. You still have to identify the most relevant data and know what to do with it. Making matters worse, data scientists are not necessarily business experts, and business experts are not necessarily experts at data analysis. That disconnect creates delays and confusion. 

Security—There are real security risks to making data easily available across the organization, from accidental disclosures to data breaches to making it easier for hackers to gain access to the system.  

Resources—Making data easily accessible takes time and money. Many solutions that look good in a Proof of Concept (POC) are complex and expensive to deploy in production, requiring a large upfront investment before you can see if they work at scale.  

Data Democratization with AI 

AI has the potential to enable data democratization, but even with AI it’s not easy.  

Uploading all of your data into an AI or copying it all into a vector database is costly, time-consuming, and a security nightmare. What an AI knows, an AI will disclose. You just have to ask nicely, or better yet, use one AI to design prompts that will convince another AI to tell all.  

On the other hand, it is true that AI can help with the data literacy problem. You just have to be very good at asking the right questions, a skill that often seems to consist of a great deal of patience combined with the magical talents of Merlin the Magician.  

And, of course, it’s often difficult to tell ahead of time if that expensive AI system will scale beyond the POC phase. The more data copying or uploading required, the greater the investment and lock-in that takes place before you know it will work.  

But there is hope.  

SWIRL Harnesses AI for Data Democratization 

SWIRL is a powerful AI framework that finally puts the holy grail of data democratization within reach. SWIRL addresses the key issues that make data democratization hard: 

Data Silos—SWIRL connects to a huge number of data sources, including databases, cloud providers, email, and productivity apps such as Slack, Confluence, Teams, and Zoom. SWIRL is constantly adding more connectors, so it can read your data no matter where that data is located or what format or technology it is in. It doesn’t require large scale data movement or duplication, so your data stays in place (no new silos!). SWIRL ends the data scavenger hunt and gives you back that lost day. 

Data Literacy—SWIRL engages interactively with you, answering questions and making suggestions. While there will always be data analysis problems that require high-level training to resolve, SWIRL dramatically expands the range of problems that can be solved by business domain experts who are not trained data scientists or statisticians. 

Security—SWIRL integrates with your existing security protocols, so no one gets access to data they are not supposed to have. And because data stays in place, there’s no risk of your data being exposed in a vendor data breach. SWIRL brings the AI to the data, not the other way around, making SWIRL an ideal choice when security is critical (including air-gapped systems).   

Resources—SWIRL is easy to set up and easy to use and does not require you to copy data into a vector database or vendor cloud. It also lets you choose which AIs you talk to, whether homegrown or a model approved by your IT department. It’s easy to try SWIRL at scale and verify that it meets your needs.  

With SWIRL, data democratization is no longer an unattainable Holy Grail. To find out how SWIRL can help you achieve data democratization, contact SWIRL today.