I own a 1946 Chevy pickup truck. It is a simple vehicle. No radio, no air conditioning; heck, seat belts and rear turn signals were options. But despite all of its simplicity, it is not that easy to drive. It has no power steering, it is slow and the manual transmission is as grumpy as my ten year old son in the morning. Thankfully, vehicles have evolved, and while they have become highly complex machines with onboard computers, back-up cameras, electronic fuel injection and power steering, they are actually much easier to drive than that old truck. While my modern car may have more computational power than the Apollo 11 that put Armstrong and Aldrin on the moon, I don’t have to be a rocket scientist to use it.
And so it goes for most modern day conveniences. I don’t know much about photography but I can take perfect pictures with just the push of a button. I don’t need to learn how to write code to use my computer. Virtually every piece of technology that we interact with has been created with a simple, easy to use interface. Except databases and data warehouses.
With over 300 vendors to choose from to store what is expected to be 25 zettabytes by 2025, the complexity of managing all of this data is mind-boggling. And as the complexity has increased, ease of use has decreased, so much so, that today only a very select and highly trained few can interface with it.
This translates into a highly complex environment that has removed the business user from being able to interact with their data. Instead, they rely on data scientists to answer their most pressing questions, and that is not working out so well. No disrespect to data scientists, but there just aren’t enough of you to go around.
If I was graduating from college today, this is the career path I would pursue because demand is high, and supply is low. There is a shortage of data scientists in relation to the massive amounts of data that demands their attention, which has resulted in a roadblock for business users as queries relating to running an efficient and successful business are delayed weeks, if not months.
A solution is needed to help remove the obstacles preventing business users from having a direct relationship with their data. How can data analysis be scaled to fit the enterprise, rather than being compartmentalized and managed by a highly skilled few?
Promethium believes they have found a way. Promethium not only streamlines the entire data analytics process with just one tool, but significantly improves the accuracy of the results by allowing the user to start a search by asking a simple question in English and using AI to automatically map the relevant data required to answer that question. For example, instead of spending weeks and months searching through granular layers of files and tables with no contextual relevance, a user can simply ask: “What types of drugs were sold in the last 30 days?” Promethium then automates and simplifies every step of the process. Equally important, with Promethium, non-technical business users can have everything from data models, lineage, data quality, and even SQL queries automatically generated for him/her just by typing a question in English.
Modern technology has given us the ability to process and analyze vast amounts of data at a scale unimaginable just a few years ago, but it comes with layers and layers of complexity that has distanced the business user from gaining access to its answers. Promethium has simplified data analysis and the data complexity matrix, reducing time to value, cost and complexity for the business user.
To learn more about how Promethium can help streamline your data analytics and governance efforts, download our ‘End-to-End Self Service Analytics’ use case or visit www.pm61data.com.
About Promethium:
Promethium is an augmented data management provider and the first company to combine natural language processing with self-service analytics, which allows users to tap their organization’s entire data estate for answers to questions asked in plainspoken language. Promethium’s AL and ML-driven contextual automation software delivers actionable insight within minutes instead of months while ensuring all data used to deliver information is fully governed."