There is a lot of buzz in the analytics industry today about how to operationalize and deliver a return on investment for artificial intelligence (AI) and machine learning (ML) projects. What is well known about these ambitious efforts is that it takes time to build the models, and roughly 70% of a data scientist’s time is spent either cleaning data or creating attributes and features (the structured data inputs) for models.
But what is often overlooked or goes unrealized is these features have likely already been developed in their team or organization. You can find them in business intelligence reports, operational software platforms, ad hoc analyses, and on and on. The dirty secret is most of these features are developed first in SQL, though they’re not easily discoverable and even if they were, they’re not consistent. Teams and departments are starting to realize this, and a new emerging category is starting to gain steam, Analytics Management.
We’ve all heard of Data Management, but only so much can be gained by managing your data. Most in the industry are quickly finding out you must also manage and govern your logic or math, your analytics, viewing it as an organizational asset.
As a pioneer in the analytic management space, Aginity, the only active analytics catalog company, is reimagining and transforming the boundaries of analytic management, empowering organizations to mine and leverage the full value of their analytic logic. Aginity believes it’s easier to than you might think to get started – start by managing your SQL first.
SQL is still the #1 data and analytics programming language. SQL is still the first programming language in which most analytics are first developed. Yet today’s SQL logic is trapped in desktops, servers, endpoint applications, repositories and most often shared via email or chat applications. It’s not consolidated and easily reusable, so it’s rebuilt over and over again leading to inconsistency and duplicative work. Plus, SQL tools and methodologies still function and look the way they did 15 years ago.
Aginity knows these challenges firsthand. They have supported the SQL community for more than 10 years via Aginity Workbench, the SQL tool of choice for more than 3,000 companies worldwide. This spring they expanded their offerings to provide a way for individual SQL developers to catalog, manage and reuse context-rich SQL on their desktops with Aginity Pro. Quickly on the heels of Aginity Pro, Aginity Team launched this summer and enables an additional level of analytic discovery and team collaboration to improve productivity and maintain total consistency across users and their peers.
“The true differentiator in these products is users can execute saved SQL queries or their sub-components at runtime by referring to their catalog names. For individuals, it makes them faster analysts, focused on the next novel analysis. For teams, it essentially allows users to “subscribe” to the best SQL assets of an organization and to find and re-use those consistently. If you have the correct permissions and security access, the trusted SQL logic you need is right there for you.”, said Jeff Grossman Vice President of Product and Customer Solutions at Aginity.
The company believed in managing your SQL first so much they pivoted their business model from a top-down sales and deployment approach to a grassroots effort to connect with their Workbench community and the approximately 20 million SQL analysts worldwide and to show them there’s a new way to work with SQL – the strategy is working.
The market is responding and adopting Aginity’s new products quickly. Since launching Aginity Pro is actively being used by more than 8,000 SQL analysts and several teams are adopting Aginity Team at large companies. Today, Aginity is working with 33% of the Fortune 100 across a wide range of industries including health care, finance and insurance, retail and technology and consulting.
“We’re excited about the success we’ve had this year. We saw the re-creation of math over and over again at companies, and we knew there was a better way. That’s why we built Aginity Pro and Aginity Team – to help teams and companies build a foundation of consistent analytics that were easily discoverable, sharable, reusable, and governed across a wide range of use cases”, said Paul Schaut, CEO of Aginity, a seasoned executive with 37 years of experience in data and analytics.
While Aginity is focused on driving the growth of Aginity Pro and Aginity Team, they know this is just the start of a bigger opportunity. Analytics Management will go beyond just SQL to manage more sophisticated analytics such as AI and ML models. But to get started, Aginity will remind you to start small and remember it’s “all about the SQL first”.