Mining useful information from a database can be difficult, especially when your database is large and structured in a complex fashion.
Yet information is like lifeblood for businesses, and those who can extract it can use it to gain market share and dominate competitors.
While most companies have large amounts of data, either the data is not structured in a way that makes it useful or they do not have the tools needed to extract information efficiently.
Ultimately you can think of machine learning as one way to perform predictive analytics, and in many cases, it is the most accurate.
Embedding AI capabilities into an existing database make the power of machine learning accessible to anyone able to run an SQL query.
Simply adding AI to an existing database opens the data’s full potential by bringing machine learning directly to the source.
As noted earlier, building a machine learning model is complex and requires specialized resources.
Just connect it to your database, run a query, train the model, and get forecasts as tables in your existing databases.
In the end, simplifying machine learning and bringing it to the database allows data users to reap more benefits of predictive analytics.
Giving machine learning tools to the end-user will reveal exciting new uses for the technology and new ways to leverage the insights gained.
As machine learning matures as a technology, companies will enjoy an improved ability to predict customer behavior.
Is your business having difficulties with extracting information to gain market share?