Datameer wants to make Big Data more accessible for decision makers with “Smart Analytics,” a set of self-service machine learning capabilities built into the newest release of its flagship solution. The toolset empowers users to “identify patterns, relationships, and even recommendations based on data stored in Hadoop” using a simple point-and-click interface.

Smart Analytics covers a lot of bases. It automatically sorts data based on location, operating system and other criteria, and generates decision trees that map consumer behavior. It also includes a column dependency function that identifies and visualizes non-obvious correlations between metrics such as location and disease type, or job title and credit score.

The fourth Smart Analytic capability is a predictive recommendation tool that uses historical data to calculate if and how likely a given person is to be interested in a specific offering, be it content, products or services.

Stefan Groschupf, the CEO of Datameer, explained that “the pace of business continues to accelerate while the volume and complexity of data continues to grow, making it difficult for businesses to get the timely insights they need. With the new functionality in Datameer 3.0, it’s all about making big data analytics faster, easier, and now smarter by helping business users amplify the signal in the noise, without a data scientist.”

Datameer is looking to make Big Data more consumable by taking the alpha geek out of the equation, but a startup called Mortar Data is taking a different approach. According to  CEO Jon Hoffman, the company’s cloud-based Hadoop framework leverages MongoDB to help data scientists process information both rapidly and cost-effectively. He stopped by theCube at the recent MongoDB Days conference to discuss the product and make the case for data science.