Committed to making big data analytics faster and easier for everyone, Datameer today announced Datameer 3.0, the newest version of its big data analytics tool for business users. Building on its self-service data integration, analytics, and visualization capabilities, Datameer 3.0 will add new Smart Analytic functions, which, with a single click, will automatically identify patterns, relationships, and even recommendations based on data stored in Hadoop.
With Smart Analytics, four advanced machine learning techniques, Clustering, Decision Trees, Column Dependencies and Recommendations become self-service and accessible for data-driven business users for the first time. Previously, these advanced analytics required highly specialized data scientists to build custom functionality, which is a costly and time-consuming process.
“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,” said Stefan Groschupf, CEO of Datameer. “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.”
Clustering, Decision Trees, Column Dependencies and Recommendations
Each new Smart Analytic function enables users to better understand their data, faster, and see where to concentrate their efforts or dig deeper in their analytics.
• With the new Clustering feature, Datameer automatically organizes and aggregates groups within a given dataset. This way, businesses can improve targeting based on common data attributes like location, medication, phone type, operating system, or any number of attributes that might allow a business to better segment their data.
• The new Decision Tree function allows users to select a desired outcome like purchase, response to a medication, pass or fail, or download, for example, and have Datameer automatically identify and weight the different combinations of data attributes that lead to that result. Then, the user can see the attributes of a customer, and/or type of outreach a customer responded to that led to a transaction, for instance.
• The Column Dependency function automatically compares every possible combination of data attributes and visually previews the strength of each attribute’s correlation. This can reveal non-obvious correlations between specific data attributes, like location and disease type, or job title and credit score.
• Finally, Datameer’s new Recommendation function automatically predicts if, and how likely it is, a person will be interested in something based on historical data from many users. This allows businesses to serve up more relevant content, products or service recommendations without needing a data scientist.
“I see tremendous value in what Datameer is doing with the new Smart Analytics functionality in combination with their already strong self-service data integration, analytics, visualization and collaboration features,” said John Myers, Senior Analyst for Business Intelligence and Data Warehousing at Enterprise Management Associates, a Boulder Colorado based research firm. “Advancements like this make Hadoop even more usable to the business.”
Datameer 3.0 will be available in the Fall of 2013. In the meantime, anyone can sign up for the Datameer 3.0 early adopter program at http://info.datameer.com/early-adopter.html.