|Deeper Analytic Insights
||Create highly complex business logic using conditional statements, extensions to programming languages such as R and Python, and pattern identification, statistical, dimensional, and correlation analysis capabilities. Apply that logic to large data sets from multiple data sources to gain deeper, more accurate analytic insights.
|Rapid Analytic Development
||A visual interface and agile data management capabilities allow analysts to create or change analytic applications 10 times faster than with traditional analytic tools, resulting in faster insight and a quicker response to new questions that arise.
|Agile Data Integration, Preparation, and Management
||Cleanse, transform, enrich and combine data without intensive scripting, modeling or schema development –just “join and go”.Use fuzzy matching to join data without a clear one-to-one join field. Harness the value of enterprise systems, cloud-based applications, Big Data sources, such as MongoDB and Hadoop, warehouses, databases, legacy systems, and files using standard connectors for JDBC/ODBC, web services, XML and more.
||IT can publish custom visual elements to govern the calculations, business rules, and data used for analytics. IT can govern the use of data and analytic logic by user or user type.
|Greater Trust in Data and Analysis
||A “self-documenting” visual environment helps you communicate logic and insights to non-technical business users so you can build trust in your analytic application and shorten the time to take action on the insight.
|Faster Time to Action
||Run analytics continuously to monitor operational data and ensure compliance or identify outliers, anomalies, or exceptions. Use integrated alarming, case management, reporting, and query capabilities to resolve issues or opportunities detected by the platform in a consistent, detailed, and controlled manner.