SiSense, a provider of business intelligence (BI) tools for SMBs, has unveiled PrismCubed, a new tool for business intelligence, capable of visual representation and ad-hoc queries of integrated data from several data sources.
SiSense said that small and mid-sized businesses have multiple data sources that need to be integrated. With PrismCubed, companies can perform information analysis from existing company databases and deploy them to users and create a secure product..
The new tool’s interface is designed for business intelligence application creation, including intuitive dashboards and guided analytics from multi-sourced and disparate data. It allows users to perform all data preparation, integration, synthesis and joins using a visual workflow, enabling the development of an enhanced business intelligence practice, the company said.
According to SiSense, PrismCubed’s new data store utilises in-memory technology coupled with a columnar database, eliminating the demand for resource-draining data warehouses or OLAP implementations. The PrismCubed tool can connect directly to data sources such as Oracle, SQL Server MySQL and even an existing OLAP to show live dashboards and guided analytics applications.
SiSense, co-founder and CEO of Elad Israeli, said: “SMBs need clean data that is ready for analysis and accessible by many. They need all the power and functionality of an enterprise analytics system brought to the fingertips of any executive or IT manager without the resource baggage of programming, long project cycles, training, and unnecessary drain on time and budget.”
The PrismCubed tool is expected to cover the entire process of building business intelligence applications powered by multidimensional analytics, from Extract, Transform and Load (ETL) of data coming from disparate data sources to dashboard and analytics creation and deployment.
Reportedly, data from sources like Excel, csv, Access, Microsoft Analysis Services, SQL, MySQL, Oracle and others can be sourced and processed for analysis by PrismCubed. The integrated centralised data can be deployed locally or on a server.
