Scheduled Analytics
Setting up and managing scheduled analytics. Scheduling off hours access to production data
CENTRALIZED ANALYTICS - SIMPLIFIED
Contrary to what many companies have experienced, deploying a centralized analytics platform does not need to be complicated, time consuming, or expensive. The Arbutus Hub has proven to be powerful but, easy to implement solution for many organizations around the world
POWERFUL FEATURES
The Arbutus Hub is the foundational component of Arbutus Platform, as well as an optional, but key part for Fraud Detection, Cost Recovery and Data Solutions. The Arbutus Hub is used to support a number of important capabilities that benefit from having a centralized platform. Some of the capabilities that Arbutus Hub enables include:
Secure Analysis
Maintaining all sensitive and important data on secure servers. World wide access to data, tests and results in a secure way
Incredible Performance
Additional processing performance for big data files. Offloading of time-consuming analytics from production or desktop environments
Engineered For High Performance
Designed to Scale. Built for Speed
The Arbutus Hub resides natively on one or more of your organizations servers, providing fast, efficient data access and query processing support for Audit Analytics, Fraud Detection, Cost Recovery and Data Solutions. Advantages of the Arbutus Hub:
- Staging data from multiple platforms
- Offloading CPU cycles from prod environments
- Access solutions for historical data
- Process any data
- Analyzing data
- Sharing of data
- Optimal processing performance
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Optimizes performance or increases analysis and reporting capabilities
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Allows for the transparent joining and comparing of data from disparate sources
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Staged data can be used just as if it were in a data warehouse
- A simple, low-cost solution to stage and access all of your organizational data including mainframe, AS/400 and SAP data
- Staging data is as simple as a file transfer, with no data transformation required
Usage and access solutions for historical data from decommissioned platforms
- Fully compatible with all data set structures and data types encountered on your mainframe, Unisys, HP, or DEC platforms
- Staging historical data is as simple as a file transfer, with no data transformation required
Moving, Combining and processing data from any data file, database, and data mart
- Process data from any database that can be accessed via any ODBC connection including DB2, SQL Server, and Oracle
- Specializes in reading both relational and non-relational data sources, including the most complex legacy file structures
- Local data, staged mainframe data, and even SQL databases can be combined and integrated in any way desired, into a single unified view
- Data sources can be easily moved between server platforms or from the server to the desktop
- Data and databases can be easily brought together from multiple platforms for analysis and reporting purposes
- Analysis can take place on the server, the desktop, or a combination of each
- Allows analysis to occur against ‘live’ data or staged data, providing complete analysis flexibility
- Supports the easy sharing of data access and analysis among users
- Data access can be controlled by a central administrator, whether on-site or from a remote location
- Optimized for strong performance in processing large data files, allowing end-users to experience faster response times to their queries