Putting the Data to Work for You

Your business has access to more data than ever before. Data warehouses, CRM applications, e-business solutions – each add to your enterprise data resources. What matters though is not that you have the data, but rather what you can do with the data. Or better yet – what the data can do for you.

CCA Analytics is a business intelligence solution that helps users analyze their data resources and ultimately make better business decisions. With CCA Analytics, users can explore their data at will. Slice and dice data in any way necessary. Ask questions of their data that they had never before considered. And do all this on demand and without the need for IT assistance.

Working in a Windows-based point-and-click environment, business users are able to:

• Acquire a better understanding of the data
• Create subsets or segments of the data for targeted analytical or operational purposes
• Display or export the data in whatever format is required for maximum decision-making

Ultimately, CCA Analytics enhances your business and sharpens your competitive edge by helping you get the most out of all your data resources.

Functional Overview

Business users typically know what information they want from the data, but do not have the programming skills required to get it. As a result, they often rely on the IT department to deliver custom reports, charts, and graphs each time they require a new piece of information. CCA Analytics changes all that by providing a powerful yet intuitive environment for business users to browse, discover, and analyze their data, without constant intervention from the IT staff.

Query and Segmentation

With CCA Analytics, users can easily perform simple or complex queries in a point-and-click environment, without really knowing anything about the data. The values associated with each field are provided to the user upon request, helping the user find the exact data needed. Users can even search the data based on the result of a macro or formula, versus a specific value. Because users don’t always know what they’re looking for when they first begin to access the data, queries can be iteratively refined, allowing them to eventually narrow down the database in a step-by-step fashion. Once the ideal selection set of records and fields is found, the user can name and save the selection criteria for easy retrieval at a later date.

Data Summarization

Analytical applications are generally more concerned with data summaries than with detailed records. Using CCA Analytics, users can quickly obtain summaries of the data such as counts, averages, and maximum and minimum values. Summaries can be grouped by any number of different fields, or even by computed values. Because of the unique indexing technology inherent to CCA Analytics, summaries appear fast – regardless of database size – because computations are executed against the efficient index table structures, rather than the actual database records. This technology is further described below.

Displaying the Data

CCA Analytics provides numerous tools for viewing selected data, including reports, charts, and graphs. Multi-dimensional graphical displays are supported to help users easily visualize complex relationships present in the data. Not only do these output formats display the data, but they are interactive, allowing the user to manipulate them to form new queries, drill down to underlying data, or view the data from different perspectives. If you require more specialized viewing of the data, CCA Analytics lets you easily export the data into other analytical packages such as spreadsheets or OLAP tools.

Maximum Performance with Bit-Map Indexing Technology

Analytical applications are different from their OLTP counterparts. They generally require fast analysis and summarization of exceedingly large quantities of data. While every analytical tool provides easy-to-use query and display features such as those mentioned above, they cannot always be used for real-world analytical applications, such as a data warehouse, due to performance restrictions.

CCA Analytics relies on the advanced bit-mapped indexing technology pioneered by Rocket's Model 204 database management system, and widely recognized today as the best technology for many types of queries and transactions. Bit-mapped indexing dramatically speeds data access by eliminating the need to constantly access full data records. Queries and transactions are often performed solely on the compact indexes, significantly reducing costly disk I/O.

CCA Analytics also allows every data item in every database to be indexed and supports the revolutionary concept of ‘Invisible Data’. Using ‘Invisible Data’, new criteria can be added for analysis without storing actual data in the physical records. This allows databases to be “pre-joined”, which dramatically improves the performance of queries that involve fields from multiple databases. It also means that CCA Analytics does not need to store actual data records at all! So you can represent multi-gigabyte databases solely as index structures, saving a tremendous amount of disk space, and resulting in lightning-fast queries against the data.

These sophisticated technologies result in superior performance and tremendous cost-savings for analytical applications.