2 Introduction – Data Block Architecture

The data modeling features in Style Studio allow you to connect to various data sources, and create queries, data models, and virtual private models (VPMs). These assets can be used directly to supply data to reports and dashboards. They also lay the foundation for Data Block technology, which allows you to create sophisticated data mash-ups from heterogeneous data sources. (For more information on Data Worksheets, please see the Data Mashup.)

Style Studio's data modeling features give you ready access to data stored in relational databases, objects, and flat files. Databases include data warehouses, data marts, mainframes, operational data stores (ODS), multi-dimensional databases (OLAP), and transactional databases (OLTP). Objects include web services, XML, and plain old java objects (POJO). Flat files include spreadsheets, CSV, and text.

Data Block architecture distinguishes the Style Intelligence approach to meta-data modeling from that of other business intelligence platforms. Instead of focusing on narrow pre-purposed business intelligence tasks, Style Intelligence lets you concentrate on designing Data Blocks that represent data in a way that business users understand. You can then assemble these Data Blocks in different combinations to address whatever business needs arise, now or in the future.

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