Value of the SAS Intelligence Platform

Components of the SAS Intelligence Platform

The SAS Intelligence Platform includes components in the following categories:

Data Integration	The data integration components enable you to consolidate and manage enterprise data from a variety of source systems, applications, and technologies. Components are provided to help you cleanse, migrate, synchronize, replicate, and promote your data. Metadata for all of your intelligence resources is stored centrally and controlled through a single management interface.
Business Intelligence	The business intelligence components enable users with various needs and skill levels to create, produce, and share their own reports and analyses. Through easy-to-use interfaces, users can obtain their own answers to business questions. Meanwhile, the information technology staff retains control over the quality and consistency of the data.
Analytics	SAS offers the richest and widest portfolio of analytic products in the software industry. The portfolio includes products for statistical data analysis, data and text mining, forecasting, econometrics, quality improvement, and operations research. You can use any combination of these tools with the SAS Intelligence Platform to add extraordinary precision and insight to your reports and analyses.
Intelligence Storage	The intelligence storage options are optimized for analytical processing, enabling you to quickly retrieve and report on large volumes of data. The options include simple relational databases, a threaded multidimensional database that supports online analytical processing (OLAP), and relational storage with a threaded multiple input/output (I/O) subsystem for intensive use by focused applications.

The following sections describe the data integration, business intelligence, analytics, and intelligence storage components in more detail.

Data Integration

The software tools in the data integration category enable you to consolidate and manage enterprise data from a variety of source systems, applications, and technologies. The data sources can include SAS data sets, database management system (DBMS) tables, and data from enterprise resource planning (ERP) systems. Metadata for all of your intelligence resources is stored centrally in the SAS Metadata Repository.

Each of the data integration tools is described briefly in the following sections.

SAS Data Integration Studio

SAS Data Integration Studio is a visual design tool that enables you to consolidate and manage enterprise data from a variety of source systems, applications, and technologies. The software enables you to create jobs and process flows that extract, transform, and load data for use in data warehouses and data marts. You can also create processes that cleanse, migrate, synchronize, replicate, and promote data for applications and business services.

For more information, see Clients in the SAS Intelligence Platform.

SAS/ACCESS

SAS/ACCESS provides interfaces to a wide range of relational, hierarchical, and network model databases. With this product, SAS Data Integration Studio and other SAS applications can read, write, and update data regardless of which database and platform the data is stored on. SAS/ACCESS interfaces provide fast, efficient data loading and enable SAS applications to work directly from your data sources without making a copy.

SAS Data Surveyor

The SAS Data Surveyor applications enable you to build SAS Data Integration Studio jobs to read data directly from these ERP vendors: SAP, Oracle, Salesforce.com, PeopleSoft, and Siebel.

SAS Data Quality Server

The SAS Data Quality Server works with software from DataFlux (a SAS company) to analyze, cleanse, transform, and standardize your data. In addition, this product provides SAS procedures and functions that execute jobs and real-time services on DataFlux Integration Servers. The language elements that make up the SAS Data Quality Server software form the basis of the data quality transformations in SAS Data Integration Studio.

Platform Suite for SAS

Platform Suite for SAS is an optional product that provides enterprise-level scheduling capabilities in a single-server environment. Platform Suite for SAS is also included as part of the SAS Grid Manager product to enable distributed enterprise scheduling, workload balancing, and parallelized workload balancing. The components of Platform Suite for SAS include Process Manager, Load Sharing Facility (LSF), and Grid Management Services.

SAS Metadata Repository

All of your information assets are managed in a common metadata layer called the SAS Metadata Repository.

This repository stores logical data representations of items such as libraries, tables, information maps, and cubes, thus ensuring central control over the quality and consistency of data definitions and business rules. The repository also stores information about system resources such as servers, the users who access data and metadata, and the rules that govern who can access what.

All of the data integration and business intelligence tools read and use metadata from the repository and create new metadata as needed.

SAS Management Console

SAS Management Console provides a single interface through which system administrators can manage and monitor SAS servers, explore and manage metadata repositories, manage user and group accounts, and administer security.

Business Intelligence

The software tools in the business intelligence category address two main functional areas: information design, and self-service reporting and analysis.

The information design tools enable business analysts and information architects to organize data in ways that are meaningful to business users, while shielding the end users from the complexities of underlying data structures. These tools include the following products:

SAS Information Map Studio enables analysts and information architects to create and manage information maps that contain business metadata about your data.
SAS OLAP Cube Studio enables information architects to create cube definitions that organize summary data along multiple business dimensions.

The self-service reporting and analysis tools enable business users to query, view, and explore centrally stored information. Users can create their own reports, graphs, and analyses in the desired format and level of detail. In addition, they can find, view, and share previously created reports and analyses. The tools feature intuitive interfaces that enable business users to perform these tasks with minimal training and without the involvement of information technology staff.

The self-service reporting and analysis tools include the following products:

SAS Web Report Studio is a Web-based query and reporting tool that enables users at any skill level to create, view, and organize reports.
SAS Information Delivery Portal provides a Web-based, personalized workplace to help decision makers easily find the information they need.
SAS BI Portlets includes portlets, such as the SAS Stored Process Portlet and the SAS Report Portlet, that add value to the SAS Information Delivery Portal.
SAS BI Dashboard enables SAS Information Delivery Portal users to create, maintain, and view dashboards to monitor key performance indicators that convey how well an organization is performing.
SAS Add-In for Microsoft Office enables users to access SAS functionality from within Microsoft Office products.
SAS Enterprise Guide is a project-oriented Windows application that enables users to create processes that include complex computations, business logic, and algorithms.

As users create information maps, cubes, report definitions, portal content definitions, and stored processes, information about them is stored in the SAS Metadata Repository. Client applications and users can access these information assets on a need-to-know basis. Access is controlled through multilayered security that is enforced through the metadata.

For a description of each of the business intelligence tools, see Clients in the SAS Intelligence Platform.

Intelligence Storage

The data storage options that are available with the SAS Intelligence Platform include SAS data tables, parallel storage, multidimensional databases, and third-party databases. These storage options can be used alone or in any combination.

All metadata for your data sources is stored centrally in the SAS Metadata Repository for use by other components of the intelligence platform.

Each of the options is described briefly in the following sections.

Relational Storage: SAS Data Sets

You can use SAS data sets, the default SAS storage format, to store data of any granularity. The data values in a SAS data set are organized as a table of observations (rows) and variables (columns). A SAS data set also contains descriptor information such as the data types and lengths of the columns, as well as which SAS engine was used to create the data.

Multidimensional Storage: SAS OLAP Server

The SAS OLAP Server provides dedicated storage for data that has been summarized along multiple business dimensions. The server uses a threaded, scalable, and open technology and is especially designed for fast-turnaround processing and reporting.

A simplified ETL process enables you to build consistent OLAP cubes from disparate systems. A threaded query engine and parallel storage enable data to be spread across multiple-disk systems. Support is provided for multidimensional (MOLAP) and hybrid (HOLAP) data stores, as well as for open industry standards.

Parallel Storage: SAS Scalable Performance Data Engine and SAS Scalable Performance Data Server

The SAS SPD Engine and SAS SPD Server provide a high-speed data storage alternative for processing very large SAS data sets. They read and write tables that contain millions of observations, including tables that exceed the 2-GB size limit imposed by some operating systems. In addition, they provide the rapid data access that is needed to support intensive processing by SAS analytic software and procedures.

These facilities work by organizing data into a streamlined file format and then using threads to read blocks of data very rapidly and in parallel. The software tasks are performed in conjunction with an operating system that enables threads to execute on any of the CPUs that are available on a machine.

The SAS SPD Engine, which is included with Base SAS software, is a single-user data storage solution. The SAS SPD Server, which is available as a separate product, is a multi-user solution that includes a comprehensive security infrastructure, backup and restore utilities, and sophisticated administrative and tuning options.

Third-party Databases

The SAS Intelligence Platform can access data that is stored in third-party relational, hierarchical, and network model databases. Examples include DB2, Oracle, SQL Server, Teradata, IBM Information Management System (IMS), and Computer Associates Integrated Database Management System (CA-IDMS). SAS/ACCESS interfaces provide fast, efficient reading and writing of data to these facilities.

Several SAS/ACCESS engines support bulk load of data files and threaded reads. Threaded reads let you read blocks of data on multiple threads instead of a record at a time. Several engines can use multiple threads to the parallel database management system (DBMS) server to access DBMS data. Both features significantly improve performance so that you can read and load data more rapidly without changing your original data.

Analytics

SAS offers the richest and widest portfolio of analytic products in the software industry. The portfolio includes products for statistical data analysis, data and text mining, forecasting, econometrics, quality improvement, and operations research. You can use any combination of these tools with the SAS Intelligence Platform to add precision and insight to your reports and analyses.

SAS software provides the following types of analytical capabilities:

statistical data analysis, to drive fact-based decisions
data and text mining, to build descriptive and predictive models and deploy the results throughout the enterprise
forecasting, to analyze and predict outcomes based on historical patterns
econometrics, to apply statistical methods to economic data, problems, and trends
quality improvement, to identify, monitor, and measure quality processes over time
operations research, to apply techniques such as optimization, scheduling, and simulation to achieve the best result

The following are examples of analytic products:

SAS Enterprise Miner enables analysts to create and manage data mining process flows. These flows include steps to examine, transform, and process data to create models that predict complex behaviors of economic interest. The SAS Intelligence Platform enables SAS Enterprise Miner users to centrally store and share the metadata for models and projects. In addition, SAS Data Integration Studio provides the ability to schedule data mining jobs.
JMP is interactive, exploratory data analysis and modeling software for the desktop. JMP makes data analysis--and the resulting discoveries--visual and helps to communicate those discoveries to others. JMP presents results both graphically and numerically. By linking graphs to each other and to the data, JMP makes it easier to see the trends, outliers, and other patterns that are hidden in your data.

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