Oracle & OLAP

On-Line Analytical Processing (OLAP) is a category of software technology that enables analysts, managers and executives to gain insight into data through fast, consistent, interactive access to a wide variety of possible views of information that has been transformed from raw data to reflect the real dimensionality of the enterprise as understood by the user.

OLAP functionality is characterized by dynamic multi-dimensional analysis of consolidated enterprise data supporting end user analytical and navigational activities including:

• calculations and modeling applied across dimensions, through hierarchies and/or across members
• trend analysis over sequential time periods
• slicing subsets for on-screen viewing
• drill-down to deeper levels of consolidation
• reach-through to underlying detail data
• rotation to new dimensional comparisons in the viewing area

OLAP is implemented in a multi-user client/server mode and offers consistently rapid response to queries, regardless of database size and complexity. OLAP helps the user synthesize enterprise information through comparative, personalized viewing, as well as through analysis of historical and projected data in various "what-if" data model scenarios. This is achieved through use of an OLAP Server.

OLAP SERVER

An OLAP server is a high-capacity, multi-user data manipulation engine specifically designed to support and operate on multi-dimensional data structures. A multi- dimensional structure is arranged so that every data item is located and accessed based on the intersection of the dimension members which define that item. The design of the server and the structure of the data are optimized for rapid ad-hoc information retrieval in any orientation, as well as for fast, flexible calculation and transformation of raw data based on formulaic relationships. The OLAP Server may either physically stage the processed multi-dimensional information to deliver consistent and rapid response times to end users, or it may populate its data structures in real-time from relational or other databases, or offer a choice of both. Given the current state of technology and the end user requirement for consistent and rapid response times, staging the multi-dimensional data in the OLAP Server is often the preferred method.

It is important to distinguish the capabilities of a Data Warehouse from those of an OLAP (On-Line Analytical Processing) system. In contrast to a Data Warehouse, which is usually based on relational technology, OLAP uses a multidimensional view of aggregate data to provide quick access to strategic information for further analysis.

OLAP enables analysts, managers, and executives to gain insight into data through fast, consistent, interactive access to a wide variety of possible views of information. OLAP transforms raw data so that it reflects the real dimensionality of the enterprise as understood by the user.

While OLAP systems have the ability to answer "who?" and "what?" questions, it is their ability to answer "what if?" and "why?" that sets them apart from Data Warehouses. OLAP enables decision-making about future actions. A typical OLAP calculation is more complex than simply summing data, for example: "What would be the effect on soft drink costs to distributors if syrup prices went up by $.10/gallon and transportation costs went down by $.05/mile?"

OLAP uses

Typical OLAP Applications

• The need of end users to analyze corporate data for the purpose of making better decisions is of paramount importance.
• OLAP technologies are essential to delivering this end-user value and are a critical component of a broader information technology architecture.
• Corporate data needs to be transformed into multidimensional aggregations supporting enterprise-scale data volumes and hierarchies.
• Fast, consistent response to end-user requests is critical to interactive, ad-hoc exploration, comparison and analysis of data, regardless of database size and complexity.
• End users must be able to manipulate and derive data for analysis purposes by applying analytical operations such as ratios, cumulative totals, trends and allocations across dimensions and across hierarchical levels.
• An OLAP Server may either physically stage the processed multidimensional information or populate its data structures in real-time from relational, OLTP or other databases, as long as it delivers consistent and rapid response to end users.

OLAP has evolved as users' needs for data analysis have grown. It provides executives, analysts and managers with valuable information via a " slice, dice and rotate" method of end user data access, augmenting or replacing the more complicated relational query. This slice and dice method gives the user consistently fast access to a wide variety of views of data organized by key selection criteria that match the real dimensions of the modern enterprise. OLAP performs multidimensional analysis of enterprise data including complex calculations, trend analysis and modeling. Derived from end-user requirements, OLAP enables end-users to perform ad hoc analysis of data in multiple dimensions, thereby giving them the insight and understanding they need for better decision making.

OLAP server technology is the key to high performance analytical use of large databases. Its added intelligence about the structure and organization of the data, as compared with flat, detailed relational tables, makes an OLAP server more responsive to end user requests while also eliminating SQL-style queries. An OLAP server may physically stage the processed multi-dimensional information to deliver consistent and rapid response times to end users, or it may populate its data structures in real-time from relational or other databases, or it may offer a choice of both.

Time Intelligence

Time is an integral component of almost any analytical application. Time is a unique dimension because it is sequential in character (January always comes before February). True OLAP systems understand the sequential nature of time. Business performance is almost always judged over time, for example, this month vs. last month, this month vs. the same month last year.

In addition, OLAP systems must understand the concept of balances over time.

Oracle Software

Extending Leadership to the Internet
Oracle8i is the only database specifically designed as an Internet development and deployment platform, extending Oracle's long-standing technology leadership in the areas of data management, transaction processing and data warehousing to the new medium of the Internet. Built directly inside the database, breakthrough Internet features help companies and developers build Internet-savvy applications that lower costs, enhance customer and supplier interaction, and provide global information access across platforms and across the enterprise.

Oracle8i JVM
Oracle8i JVM is a server side Java engine for the Oracle8i database. It includes a Java Virtual Machine with a native compiler, a CORBA 2.0 ORB, an EJB server, an embedded server side JDBC driver, and a SQLJ translator. The Oracle8i JVM constitutes the heart of Oracle8i's support for Java. Developed by Oracle, the VM is 100% JDK compliant and leverages Oracle8i's multithreaded and highly scalable parallel server architectures with excellent performance on SMP and MPP architectures. It enjoys an advanced memory model for exceptional scalability to thousands of simultaneous connections over the Internet for an entire enterprise.

Portal-to-Go, a component of the Oracle Internet Platform, is a new server product that enables any existing database and internet application to be made accessible from virtually any device connected to the internet:

	WAP smartphones
	Wireless PDAs such as the Palm VII
	Standard phones connected to Interactive Voice Recognition (IVR) systems.
	Modem equipped personal organizers
	Set-top boxes, etc.

Using Portal-to-Go, mobile operators, content providers, and wireless ISPs may create their own wireless portal, and small to large corporations may seamlessly extend the reach of their existing enterprise systems to mobile users.