Is a glass half full or half empty? That depends on your point of view. The same facts and data can produce multiple points of view. These multiple views can be utilized by multiple people for different reasons. This is the function of OLAP Services. On-Line Analytical Processing (OLAP) provides customers with tools that can be used to perform "multidimensional analysis" on data to discover hidden information within the database. NCR Corporation recently announced that it has added a comprehensive suite of OLAP Services to its Teradata relational database.
OLAP uses a multidimensional view of aggregate data to provide quick access to strategic information for further analysis. Users can gain insight into data through fast, consistent, interactive access to a wide variety of possible views of information. This allows everyone in the enterprise to see the corporate data warehouse from their particular point of view.
Data warehouses have always been able to answer "who" and "what" questions. OLAP applications take the next step by answering "what if" and "why" questions. OLAP enables decision making about future actions, and that is typically more complex than simply summoning data. An example of an OLAP calculation: "What are my month-to-date revenue and unit sales, along with the current and ending on-hand position for the top 10 products in the women's casual wear product category, and what is their percentage contribution to the total sales in the category?"
Teradata and OLAP Services are an excellent combination. Teradata is the performance leader in data warehousing and OLAP Services are designed to help customers achieve even better performance on large volumes of data. Teradata is the only database on the market that loads data, processes data and backs up data in parallel.
This is the most efficient way to process gigabytes and terabytes of data by spreading the work evenly among hundreds of processors. Each processor is responsible for a different portion of the database. When a request is made, the processors work in parallel on their portion of the database. The larger the data warehouse grows, the more Teradata outperforms competitive products.
NCR has developed a new Teradata database feature that will be the basis for OLAP Services called TeraCube. TeraCube is designed to generate information for business users by dynamically generating SQL (Structured Query Language) from dimensions of a user's inquiry using specialized database navigation technology and standard programming objects. This will create multidimensional data on an ad hoc basis--thus providing an environment that is more responsive to changing business needs than traditional databases.
In addition, NCR has also developed new parallel OLAP extensions to Teradata SQL that will improve the performance of OLAP tools and applications. These include:
- Statistical functions that will take advantage of Teradata's parallelism, resulting in faster computation of functions such as FORECAST, RANK and QUANTILE;
- Functions that pre-select data which meet certain criteria and that significantly reduce the amount of data that will need to be returned to intermediate result sets or temporary tables;
- New "calendar" functions that improve performance of arithmetic and comparisons involving dates.
Teradata OLAP Services are designed to provide an open foundation for tools and solutions from NCR's many third-party partners. These capabilities are accessed through industry-standard interfaces, including the Microsoft OLE DB for OLAP specification. By aligning with Microsoft, NCR and its third-party partners are further able to develop their strategic alliances and jointly bring new products to market.
OLAP and data warehouses go hand in hand. A data warehouse stores and manages data, and OLAP transforms the data into strategic information. OLAP ranges from basic navigation and browsing, to complex calculations, to more serious analyses--such as time series. As decision-makers gain experience with OLAP capabilities, they move from data access to information to knowledge.
OLAP insulates users from complex query syntax, modeling designs and elaborate joins. OLAP's multidimensional view of data provides the foundation for analytical processing through flexible information access. The design of the database should not be the "controlling" factor in determining which operations can be performed on a dimension or the speed at which those operations are performed. Users must be able to analyze data across any dimension, at different levels of aggregation, with equal functionality and ease.
OLAP also provides users with the information they need to make effective decisions about an organization's strategic directions. A key indicator of a successful OLAP application is its ability to provide pertinent information for effective decision making.
Teradata has been one of the data warehouse leaders for more than 10 years because it was designed around parallel processing. Teradata was created to manage from as little as 10 gigabytes to multiple terabytes of detailed data; and the introduction of OLAP Services has extended its power, flexibility and ease of use.
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