Intentia is launching Movex Business Performance Warehouse, a new decision support solution for Movex customers. The package is based on industry standards and allows customers to analyze data, implement routines and measure performance. It is easy to use and currently consists of 20 predefined views of the information stored in the information warehouse. The philosophy behind the Movex Business Performance Warehouse is partly based on the leading decision support vendor Cognos` strategy "24 Ways" and partly based on the experience from more than 4000 implementations of Movex.
"Movex Business Performance Warehouse gives the management significantly improved access to tactical and strategic business data which is vital in today`s competitive markets", says Johan Berg, CEO of Intentia Research & Development.
With this solution, business managers can measure how efficient the company`s processes are and thereby create a foundation for improving on these processes. It also makes it easier to follow up on financial and non-financial units and combination of these. You could for example track your processes in units like amount, time, quality or other more or less abstract ways of measuring the business processes.
Open Architecture
"The open architecture and the standard technologies that Movex Business Performance Warehouse is built on enables any supplier of business intelligence end-user tools, like Excel 2000, to build customized data marts. This means that Intentia is opening up for a number of strategic alliances in the Business Intelligence Area", says Per Melander, Product Manager at Intentia R&D.
Sometimes the multitude and volume of data in a corporation can overwhelm, and make it difficult to obtain the high quality information needed to make the right decision. By creating separate databases with just the information needed, business managers and other decision-makers can effectively analyze the information by using a set of easy-to-use graphical tools. These databases are commonly known as information warehouses.
Trend Spotting
Business trends and anomalies are often discovered by studying various combinations and permutations of the information available. By combining different factors and combining them in different ways, a business manager might find trends that otherwise would have been difficult to detect.
There are currently some 20 different models supplied with the system, covering the most important business processes like purchasing, storing, finance, sales and human resources. These can be modified to suit each individual customer`s specific demand.
The Technology
The Movex Business Performance Warehouse is based on MicrosoftSQL Server 7 on Windows NT and can be used with Microsoft Excel 2000 as an easy-to-use end user tool where the information is stored in so called OLAP cubes. OLAP stands for Online Analytical Processing and is a way of preparing the information in multidimensional cubes for online, real-time, analysis.
Movex Business Performance Warehouse is a metadata-centric client/server application based on the knowledge of how Movex deals with queries against massive amounts of Movex data. It does automatic transformations of the Movex data into external OLAP models.
These transformations are automatically generated by Movex Business Performance Warehouse` Repository Services and are then scheduled by Microsoft SQL Agent.
Wide Selection of End-User Tools
By using the OLE DB for OLAP, which is supported by many OLAP vendors, the customer can choose from a wide range of tools to use for the end-user. PowerPlay from Cognos is one popular product that is in use among Intentia`s customers all over the world.
The data is transferred incrementally or wholly from Movex and other systems to one or several staging databases. This means that there is less stress to the production databases accessed by the Movex users. From the staging databases, the data is transformed to star schemas where the natural keys have been replaced by dimensional keys. These dimensional keys make it possible to let not just facts, but also dimensions to have a time aspect (a history). Thereby you can follow a product`s life between product groups and product types and so forth. The structures in Movex that aren`t suitable for SQL queries, like tree structures, are straightened out to become de-normalized structures. The transaction tables are aggregated to the desired granularity and the dimensional references are created.
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