OLAP also contains something called LEVEL. The levels are hierarchical subsets of a dimension. For instance if the parent level is Nissan the child level would be Altima. OLAP has many storage alternatives like; ROLAP (Relational OLAP), MOLAP (Multidimensional OLAP), and HOLAP (Hybrid OLAP). These variations where created to better meet specific needs as for ROLAP; it was design with the purpose in mind of processing certain queries as well as other types of extensions that other relational database products would be more than adequate to handle. On the other hand MOLAP was designed to handle what some believe to be better performing in that it would handle specialized reports, queries and transaction processing in a more specialized way than any database management system could possibly produce. As the word HYBRID suggests, this was created with the .
OLAP, DW, DM, TTA, ASP 4.
purpose of using the best performance attributes of the MOLAP and the ROLAP in order to gain a much more hi performance data storage system that both, the OLAP and DBMS system could benefit from. So in essence OLAP is not a graphical presentation application, it is a data storage application option that can be accessed by different DBMS query languages. .
Another storage solution for data is Data Warehouse. As data is accessed by users it increases in it utility. However the more users access this data, the management of such becomes more cumbersome in nature. This is why Data Warehouse was created. Data Warehouse is nothing more than a location where to store large amounts of data thus making it more manageable for the database administrator as well as anyone involved with its maintenance. Its main role is to provide the information requested by the end users in a form that is useful to all that accessed it. It can hold a multitude of information in many different formats whether it be images or any none scalar data.
This could be accomplished using an OLAP tool against the data warehouse. ... Data retailers are often called Online Analytical Processing (OLAP) systems. In contrast to OLTP systems, OLAP systems are optimized for rapid data retrieval, summarization and, as the term indicates, analysis. The goal of OLAP systems is to turn large amounts of data into valuable, actionable business information for decision making. ...
Abstract The plain and simple fact is that e-businesses today cannot endure or prevail without quality data about their internal and external environment and operations (O'Brien, 2003). Therefore, many companies, large and small, need to use database management systems. We will be exploring some of...
Introduction DATA is a dream. Documents are a nightmare. Companies that have taken the leap into the ERP Age, wiring up their operations across the organisation, are soaking up the benefits of having real-time, accurate, and crisp facts and figures delivered to every desktop so greedily that they've forgotten about the messier half of information management.So this is the other side to the picture. WHILE ERP integrates all kinds of data-no matter where in the organisation it originates-into a single, accurate, updated body of information available to everyone, it can only work with ...