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En pratiqueInscriptions Designers of data warehouses.
Basic understanding of relational database systems is required (see RDBMS concepts).
The theory will be illustrated by exercises. As the number of attendees is limited, all students will be individually coached during these exercises. Furthermore, an extra instructor will be present when needed. In this way, everyone will get optimal benefit from this course, even if there are differences in the background of the students.
Harm van der Lek.
3 days.
| date | langue | lieu | prix | remarques |
| 06/03/2012 | N | Hilversum | 1890 EUR | |
| 05/06/2012 | N | Hilversum | 1890 EUR |
For the design of data structures of a data warehouse, star scheme techniques are becoming more important every day. This course treats dimensional modeling in detail, including the latest developments (e.g. data vault of Dan Lindstedt).
What is dimensional modeling? • Why a star scheme? • relational versus multidimensional databases • facts table, dimension tables • dimensions: causal, heterogeneous, monster, mini, degenerated • normalisation, denormalisation, snowflake schemes • pure star scheme versus snapshot.
Detail versus analytic attributes • mutations in dimensions, type 0 to 5 approach • minidimensions and history • transaction orientation versus state orientation • scheme changes through time
The One Attribute Set Interface • technical versus user dimensions • join navigation, aggregate navigation • OASI and heterogeneous dimensions
DWH-Blueprint, evolutionary development • conform dimensions • sample - snapshot - adapting a star scheme • OLAP design • approach for dimensional modeling • starfinding
Bridge tables • complex hierarchies • star schemes and meta-data • extraction, cleansing, transformation and loading
Middleware • protection against 'runaway' queries • OLAP tools • report tools