This book provides the business or IT professional with a practical
working knowledge of data modelling concepts and best practices,
along with how to apply these principles with ER/Studio DA. You
will build many ER/Studio DA data models along the way, applying
best practices to master these ten objectives: You will know why a
data model is needed and which ER/Studio DA models are the most
appropriate for each situation; You will be able to read a data
model of any size and complexity with the same confidence as
reading a book; You will know how to apply all the key features of
ER/Studio DA; You will be able to build relational and dimensional
conceptual, logical, and physical data models in ER/Studio DA; You
will be able to apply techniques such as indexing, transforms, and
forward engineering to turn a logical data model into an efficient
physical design; You will improve data model quality and impact
analysis results by leveraging ER/Studio DAs lineage functionality
and compare/merge utility; You will achieve enterprise architecture
through ER/Studio DAs repository and portal functionality; You will
be able to apply ER/Studio DAs data dictionary features; You will
learn ways of sharing the data model through reporting and through
exporting the model in a variety of formats; You will leverage
ER/Studio DAs naming functionality to improve naming consistency.
This book contains four sections: Section I introduces data
modelling and the ER/Studio DA landscape. Learn why data modelling
is so critical to software development and even more importantly,
why data modelling is so critical to understanding the business.
You will also learn about the ER/Studio DA environment. By the end
of this section, you will have created and saved your first data
model in ER/Studio DA and be ready to start modelling in Section
II. Section II explains all of the symbols and text on a data
model, including entities, attributes, relationships, domains, and
keys. By the time you finish this section, you will be able to read
a data model of any size or complexity, and create a complete data
model in ER/Studio DA. Section III explores the three different
levels of models: conceptual, logical, and physical. A conceptual
data model (CDM) represents a business need within a defined scope.
The logical data model (LDM) represents a detailed business
solution, capturing the business requirements without complicating
the model with implementation concerns such as software and
hardware. The physical data model (PDM) represents a detailed
technical solution. The PDM is the logical data model compromised
often to improve performance or usability. The PDM makes up for
deficiencies in our technology. By the end of this section you will
be able to create conceptual, logical, and physical data models in
ER/Studio DA. Section IV discusses additional features of ER/Studio
DA. These features include data dictionary, data lineage,
automating tasks, repository and portal, exporting and reporting,
naming standards, and compare and merge functionality.
General
Is the information for this product incomplete, wrong or inappropriate?
Let us know about it.
Does this product have an incorrect or missing image?
Send us a new image.
Is this product missing categories?
Add more categories.
Review This Product
No reviews yet - be the first to create one!
Welcome to Loot.co.za!
Sign in / Register |Wishlists & Gift Vouchers |Help | Advanced search
