By: Meisam Nazariani Professor: A. Abdollahzadeh Amir Kabir University Of Technology Computer...
Click here to load reader
prev
next
of 22
By: Meisam Nazariani Professor: A. Abdollahzadeh Amir Kabir University Of Technology Computer Engineering and Information Technology Faculty AUT - Business
By: Meisam Nazariani Professor: A. Abdollahzadeh Amir Kabir
University Of Technology Computer Engineering and Information
Technology Faculty AUT - Business Intelligence - Meisam Nazariani 1
Meta Data Repository Analysis Business Intelligence Road Map 11
December 2009
Slide 2
This Chapter Covers The Following Topics: AUT - Business
Intelligence - Meisam Nazariani 2 Things to consider when analyzing
whether to license (buy) or build a meta data repository Why it is
important to deliver meta data with every BI project The
differences between the two categories of meta data: business meta
data and technical meta data How a meta data repository can help
business people find and use their business data The four groupings
of meta data components: ownership, descriptive characteristics,
rules and policies, and physical characteristics 11 December
2009
Slide 3
This Chapter Covers The Following Topics: AUT - Business
Intelligence - Meisam Nazariani 3 How to prioritize meta data for
implementation purposes Five common difficulties encountered with
meta data repository initiatives: technical, staffing, budget,
usability, and political challenges The entity-relationship (E-R)
meta model used to document the meta data requirements A definition
and examples of meta-meta data Brief descriptions of the activities
involved in meta data repository analysis, the deliverables
resulting from those activities, and the roles involved The risks
of not performing Step 7Step 7 11 December 2009
Slide 4
Things to Consider: AUT - Business Intelligence - Meisam
Nazariani 4 Meta Data Repository Usage Meta Model Requirements Meta
Data Repository Security Meta Data Capture Meta Data Delivery
Staffing 11 December 2009
Slide 5
Meta Data Repository Definition: AUT - Business Intelligence -
Meisam Nazariani 5 A meta data repository is a database. But unlike
ordinary databases, a meta data repository is not designed to store
business data for a business application. Instead, it is designed
to store contextual information about the business data. 11
December 2009
Slide 6
Contextual Information About Business Data: AUT - Business
Intelligence - Meisam Nazariani 6 Examples of contextual
information about business data include the following: Meaning and
content of the business data Policies that govern the business data
Technical attributes of the business data Specifications that
transform the business data Programs that manipulate the business
data 11 December 2009
Slide 7
Some Important Characteristics Of Meta Data: AUT - Business
Intelligence - Meisam Nazariani 7 A meta data repository is
populated with meta data from many different tools, such as CASE
tools, ETL tools, OLAP tools, and data mining tools. Meta data
documents the transformation and cleansing of source data and
provides an audit trail of the periodic data loads. Meta data helps
track BI security requirements, data quality measures, and growth
metrics (for data volume, hardware, and so on). Meta data provides
an inventory of all the source data that populates the BI
applications. Meta data can be centrally managed, or it can be
distributed. Either way, each instance of a meta data component
should be unique, regardless of its physical location. 11 December
2009
Slide 8
Meta Data Categories: AUT - Business Intelligence - Meisam
Nazariani 8 1. Business meta data provides business people with a
roadmap for accessing the business data in the BI decision-support
environment. 2. Technical meta data supports the technicians and
"power users" by providing them with information about their
applications and databases, which they need in order to maintain
the BI applications. 11 December 2009
Slide 9
Meta Data Repository as a Navigation Tool: AUT - Business
Intelligence - Meisam Nazariani 9 11 December 2009
Slide 10
Groupings of Meta Data Components: AUT - Business Intelligence
- Meisam Nazariani 10 11 December 2009
Slide 11
Meta Data Usage By Business People: AUT - Business Intelligence
- Meisam Nazariani 11 11 December 2009
Slide 12
Meta Data Usage By Business People: AUT - Business Intelligence
- Meisam Nazariani 12 11 December 2009
Slide 13
Prioritization Of Meta Data Components: AUT - Business
Intelligence - Meisam Nazariani 13 11 December 2009
Slide 14
Meta Data Repository Challenges: AUT - Business Intelligence -
Meisam Nazariani 14 11 December 2009
Slide 15
Example of Meta Data in a BI Query: AUT - Business Intelligence
- Meisam Nazariani 15 11 December 2009
Slide 16
The Logical Meta Model: AUT - Business Intelligence - Meisam
Nazariani 16 11 December 2009
Slide 17
Meta-Meta Data: AUT - Business Intelligence - Meisam Nazariani
17 Since meta data is the contextual information about business
data, meta-meta data is the contextual information about meta data.
Many components of meta-meta data are similar to those of meta
data. For example, every meta data object should have components
that cover name, definition, size and length, content, ownership,
relationship, business rules, security, cleanliness, physical
location, applicability, timeliness, volume, and notes. 11 December
2009
Slide 18
Meta Data Repository Analysis Activities: AUT - Business
Intelligence - Meisam Nazariani 18 1. Analyze the meta data
repository requirements. 2. Analyze the interface requirements for
the meta data repository. 3. Analyze the meta data repository
access and reporting requirements. 4. Create the logical meta
model. 5. Create the meta-meta data. 11 December 2009
Slide 19
Meta Data Repository Analysis Activities: AUT - Business
Intelligence - Meisam Nazariani 19 11 December 2009
Slide 20
Deliverables Resulting from These Activities: AUT - Business
Intelligence - Meisam Nazariani 20 1.Logical meta model This data
model is a fully normalized E-R diagram showing kernel entities,
associative entities, characteristic entities, relationships,
cardinality, optionality, unique identifiers, and all attributes
for meta data repository objects. 2.Meta-meta data The meta data
entities and attributes from the logical meta model must be
described with meta data. Meta dataspecific meta data components
(meta-meta data) are meta data names, meta data definitions, meta
data relationships, unique identifiers, types, lengths, domains,
business rules, policies, and meta data ownership. 11 December
2009
Slide 21
Roles Involved in These Activities: AUT - Business Intelligence
- Meisam Nazariani 21 Data administrator Meta data administrator
Subject matter expert 11 December 2009
Slide 22
Risks of Not Performing Step 7: AUT - Business Intelligence -
Meisam Nazariani 22 Without meta data, the business people would
have a difficult time understanding and using the transformed data
in the BI target databases. It would be as frustrating as aimlessly
driving a car for weeks or months without a map, guessing your way
to your destination. Once the business people perceive the BI
application as difficult to use or they think the BI data is
unreliable because it no longer matches the source data in the
operational systems, they could label the BI decision- support
initiative a failure. 11 December 2009