You must answer BOTH of the following:A.Contrast the following terms (provide examples): Horizontal partitioning; vertical partitioningB.Select any one of the four ‘‘mega-vendors’’ or one of the six independent vendors from the PPT presentation. Use the Web to obtain additional information about this vendor and its BI tools. Prepare a review of this vendor and its BI tools, highlighting the strengths and weaknesses of this vendor..Need (2+2) Total 4 pages answer with APA format with citations and no plegarism.Weeks 5&6
Outline
• Capabilities of BI Solutions
•
Organizational Memory Capability
• Information Integration
• Insight Creation
• Presentation
• BI Vendors
4 Key Capabilities of BI Solutions
Organizational Memory Capability
• The ability to store information and knowledge
Information Integration
• The ability to link structured and unstructured data from a
variety of sources
Insight Creation
• The ability to develop new insights and use them in the shortterm or long-term to make better decisions
Presentation
• The ability to use appropriate reporting and balanced
scorecards tools, and thereby make BI more valuable to users
Technologies Enabling Organizational
Memory Capability
Enterprise Resource Planning (ERP)
• Refers to transactional systems that capture organizational memory
related to all business processes that the organization engages in
• Example: Order to cash captures all the transactions in an organization
Transactional Systems
• Capture all the relevant information for one accounting period (i.e.
month/quarter/year/etc.)
Data Warehouse
• Provides the source of data and information for business intelligence (BI)
analysis
Why Information Integration
Capability?
• Mutually disconnected, incompatible transactional
systems exist within an organization
• Data exists outside of transactional systems such
as e-mail, audio and video files, etc.
• A lot of relevant external data is available, such as
web sites, industry reports, expert opinions
• More complex decision making due to an increase
in the diversity of factors to consider
Technologies Enabling Insight Creation
Capabilities
Data mining
• Describe what happened or predict what will happen
Business analytics
• Discovery by using existing information
• Discovery by finding useful patterns in observations
Knowledge-modeling tool
• Decision trees, rule induction
Real time decision support
Why Insight Creation Capabilities?
• Need quick reflexes
•
Decisions must be made quickly to be competitive
• Domain complexity is increasing
•
Must consider information from diverse arenas
Why Presentation Capability?
Content and format needs differ
• Role
• Ex. Top executive interest in firm-level performance vs. customersupport personnel interest in aids that support real-time
responses to customers
• Task
• Ex. Customer-support specialist uses different information for
each task
• Preference
• Ex. Individuals differ: Big picture view vs details first
Technologies That Enable Presentation
Capability
Online Analytical Processing (OLAP)
• OLAP is used essentially to query the data warehouse
Visual Analytics
• Refers to the use of computer graphics to create a visual representation of
large collections of information
Performance Dashboards
• Measure performance
• Used for forecasting
Inputs and Outputs of the Four Business Intelligence
Capabilities
Users
Information presented in
user-friendly fashion and in
ways most appropriate for
the specific role, task, and
situation
Roles, tasks, and users’ inputs
regarding preferred nature of
presentation
Users’ inputs about the
analyses that may be
appropriate
Real-time data,
Unstructured Information,
External Information
Data, information, explicit
knowledge (mainly internal,
structured) stored in systems
as events occur
Presentation
Insight Creation
New insights and
information to support
learning and real-time
decision making
Synthesized information
about the past and present
(structured and
unstructured, external and
internal)
Information Integration
Organizational Memory
Historical information and
explicit knowledge
accumulated over time
(mainly structured and
internal)
Four BI Mega-Vendors
• Oracle (including Hyperion)
• SAP (including Business Objects)
• IBM (including Cognos and SPSS)
• Microsoft
Six Major Independent BI Vendors
• SAS
• Micro Strategy
• Information Builders
• TIBCO (including Spotfire)
• Qliktech
• Actuate
Physical Database Design and
Performance
Modern Database Management
Chapter 5
© 2011 Pearson Education, Inc. Publishing as Prentice Hall
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Objectives
•
•
•
•
•
•
•
•
Define terms
Describe the physical database design process
Choose storage formats for attributes
Select appropriate file organizations
Describe three types of file organization
Describe indexes and their appropriate use
Translate a database model into efficient structures
Know when and how to use denormalization
Chapter 5
© 2011 Pearson Education, Inc. Publishing as Prentice Hall
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Physical Database Design
• Purpose–translate the logical description of
data into the technical specifications for
storing and retrieving data
• Goal–create a design for storing data that will
provide adequate performance and insure
database integrity, security, and recoverability
Chapter 5
© 2011 Pearson Education, Inc. Publishing as Prentice Hall
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Physical Design Process
Inputs
Normalized
Volume
Decisions
relations
Attribute data types
estimates
Physical record descriptions
Attribute definitions
Response time
Data
expectations
security needs
Backup/recovery needs
Integrity expectations
DBMS
technology used
Chapter 5
(doesn’t always match
logical design)
Leads to
File
organizations
Indexes and
database
architectures
Query optimization
© 2011 Pearson Education, Inc. Publishing as Prentice Hall
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Figure 5-1 Composite usage map
(Pine Valley Furniture Company)
Chapter 5
© 2011 Pearson Education, Inc. Publishing as Prentice Hall
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Designing Fields
• Field: smallest unit of data in database
• Field design
– Decision #1: Choosing data type
•
•
•
•
•
•
•
Chapter 5
CHAR–fixed-length character
VARCHAR2–variable-length character (memo)
LONG–large number
NUMBER–positive/negative number
INEGER–positive/negative whole number
DATE–actual date
BLOB–binary large object (good for graphics, sound clips, etc.)
© 2011 Pearson Education, Inc. Publishing as Prentice Hall
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Field design decision #2: Coding,
compression, encryption
Code saves space, but costs
an additional lookup to
obtain actual value
Chapter 5
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Field design decision #3: Controlling
data Integrity
•
•
•
•
Default value–assumed value if no explicit value
Range control–allowable value limitations
(constraints or validation rules)
Null value control–allowing or prohibiting empty
fields
Referential integrity–range control (and null value
allowances) for foreign-key to primary-key matchups
Sarbanes-Oxley Act (SOX) legislates importance of financial data integrity
Chapter 5
© 2011 Pearson Education, Inc. Publishing as Prentice Hall
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Handling Missing Data
• Substitute an estimate of the missing value (e.g.,
using a formula)
• Construct a report listing missing values
• In programs, ignore missing data unless the value
is significant (sensitivity testing)
Triggers can be used to perform these operations
Chapter 5
© 2011 Pearson Education, Inc. Publishing as Prentice Hall
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Physical Records
• Physical Record: A group of fields stored in
adjacent memory locations and retrieved
together as a unit
• Page: The amount of data read or written in
one I/O operation
• Blocking Factor: The number of physical
records per page
Chapter 5
© 2011 Pearson Education, Inc. Publishing as Prentice Hall
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Denormalization
• Transforming normalized relations into non-normalized
physical record specifications
• Benefits:
– Can improve performance (speed) by reducing number of table lookups
(i.e. reduce number of necessary join queries)
• Costs (due to data duplication)
– Wasted storage space
– Data integrity/consistency threats
• Common denormalization opportunities
– One-to-one relationship (Fig. 5-3)
– Many-to-many relationship with non-key attributes (associative entity)
(Fig. 5-4)
– Reference data (1:N relationship where 1-side has data not used in any
other relationship) (Fig. 5-5)
Chapter 5
© 2011 Pearson Education, Inc. Publishing as Prentice Hall
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Figure 5-3 A possible denormalization situation: two entities with oneto-one relationship
Chapter 5
© 2011 Pearson Education, Inc. Publishing as Prentice Hall
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Figure 5-4 A possible denormalization situation: a many-to-many
relationship with nonkey attributes
Extra table
access
required
Null description possible
Chapter 5
© 2011 Pearson Education, Inc. Publishing as Prentice Hall
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Figure 5-5
A possible
denormalization
situation:
reference data
Extra table
access
required
Data duplication
Chapter 5
© 2011 Pearson Education, Inc. Publishing as Prentice Hall
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Partitioning
• Horizontal Partitioning: Distributing the rows of a table
into several separate files
– Useful for situations where different users need access to
different rows
– Three types: Key Range Partitioning, Hash Partitioning, or
Composite Partitioning
• Vertical Partitioning: Distributing the columns of a table
into several separate relations
– Useful for situations where different users need access to
different columns
– The primary key must be repeated in each file
• Combinations of Horizontal and Vertical
Partitions often correspond with User Schemas (user views)
Chapter 5
© 2011 Pearson Education, Inc. Publishing as Prentice Hall
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Partitioning (cont.)
• Advantages of Partitioning:
–
–
–
–
–
Efficiency: Records used together are grouped together
Local optimization: Each partition can be optimized for performance
Security: data not relevant to users are segregated
Recovery and uptime: smaller files take less time to back up
Load balancing: Partitions stored on different disks, reduces
contention
• Disadvantages of Partitioning:
– Inconsistent access speed: Slow retrievals across partitions
– Complexity: Non-transparent partitioning
– Extra space or update time: Duplicate data; access from multiple
partitions
Chapter 5
© 2011 Pearson Education, Inc. Publishing as Prentice Hall
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Horizontal Partitioning Methods
• Range partitioning
– Partitions defined by range of field values
– Could result in unbalanced distribution of rows
– Like-valued fields share partitions
• Hash partitioning
– Partitions defined via hash functions
– Will guarantee balanced distribution of rows
– Partition could contain widely varying valued fields
• Composite partitioning
– Combination of the other approaches
Chapter 5
© 2011 Pearson Education, Inc. Publishing as Prentice Hall
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Designing Physical Files
• Physical File:
– A named portion of secondary memory allocated for
the purpose of storing physical records
– Tablespace–named set of disk storage elements in
which physical files for database tables can be stored
– Extent–contiguous section of disk space
• Constructs to link two pieces of data:
– Sequential storage
– Pointers–field of data that can be used to locate
related fields or records
Chapter 5
© 2011 Pearson Education, Inc. Publishing as Prentice Hall
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File Organizations
• Technique for physically arranging records of a file on
secondary storage
• Factors for selecting file organization:
• Types of file organizations
– Sequential
– Indexed
– Hashed
Chapter 5
Sequential file Records of the file
are stored in
sequence by the
primary key field
values
If sorted – every
insert or delete
requires resort
If not sorted
Average time to find
desired record = n/2
© 2011 Pearson Education, Inc. Publishing as Prentice Hall
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Indexed File Organizations
• Indexed File Organization: the storage of records either
sequentially or nonsequentially with an index that allows
software to locate individual records
• Index: a table or other data structure used to determine in
a file the location of records that satisfy some condition.
• Primary keys are
automatically indexed
• Other fields or
combinations of fields
can also be indexed;
these are called
secondary keys
uses a tree search
Average time to find desired
record = depth of the tree
Chapter 5 © 2011 Pearson Education, Inc. Publishing as Prentice Hall
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Hashed file
organization
Hash algorithm
Usually uses divisionremainder to determine
record position. Records
with same position are
grouped in lists.
Bitmap index index
organization
Bitmap saves on
space requirements
Chapter 5
Rows – possible values of the
attribute
Columns – table rows
Bit indicates whether the attribute
of a row has the values
© 2011 Pearson Education, Inc. Publishing as Prentice Hall
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Join Indexes–speeds up join operations
a) Join index for matching foreign
key (FK) and primary key (PK)
a) Join index
for common
non-key
columns
Chapter 5
© 2011 Pearson Education, Inc. Publishing as Prentice Hall
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Clustering Files
• In some relational DBMSs, related records from
different tables can be stored together in the same
disk area
• Useful for improving performance of join operations
• Primary key records of the main table are stored
adjacent to associated foreign key records of the
dependent table
• e.g. Oracle has a CREATE CLUSTER command
Chapter 5
© 2011 Pearson Education, Inc. Publishing as Prentice Hall
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Rules for Using Indexes
1. Use on larger tables
2. Index the primary key of each table
3. Index search fields (fields frequently in
WHERE clause)
4. Fields in SQL ORDER BY and GROUP BY
commands
5. When there are >100 values but not when
there are
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