What are the 4 key capabilities of BI solutions?

  

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 citationsand 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
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Physical Database Design
Purposetranslate the logical description of
data into the technical specifications for
storing and retrieving data
Goalcreate a design for storing data that will
provide adequate performance and insure
database integrity, security, and recoverability
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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
(doesnt always match
logical design)
Leads to
File
organizations
Indexes and
database
architectures
Query optimization
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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

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Chapter 5
CHARfixed-length character
VARCHAR2variable-length character (memo)
LONGlarge number
NUMBERpositive/negative number
INEGERpositive/negative whole number
DATEactual date
BLOBbinary large object (good for graphics, sound clips, etc.)
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Field design decision #2: Coding,
compression, encryption
Code saves space, but costs
an additional lookup to
obtain actual value
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Field design decision #3: Controlling
data Integrity

Default valueassumed value if no explicit value
Range controlallowable value limitations
(constraints or validation rules)
Null value controlallowing or prohibiting empty
fields
Referential integrityrange control (and null value
allowances) for foreign-key to primary-key matchups
Sarbanes-Oxley Act (SOX) legislates importance of financial data integrity
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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
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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
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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)
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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
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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
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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)
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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
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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
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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
Tablespacenamed set of disk storage elements in
which physical files for database tables can be stored
Extentcontiguous section of disk space
Constructs to link two pieces of data:
Sequential storage
Pointersfield of data that can be used to locate
related fields or records
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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
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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
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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
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Join Indexesspeeds up join operations
a) Join index for matching foreign
key (FK) and primary key (PK)
a) Join index
for common
non-key
columns
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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
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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

Introduction:

Business Intelligence (BI) solutions help organizations in making better business decisions by analyzing data and providing insights. BI has four key capabilities which are Organizational Memory Capability, Information Integration, Insight Creation, and Presentation. Each capability is important in its own way and enables organizations to manage their data effectively and make better decisions. In order to use BI effectively, it is important to understand each capability and how they work together.

Description:

This content focuses on the four key capabilities of BI solutions and the technologies that enable them. The first capability is organizational memory capability which enables organizations to store information and knowledge. Enterprise Resource Planning (ERP) and Data Warehouse are two important technologies that enable this capability. The second capability is information integration which allows organizations to link structured and unstructured data from various sources. In addition to transactional systems, data mining and business analytics are important technologies that enable this capability.

The third capability is insight creation which enables organizations to develop new insights and use them in short-term or long-term decision making. Decision trees, rule induction, and real-time decision support are technologies that enable this capability. The fourth and final capability is presentation which allows organizations to present data and insights in a user-friendly way. Online Analytical Processing (OLAP), visual analytics, and performance dashboards are the technologies that enable this capability.

In order to make the most of BI solutions, organizations must take advantage of all four capabilities. Each capability is important in its own way and together they enable organizations to manage their data, gain insights, and make better decisions. It is also important to use the appropriate technologies that enable each capability.

Contrast of terms:

A. Horizontal Partitioning and Vertical Partitioning are two different concepts used in Database Management Systems to improve database performance. Horizontal partitioning divides the table by rows while vertical partitioning divides the table by columns. Example of horizontal partitioning includes partitioning customers table based on geographic location while an example of vertical partitioning includes partitioning a table based on frequently queried columns.

B. Review of Microsoft – Microsoft Power BI

Microsoft Power BI is a cloud-based business analytics tool that provides data analysis and visualization in a user-friendly way. It is one of the leading BI tools in the market. Strengths of Power BI include its ease of use and integration with various data sources. Power BI can connect to many different data sources such as Excel spreadsheets, SQL Server databases, and cloud-based data sources. This makes it easy for businesses to connect and integrate data from different sources.

Power BI also offers a wide range of visualizations and analytics features that allow businesses to analyze data in flexible and compelling ways. Power BI dashboards and reports are very customizable and all of its features can be accessed within a web browser or mobile app.

Its weakness includes its limited modeling and transformation capabilities compared to other BI tools. Additionally, Power BI’s data visualization and report formatting capabilities, when compared to competitor products, lack the high-quality design elements.

Overall, Microsoft Power BI is a powerful BI tool that offers an easy-to-use interface and great integration with various data sources. However, its modeling and transformation capabilities need improvement in order to provide customers with a comprehensive BI solution.

Objectives:

– To understand the differences and similarities between horizontal and vertical partitioning.
– To analyze and evaluate the strengths and weaknesses of a chosen vendor and its BI tools.

Learning Outcomes:

– Students will be able to distinguish between horizontal and vertical partitioning, and provide examples for each.
– Students will be able to identify and explain the capabilities of BI solutions, including organizational memory, information integration, insight creation, and presentation.
– Students will be able to evaluate a chosen vendor and its BI tools, based on additional research and analysis, and evaluate its strengths and weaknesses.

Contrasting Horizontal and Vertical Partitioning:

Horizontal partitioning, also known as sharding, is a database design technique that involves splitting up a large database into smaller, more manageable parts or shards. Each shard is stored in a separate database server, which can be distributed across different physical locations. This technique is useful for scaling horizontally, as it allows for efficient access to large databases. For example, a social media platform may use horizontal partitioning to store user data based on geographical regions.

On the other hand, vertical partitioning is a technique that involves dividing a database into vertical partitions or tables based on specific columns or attributes. This technique is useful for scaling vertically, as it allows for efficient access to specific data sets within a large database. For example, a hospital may use vertical partitioning to store patient data in different tables based on their medical history, diagnosis, and treatment.

Review of a BI Vendor – Microsoft Power BI:

Microsoft Power BI is a cloud-based business analytics service that enables organizations to visualize and analyze data with greater ease and speed. One of the strengths of Power BI is its integration with other Microsoft products, such as Excel, SharePoint, and Dynamics 365. This integration allows for easy data sharing and collaboration across different platforms.

Another strength of Power BI is its ease of use and flexibility. The service offers a wide range of visualizations, customizations, and dashboard options, which can be tailored to specific industry needs and business objectives. Additionally, Power BI offers a seamless transition between desktop and mobile devices, making it easier for users to access and share information on-the-go.

However, a potential weakness of Power BI is its limited data storage capacity. Although the service allows for connecting to multiple data sources, including cloud-based services such as Google Analytics and Salesforce, it has a limit of 1 GB for its data model and 10 GB for its data capacity. This limitation may be a challenge for organizations with large and complex data sets.

Another potential weakness of Power BI is its limited data cleansing and transformation options. Although the service has built-in data cleansing and transformation tools, they may not be sufficient for complex data sets with multiple data sources and formats. Users may need to rely on third-party tools or hire external data specialists to ensure proper data cleansing and transformation.

In conclusion, Microsoft Power BI is a powerful and user-friendly BI tool that offers a wide range of visualization and customization options, as well as seamless integration with other Microsoft products. However, its limited data storage capacity and data cleansing and transformation options may be potential challenges for organizations with complex data sets.

Solution 1: Contrasting Horizontal Partitioning and Vertical Partitioning

Horizontal partitioning and vertical partitioning are two techniques used in creating system architectures for database management. Horizontal partitioning is the process of distributing data across tables to smaller chunks or subsets. This ensures that different parts of the data are housed in different physical spindles, which improves the system’s performance. Horizontal partitioning is useful in situations where there is a need to improve data retrieval speeds, especially in large data-intensive applications.

On the other hand, vertical partitioning is a process of breaking a table into smaller chunks by separating columns, usually based on how often they are accessed. This technique is used mainly in apps where some columns are used more frequently than others, and separating them reduces the processing time required for queries. The major advantage of vertical partitioning is that data retrieval is faster since data is stored separately according to their frequency of use.

Solution 2: Review of Microsoft BI Tools

Microsoft is one of the world’s leading BI vendors, offering a comprehensive suite of BI tools, which include Power BI, Azure Stream Analytics, and Microsoft Excel. The following is a review of these BI tools.

Strengths of Microsoft BI Tools:

1. User-Friendly: Microsoft BI Tools are easy to learn and user-friendly, which makes it easier for users of all levels to understand how they work.

2. Integration with Other Microsoft Tools: Microsoft BI tools integrate easily with other Microsoft tools like Office, SharePoint, and Azure, maximizing overall productivity and leading to cost benefits.

3. Multi-Source Compatibility: Microsoft BI tools are designed to be used with numerous data sources, including cloud-based data storage.

Weaknesses of Microsoft BI Tools:

1. Limited Report Formatting: Microsoft BI reporting features have limited report customization options when compared to other reporting systems like Crystal Reports.

2. Premium Pricing: Microsoft BI tools tend to have higher price points in comparison with other BI tools available in the market.

3. Limited Connectivity: While Microsoft BI tools can work well with other Microsoft tools, they have limited interoperability with non-Microsoft applications.

In conclusion, Microsoft BI Tools are user-friendly, feature-rich, and easy to integrate with other Microsoft tools. However, they have limited customization options for reports, and they can be expensive for small and medium enterprises. Nevertheless, Microsoft BI Tools remain excellent choices for businesses that are already using other Microsoft products.

Suggested Resources/Books:

– Business Intelligence Guidebook: From Data Integration to Analytics by Rick Sherman
– The Data Warehouse ETL Toolkit: Practical Techniques for Extracting, Cleaning, Conforming, and Delivering Data by Ralph Kimball and Joe Caserta
– Business Analytics for Managers: Taking Business Intelligence Beyond Reporting by Gert Laursen and Jesper Thorlund

Similar Asked Questions:

1. What is the difference between data integration and data warehousing?
2. How can business analytics help with real-time decision making?
3. What are some common performance metrics used in BI dashboards?
4. How can data mining be used to create new insights?
5. What are some best practices for designing user-friendly BI reports?

Contrasting Horizontal and Vertical Partitioning:

Horizontal partitioning, also known as sharding, involves dividing a database into multiple smaller databases that contain subsets of data based on a common attribute, such as customer location. This allows for faster data retrieval and improved scalability. However, it can also lead to data inconsistency and greater complexity in data management.

Vertical partitioning involves dividing a database into multiple tables that contain subsets of columns based on their access frequencies. For example, frequently accessed columns such as customer names and IDs can be placed in a separate table for faster retrieval, while less frequently accessed columns such as customer addresses can be placed in another table. This can also improve data retrieval performance, but can lead to more complex queries and greater storage requirements.

Review of Microsoft Power BI:

Microsoft Power BI is a popular BI tool that allows users to create custom dashboards, reports, and visualizations. It integrates with a variety of data sources, including Excel spreadsheets, cloud-based services such as Salesforce and Google Analytics, and on-premises databases. Power BI also offers natural language processing, which allows users to ask questions in plain language and receive relevant data visualizations in response.

Strengths of Power BI include its ease of use, flexibility in creating custom reports and dashboards, and its integration with other Microsoft products such as Excel and SharePoint. It also offers a large selection of pre-built templates and visualizations to facilitate report creation.

Weaknesses of Power BI include its limited functionality for large-scale data analysis and modeling, and its dependency on other Microsoft products for full integration. Its pricing model can also be complex for organizations with larger data volumes.

Overall, Microsoft Power BI is a powerful and flexible tool for organizations of all sizes looking to improve their data analysis and reporting capabilities. Its ease of use and integration with other Microsoft products make it a popular choice for many users. However, it may not be the best fit for organizations with extremely large data volumes or complex analytical needs.

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