Business Intelligence Module 5

Business intelligence (BI) platforms enable enterprises to build BI
applications by providing capabilities in three categories: analysis, such
as online analytical processing (OLAP); information delivery, such as
reports and dashboards; and platform integration, such as BI metadata
management and a development environment.
In simple words, A business intelligence (BI) platform is technology that
helps businesses gather, understand, and visualize their data. It serves
as the backbone of a company’s business intelligence strategy, which is
how a company uses information to make better decisions.

The Business Intelligence (BI) Platform Capability Matrix sets the
technical details of the BI Platform Capabilities and also valuates the
leading BI platform products based on the technical capabilities. The
matrix serves as a high-level guide to understand the technical
capabilities of each vendor’s shipping products. Beyond the vendor
selection, the capability matrix is basically used as an architectural
guide to what should be included in a comprehensive and well-
balanced BI platform. Organizations should decide the capabilities
that are required based on the requirements.

There are 12 capabilities in BI platform and can be divided into integration,
information delivery and analysis.

Presently, in BI platform more concentration is on information delivery
but the analysis and integration also play an important role in BI
deployments. Organizations must boost their analysis capabilities to
discover new insights which will lead to competitive differentiation and
performance improvement. The BI platforms should improve their
analysis capabilities to find out new insights that can lead to
competitive differentiation and performance improvement.
It should also improve its integration capabilities to put together the
analytical insights back into the business at both the strategic and
process level. The Information delivery capabilities will always be
required to inform the stakeholders to allow them to constantly
monitor the performance of the business and also take corrective
action when the actual values are different from the projected goals.
Only the combination of all the three capability categories (integration,
information delivery and analysis) can build a platform which can
deliver BI pervasively to the business.

1. Information Delivery
There are four BI platform capabilities in the information delivery
category which are reports, dashboards, ad hoc query and Microsoft
Office Integration. User organizations are investing heavily in all of
these four capabilities which are pulling many vendors including the
nontraditional BI vendors into the space.
a. Reports: This capability allows the creation of formatted and
interactive reports with extremely scalable distribution and scheduling
capabilities. Finally, this capability should help in easy to search and
also navigate the information in the report, as well as the repository of
reports.

b. Dashboards: Dashboards gives a positive or negative trend indicator and a
colour-coded summary which shows the state of each metric compared to an
established aim or threshold. The end users should be able to create their own
performance metrics. Real-time update of the dashboards to reflect the events
or the scheduled updates to the metrics is vital for the BI applications to focus
on the operational tasks. Finally, the dashboards should allow the difficult
alerts and notifications based not just on one metric but on groups of related
metrics.
c. Ad Hoc Query: This capability allows the end users to build their own reports
by asking for ad hoc queries. Conventionally, the ad hoc query capability has
been limited to just the data warehouse but, increasingly, ad hoc queries will be
aimed at a broader set of sources. Performance is a main issue for the users
performing ad hoc queries. Hence, the BI platforms that give this capability
should fulfill many requirements to improve the query performance which
includes aggregate awareness, caching, multi-pass SQL, query governance,
performance auditing and native SQL commands.

d. Microsoft Office Integration: In many deployments, the BI platform
is used at the middle tier (application tier) to manage, secure and also
execute the BI tasks. In Microsoft Office, Excel acts as the BI client.
Some of the BI platforms include other Office applications, such as the
Word and the PowerPoint. The advanced functionality includes the
ability to prepare new reports in Microsoft Office which can be saved
back to the middle tier BI server, and the ability to centrally control and
secure the BI documents in Office.
[Caching - storing data for future use
multi-pass SQL enables the users to create more complex reports, and
have more flexibility in answering business questions on the reports.]

Integration
There are four BI platform capabilities in the integration category. They are
infrastructure, metadata, development, and workflow and collaboration. Of all
the BI platform capability categories, this is the least mature. Most of the BI
platform vendors do a reasonable job of giving an integrated infrastructure,
including the security, metadata and administration tools, but some vendors
with an aggressive acquisition strategy will find it difficult to maintain. Most of
the BI metadata is used as a semantic layer for self-service reporting. BI
metadata must play a bigger role in standardizing the dimensions, hierarchies,
measures and performance metrics across the organization. However, the BI
metadata must talk to more applications than just that same vendor’s reporting
tools. The development environment must go beyond the programmatic
Software Development Kits (SDKs) to include more visual development
functionality and more dependence on Web services. Finally, as the BI becomes
more process driven, the BI platforms will require better integration with
workflow and collaboration offerings.

[Semantic layer maps complex data into familiar business terms so that users
across the enterprise can access the same source of truth, with full confidence
in its integrity]
a. Infrastructure: To assess this category, each BI platform has to be integrated,
including the common security, metadata, administration, portal integration,
object model, query engine and also shared look- and-feel. The real litmus test
for the tightly integrated infrastructure is the capability to deploy all the BI
functionality with a single installation.
b. Metadata: Strong metadata is the vital capability of a BI platform. Not only
should all the tools leverage the same metadata, but the offering should also
give a strong way to capture, store, re use and publish the metadata objects. To
assess a BI platform’s capability in this area, analysts look for a single repository
for different types of BI metadata, which includes the dimensions, hierarchies,
measures, performance metrics and report design objects.

c. Development: The BI platform should give a set of programmatic development tools, along with a
Software Developer’s Kit, to build the BI applications and also integrate them into a business
process and put them in another application. In addition, the BI platform should allow the
developers to build the BI applications without coding by using wizards and drag-and-drop tools for
a graphical assembly process. The development environment should also support the Web services
to do common tasks such as scheduling, delivery, administration and management.
d. Workflow and Collaboration: This capability allow the BI users to both share and discuss the
information through the public folders or the discussion threads, and also integrate the BI results
within the context of a particular business process. With the help of this capability, the BI
application can assign and track events or tasks given to particular users. Often, this capability is
provided by integration with a separate portal or workflow tool. The analysts evaluate each BI
platform’s ability to activate a task-specific to the workflow based on the outcome of the BI-
generated data. The ease with which the users can build and edit the business rules to automate
the workflow was a major requirement.

3. Analysis: There are four BI platform capabilities present in the
analysis category. They are OLAP, predictive modeling, scorecards and
visualization. To date, the enormous majority of the organizations focus
on just the OLAP capability. But with the increasing interest in the
process- and strategy-driven BI, the need for predictive modeling and
scorecards will also increase. Predictive modeling is required to
determine in before hand the outcome of different business events.
This information when used rightly can promote better planning and
optimize the business processes.

a. OLAP: This capability allows the end users to analyze the data with
extremely fast query and calculation, performance, allowing a style of
analysis known as "slice and dice." This capability can span a range of
storage architectures for example, relational, multidimensional and in-
memory. The analysts look for the capability of the users to easily
define the functions and add or edit the dimension members. The BI
platforms also checked the capability to execute sophisticated sorting
or ranking, alternate hierarchies, inter-row calculations, asymmetric
hierarchies and drilling down on measures. Performance attributes,
such as the capability to perform Relational OLAP (ROLAP) calculations,
where the in-memory aggregations and trickle feed cube loading are
also examined.

b. Visualization: This capability allows the different aspects of the data
to be displayed more efficiently by using interactive pictures and charts
instead of the rows and columns. BI platforms were assessed on the
ability to project multidimensional data in a two-dimensional screen
with the help of the size, shape and colour of objects to show
dimensionality. The capability to project data onto any physical design
surface such as a physical store, airplane or stadium can also be
examined. Finally, the analysts look for BI platforms that give a wide
range of chart types beyond the basic bar and pie charts, to include the
chart types such as the heat maps and the geographic maps. Credit can
be given to the BI platforms that allowed easy interactivity with the
charts.

c. Predictive Modeling and Data Mining: This capability allows the organizations to separate the
categorical variables and also estimate the continuous variables using the advanced mathematical
techniques. Most of the BI platforms can give basic comparative statistics. The analysts assessed the BI
platforms on the capability to build predictive models based on the more sophisticated algorithms
performing the analysis such as:
o Forecasting
o Classification
o Attribute importance
o Clustering
o Affinity analysis
o Optimization
The BI platforms were assessed on the capability to handle a predictive modeling Environment which
includes:
o Experimental design o Data transformations
o Model management o Model assessment
o Real-time/batch scoring.

d. Scorecards: This capability takes the metrics displayed in the dashboard a
step further by applying them to the strategy map which aligns the key
performance metrics with the success of the strategic objectives. However, the
scorecard involves the use of a performance management methodology such as
the "balanced scorecard" framework or the Six Sigma. The analysts assessed the
BI platforms on the capability to design the strategy maps, support the common
scorecard methods, apply the performance management methodologies,
encourage the association about the performance metrics, and summaries,
display, and group the performance metrics. Most of the vendors with a
scorecard product were able to meet all the demands requested. Some of the
vendors without a formally designated scorecard product were able to show
some scorecard functionality with the reporting and dashboard products.

BI Target database
Operational Database
Operational database is designed to prevent the storage of the same data attributes in multiple
places and thus avoid the update anomalies caused by redundancy. Designing normalized database
structures is key for developing relational databases. Normalization ensures that the data is created,
stored, and modified in a consistent, nonredundant way.
Operational Databases versus BI Target Databases
Operational Databases
Geared toward eliminating redundancy, coordinating updates, and repeating the same types of
operations many times a day, every day (for example, airline reservations, deposits and withdrawals
from bank accounts, hotel room reservations ).
BI Target Databases
Geared toward supporting a wide range of queries and reports. Queries and reports may vary from
one business analyst to another or from one department to another. All of the queries and reports
may not run on the same day and may not run every day (for example, quarterly trend analysis
reports on regional sales, monthly order fulfillment report).

OD - Most of the transactional systems require subsecond response time.
TD - Although response time is important, subseconds cannot be expected. Typical response times
are seconds, minutes, or hours.
OD - Highly normalized to support consistent updates and maintenance of referential integrity.
TD - Highly denormalized to provide quick retrieval of a wide range and a large amount of data. Data
that belongs together from an analytical reporting perspective is usually stored together.
OD - Store very little derived data. Data is usually derived dynamically when needed.
TD - Store large amounts of derived data. This saves time for the queries and reports.
OD - Do not store historical data. Historical records are archived.
TD - Store large amounts of historical data, often at some level of summarization, but just as often
at a detailed level.
OD - Lightly summarized, mostly for reporting purposes.
TD - Many levels of precalculated, summarized data, from lightly summarized to highly summarized.

BI target databases are designed for simplified, high-performance data
retrieval.
Basic assumptions for designing BI target databases are listed below.
- Data is stored in such a manner that it is readily accessible in ways
that are of interest to the business people.
- The design is driven by access and usage.
- A normalized design is not necessarily intuitive for a business person
and could therefore become quite complex.
- No BI data can be invented! All data in the BI target databases must
exist in or be derivable from current internal or external operational
data sources.

Data mart
Data mart is a database which has the same characteristics as that of a
data warehouse, and is usually smaller and is focused on the data for
one division or one workgroup within an enterprise.
There are three different views of the place of the data mart in the
world of data warehousing.
· Specialized data marts are created with a subset of the information in
the data warehouse. These are easier to use because they only have
the specific information that the specific user group will require. The
use of many data marts allows the querying load to be spread among
the various computers. This can minimize the network traffic.

· Free-standing data marts are developed, independent from the data warehouse. The
information for the data mart might come from just one legacy system and is faster and
cheaper to develop a different data mart instead of building an enterprise-wide data
warehouse with the data marts got from it. The drawback of the solution is that the
company’s data will not be integrated and thus violates one of the Bill Inmon’s original
defining features of the data warehouse. If various separate data marts are built using the
strategy, then it will usually contain data that is duplicated and inconsistent.
· The data mart is the prototype or the first step in the data warehousing process. An
enterprise picks the division or the group that would benefit most from the data-based
knowledge. A data mart is built with the group’s data. The additional type of information is
added to the data mart as the time goes on until it is turned into the data warehouse.
Data mart possibly has a marketing advantage over data warehouse. The entire data
warehousing process is about creating data-based knowledge and bring that knowledge to
people. A warehouse is a place where things are kept away. A mart is a suitable place to
buy something. Most of the data warehousing professionals include quick access to the
information as a defining feature of the term ‘data warehouse’.

BI Products and Vendors
BUSINESS INTELLIGENCE (BI) tools are software that collects,
transforms, presents data to help decision-makers drive business
growth. BI tools ingest large amounts of structured and unstructured
data from varied sources, transform it and help deduce actionable
business insights from the data.
Top BI products with features are given below.

1) Zoho Analytics
Zoho Analytics is a self-service business intelligence and analytics
platform. It allows users to create insightful dashboards and visually
analyze any data in minutes. It features an AI powered assistant that
enables users to ask questions and get intelligent answers in the form of
meaningful reports.
Key Features:
• 100+ readymade connectors for popular business apps, cloud drives and
databases.
• Wide variety of visualization options--charts, pivot tables, summary
views, KPI widgets and custom themed dashboards.
• Unified business analytics for analyzing data from across business apps.
• Augmented analytics using AI, ML and NLP.
• White label BI portals and embedded analytics solutions

2) Yellowfin BI:
Yellowfin is a business intelligence platform. It is a single integrated
solution developed for companies across varying industries. It also makes
it easy to assess, monitor and understand data.
Features:
• Access dashboards from anywhere: web page, company intranet, wiki,
or mobile device
• Mapping mobile BI like features helps user to access and monitor
business-related data
• It allows faster, smarter collective decision-making.
• User's insights can be made effective through data-rich presentations
and interactive reports
• This BI tool also supports business decision-making process

3) Clear Analytics:
Clear Analytics is an accurate, timely and clear business insights system. This
business intelligence tool helps to fulfill business needs. This BI tool provides easy
extraction of large data from reliable sources and presents it in the form of
professional reports.
Features:
• It provides software solutions that require less human resources
• Dashboard creation
• Graphical data presentation
• Key Performance Indicators
• Easy Indication of issues
• Helps to create strategic planning
• It offers predictive analysis

4) BiG EVAL
BiG EVAL is a comprehensive suite of software tools aimed for leveraging the value of
enterprise data by continuously validating and monitoring quality. It automates testing
tasks during report and analysis development and provides quality metrics in
production.
Features:
• Data Quality Measuring and Assisted Problem Solving.
• Autopilot testing for agile development of analytical data models, datamarts and
data warehouses.
• High performance in-memory scripting and rules engine.
• Abstraction for any kind of data (RDBMS, APIs, Flatfiles, Business applications cloud /
on-premises).
• Clear dashboards and alerting processes.
• Embeddable into DevOps CI/CD flows, ticket systems and more.

5) SAP BUSINESS INTELLIGENCE:
SAP BI is an integrated business Intelligence software. It is an enterprise level
application for open client/server systems. It has set new standards for providing the
best business information management solutions.
Features:
• It provides highly flexible and most transparent business solutions
• The application developed using SAP can integrate with any system
• It follows modular concept for the easy setup and space utilization
• Allows to create next-generation database system that combines analytics and
transactions
• Provide support for On-premise or cloud deployment
• Simplified data warehouse architecture
• Easy Integration with SAP and non-SAP applications

6) MicroStrategy:
MicroStrategy is an enterprise analytics software. It empowers people to make better decisions and
transform the way they do business. It offers most advanced and predictive analytics.
Features:
• Advanced and predictive analytics
• Business intelligence
• Easy to use and maintain
• High-performance business intelligence
• Self-service analytics
• Big data solutions
• Software as a service (SaaS)
• Real-time WYSIWYG report design
• Scorecards and dashboards
• Enterprise reporting

7) BOARD:
Board is a Management Intelligence Toolkit. It combines features of business
intelligence and corporate performance management. It is designed to deliver
business intelligence and business analytics in a single package.
Features:
• Analyse, simulate, plan and predict using a single platform
• To build customized analytical and planning applications
• Board All-In-One combines BI, Corporate Performance Management, and
Business analytics
• It empowers businesses to develop and maintain sophisticated analytical and
planning applications
• Proprietary platform helps to report by accessing multiple data sources

8) Pentaho:
Pentaho is a Data Warehousing and Business Analytics Platform. The tool
empowers business users to access, discover and merge all types and sizes
of data.
Features:
• Enterprise platform to accelerate the data pipeline
• Community Dashboard Editor allows fast and efficient development and
deployment
• Big data integration without a need for coding
• Simplified embedded analytics
• Visualize data with custom dashboards
• Operational reporting for mongo dB
• Platform to accelerate the data pipeline

9) Jaspersoft:
Jaspersoft is an open source BI tool. It empowers people around the world
every day to make better decisions. It provides flexible, cost-effective, and
widely-deployed business intelligence solutions. It enables better decision
making through highly interactive Web-based reports, dashboards, and analysis.
Features:
• It offers reporting, data visualization, and data integration
• It can be integrated into any mobile app so that users can access data from
anywhere
• It provides support for decision-making process through key performance
indicators and problem Indicators
• Available as SaaS, On-premise and cloud platform

10) QlikView:
Qlik allows creating visualizations, dashboards, and apps. It also allows seeing
the entire story that lives within data.
Features:
• Simple drag-and-drop interfaces to create flexible, interactive data
visualizations
• Use natural search to navigate complex information
• Instantly respond to interactions and changes
• Supports multiple data sources and file types
• It allows easy security for data and content across all devices
• It shares relevant analyses, including apps and stories using centralized hub

Business Intelligence Module 5

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