Transcript Business Analytics and Data Visualization

Business Analytics and Data
Visualization
Decision Support Systems
Chattrakul Sombattheera
Agenda
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Business Analytics (BA): Overview
Online Analytical Processing (OLAP)
Reports and Queries
Multidimensionality
Advanced Business Analytics
Data Visualization
Geographic Information Systems (GIS)
Real-time Business Intelligence, Automated Decision
Support (ADS), and Competitive Intelligence
• Business Analytics and the Web: Web Intelligence and
Web Analytics
• Usage, Benefits, and Success of Business Analytics
Business Analytics (BA): Overview
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Business analytics (BA) is a broad category of applications and techniques for
gathering, storing, analyzing, and providing access to data to help enterprise users
make better business and strategic decisions.
BA is also known as analytical processing, BI tools, BI applications, and just BI.
BI is becoming a major tool for most medium and large corporations. Pizza Hut
knows what kind of pizzas customers order, what kind of coupons they usually use,
and how much customers spend in a given time period.
Marketing managers can run this information through a BI analysis that forecasts, for
example, the probability of a customer’s next order.
The company then uses this information to determine marketing strategies to
influence the customer to buy more pizzas without spending more on that marketing
strategy than it has to.
Example: An analytic application used for a loan application might:
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Calculate a credit-worthiness score
Automatically accept or deny the loan application
Select the loan limit
Select which credit card product (interest rate, payment terms, etc.) to issue to this
application or which other type of loan to approve.
Tools and Techniques of BA
MicroStrategy’s classification of BA tools:
• Enterprise reporting: highly formatted static reports destined for
broad distribution. They are pixel-perfect report formats for
operational reporting and dashboards.
• Cube analysis: provide simple OLAP multidimensional slice-anddice analytical capabilities to business managers in a limited-range
environment.
• Ad hoc querying and analysis: power users can query a database
for any answer, slice-and-dice the entire database, and drill down to
the lowest level of transactional information.
• Statistical analysis and data mining: perform predictive analysis or to
discover the cause-and-effect correlation between two metrics.
• Report delivery and alerting: proactively send full reports or alerts to
large user populations (internal and external), based on
subscription, schedules, or threshold events in the database.
Tools and Techniques of BA
SAP’s classification of strategic enterprise
management: operational, managerial, and
strategic. SAP offers three levels of support:
• Operational: SAP ERP mainly supports
transaction processing on the operational level.
• Managerial: middle managers can use SAP R/3
to access all reports, arranged by functional
areas. Managers can make queries and drill
down.
• Strategic: SAP offers products under the title
SAP SEM (Strategic Enterprise Management),
which includes BA.
Tools and Techniques of BA
Executive information and support systems. Many BI activities evolved
from two tools:
• An executive information system (EIS) is a computer based system
that serves the information needs of top executives. It provides rapid
access to timely and relevant information, to aid in monitoring an
organization’s performance by directly accessing management
reports and to improve managerial growth and learning.
• An EIS is very user friendly, is supported by graphics, and provides
the capabilities of exception reporting (i.e., reporting only the results
that deviate from a set standard) and drill down (i.e., investigating
information in increasing details).
• Executive support systems (ESS) is a comprehensive support
system that goes beyond EIS to include analysis support,
communications, office automation, and intelligence support.
Capabilities of EIS/ESS
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Drill-down: the ability to go to additional details at one or several levels. It
can be done through a series of menus or by direct queries (using intelligent
agents and natural language processing).
Critical success factors (CSF): The factors most critical for the success of
business. These can be organizational, industry, departmental, etc.
Key performance indicators (KPI): the specific measure of each CSF.
Status reports: the latest data available on KPI or some other metric, ideally
in real-time.
Trend analysis: Short-, medium-, and long-term trend of KPI or metrics,
projected using forecasting methods.
Ad hoc analysis: Analysis made at any time and with any desired factors
and relationships.
Exception reporting: Using reports that highlight deviation larger than certain
threshold. Reports may include only deviations.
Slicing and dicing: Rearranging data so that they can be viewed from
different perspectives.
Online Analytical Processing
(OLAP)
• Online analytical processing (OLAP) refers to a variety of activities
usually performed by end users in online systems.
• Such activities are generating and answering queries, requesting ad
hoc reports and graphs and executing them, conducting traditional
or modern statistical analyses, and building visual presentations.
• Essentially, OLAP products provide modeling, analysis, and
visualization capabilities to large data sets, either to database
management systems (DBMS) or, more often, data warehouse
systems, and they also provide a multidimensional conceptual view
of the data.
• OLAP differs from online transaction processing (OLTP) that it
concentrates on processing repetitive transaction in large quantities
and conducting simple manipulations, while OLAP involves
examining many data items (frequently up to millions) in complex
relationships. Furthermore, users can ask specific, open-ended
questions.
Types of OLAP
• Types of OLAP:
– Multidimensional OLAP: OLAPs that are implemented via a
specialized multidimensional databases and summarize
transactions into multidimensional views ahead of time.
– Relational OLAP: OLAPs that are implemented on top of an
existing relational database.
– Database OLAP: RDBMS that is designed to host OLAP
structures and perform OLAP calculations.
– Web OLAP: OLAP data that is accessible from a Web browser.
– Desktop OLAP: low-priced, simple OLAP tools that perform local
multidimensional analysis and presentation of data downloaded
to client machines from relational or multidimensional databases.
Reports and Queries
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Routine reports: generated automatically and distributed periodically to subscribers
on mailing lists. Examples include weekly sales figures, units produced each day and
each week, and monthly hours worked.
Ad Hoc (or on-demand) reports: created for a specific user whenever needed. An
example would be to provide a list of all customers who purchased a company’s
products for more than $5,000 each during January 2006.
Examples of Vendors’ Products for Reporting:
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Report delivery and alerting: MicroStrategy offers
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Business Object’s Crystal Reports,
MicroStrategy
Cognos 8 Business Intelligence
Hyperion
Microsoft’s Report Builder
Report distribution through any touch points
Self-subscription as well as administrator-based distribution
Delivery on-demand, on-schedule, or on-event,
Automatic content personalization.
Ad Hoc queries can be done by SQL.
Multidimensionality
Advanced Business Analytics
Data Visualization
Geographic Information Systems
(GIS)
Real-time BI, Automated Decision Support
(ADS), and Competitive Intelligence
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Real-time application are needed due to urgencies: to control (by changing light
intervals) traffic flow, to monitor the sea level sensors, etc.
Since 2003, BI software tends to produce real-time analysis and decision making
tools for operational and tactical personnel--who generally deal with the short-term
aspects of running an organization—so that they can use new BA tools and up-to-theminute results to make decision.
The proliferation of ADS and business rules management, for example, creates
pressure to implement more automated business processes that can best
implemented in a real-time data warehouse environment. When processes that
require instantaneous updates are needed for answering analytical questions, a realtime response is necessary.
To achieve real-time business analysis, real-time data warehouses need to be
updated very frequently, not just weekly or monthly.
Real-time BA can instantaneously identify, for example, customers buying patterns
based on store displays, and recommend immediate changes for placement or the
display itself.
Other applications include call-center support, fraud detection, revenue management,
transportation, and many financial-related transactions.
However, all data do not need to be updated continuously, etc. periodic reports.
Automated Decision Support (ADS)
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Automated decision support (ADS) systems are rule-based systems that provide
solutions to repetitive managerial problems. They are also known as enterprise
decision management (EDM) systems.
ADS systems are close to BA and BI that some BA models are used to create and/or
operate the business rules, which can be used to trigger the automatic decision that
can be a part of BI applications (performance monitoring and analysis systems).
Automating the decision making process is usually achieved by encapsulating
business user expertise in a set of business rules that are embedded in a rule-driven
workflow (or other action-oriented) engine (which can be part of expert or other
intelligent systems).
A signal will be passed to the rule engine for evaluation against associated business
rules, which determine what action needs to be taken.
The four types of business rules:
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Analysis rules are used to calculate performance metrics from detailed business transaction
data.
Context rules enable performance metrics to be tied to business goals and forecasts.
Exception rules specify thresholds in the metrics and actions (e.g. send alerts) need to be
perform when the metrics exceed defined thresholds.
Action rules are a set of manual decision making processes that can be implemented in a
rule engine.
Competitive Intelligence
• Many companies continuously monitor the activities of their
competitors to acquire competitive intelligence.
• This information drives business performance by increasing market
knowledge, improving knowledge management, and raising the
quality of strategic planning.
• A sporting goods company found an activist group planning a
demonstration and boycott months in advance, enable the company
to implement a counter strategy.
• Within days of launch, a software firm found dissatisfaction with
specific product features, enabling the technicians to write a patch
that fixed the problem within days instead of the months normally
required to obtain customer feedback and implement software fix.
• Barnesandnoble.com used “e-spionage” (Rivalwatch.com) to keep
track of competitors in its specialist professional and educational
book market by monitoring the price changes from their websites.
Business Analytics and the Web: Web
Intelligence and Web Analytics
• Most BA applications are related to the Web.
Software vendors provide Web tools that
connect a data warehouse with e-commerce
ordering and cataloging systems (RETSbond,
Hitachi’s e-Commerce suite tool, etc.)
• Data Warehousing and analytics and decision
support vendors are integrating their products
with Web technologies and e-Commerce, and
they are also creating new ones for the same
purpose (Web Intelligence, Appsource, Decision
Edge.
Web Analytics
• Web analytics is the application of BA activities to Web-based
processes, including e-commerce. This term is used to describe the
application of BA to Web sites. The tools and methods are highly
visual in nature.
• Clickstream Analysis is an implementation of Web analytics. It refers
to the analysis of data that occur inside the Web environment; the
data, known as clickstream data, provide a trail of the user’s
activities and the user’s browsing patterns; which sites are visited,
which pages are accessed, how long is spent on the site, etc.
• By analyzing and interpreting these data a firm can, for example,
find the effectiveness of promotions and determine which products
and ads attracts the most attention.
• As Clickstream operations increase, the amount of data to process
grows exponentially, and scalability issues become critical for Web
analytics.
• By using sorting and aggregating techniques, one can process 1
billion records per day for a Web data warehouse.
Usage, Benefits, and Success of
Business Analytics
• Almost all managers and executives can use BA
systems, but some find the tools too complicated
to use (not trained properly).
• Most businesses want a greater percentage of
the enterprise to leverage analytics, but most of
the challenges related to technology adoption
involve culture, people, and processes.
• A critical issue is to align BA application to the
business needs.
Success and Usability of BA
• Organization that have successfully implemented and used analytic
applications have realized returns ranging from 17 percent to more
than 2000 percent (IDC 2000), with a median ROI of 122 percent.
• However, more than half of BI projects fail.
• BI activities should be regarded as a constantly evolving strategy,
vision and architecture that continuously seeks to align an
organization’s operations and direction with strategic business
goals.
• BI tools can be used to identify inflated invoices, embezzlement,
customer impersonation, and similar offenses.
• The estimate of total fraud in UK is almost US$30 billion. Fraud
committed by employees causes median losses of $60,000, and
fraud committed by managers or executives causes median losses
of $250,000.
• When managers and employees conspire, the median loss rises to
$500,000.
Why BI/BA Projects Fail
• Failure to recognize. BI projects are different from typical standalone applications that they are cross-organizational.
• Unengaged or weak business sponsors.
• Unavailable or unwilling business representatives from the
functional areas.
• Lack of Skilled (or available) staff, or suboptimal staff utilization.
• No software release concept (i.e., no iterative development method).
• No work breakdown structure (i.e., no methodology).
• No business analysis or standardization activities.
• No appreciation of the negative impact of “dirty data” on business
profitability.
• No understanding of the necessity for and the use of metadata.
• Too much reliance on disparate methods and tools.
System Development and the Need
for Integration
• Developing and effective BI decision support application
can be fairly complex.
• Integration, whether of applications, data sources, or
even development environment, is a major CSF for BI.
• Most BI vendors (Oracle, BusinessObjects,
MicroStrategy, IBM, and Microsoft) offer highly integrated
collections of applications, including connection to ERP
and CRM.
• OLAP can be integrated and the output can be analyzed
by the neuron network.
• Most BI vendors provide for application integration,
usually Web enabled.