INTELLIGENT SYSTEMS BUSINESS MOTIVATION BUSINESS INTELLIGENCE

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INTELLIGENT SYSTEMS BUSINESS MOTIVATIONBUSINESS
INTELLIGENCE

• M. Gams

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Intelligent systems, BI
IN. SOCIETY

ENGINEERING, TECHNOLOGY,BUSINESS, ECONOMY
ARTIFICIAL INTELLIGENCE
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Definition

• Business intelligence (BI)
• (Wikipedia)
• mainly refers to computer-based techniques used
  in identifying, extracting, and analyzing
  business data, such as sales revenue by products
  and/or departments, or by associated costs and
  incomes.
• BI technologies provide historical, current and
  predictive views of business operations. Common
  functions of business intelligence technologies
  are reporting, online analytical processing,
  analytics, data mining, process mining, complex
  event processing, business performance
  management, benchmarking, text mining and
  predictive analytics.

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Definition

• Business intelligence (BI)
• (Wikipedia)
• Sometimes used as a synonym for competitive
  intelligence, because they both support decision
  making, but BI uses technologies, processes, and
  applications to analyze mostly internal,
  structured data and business processes while
  competitive intelligence gathers, analyzes and
  disseminates information with a topical focus on
  company competitors.
• For us, BI including some AI tool (seminar work
  rather not including genetic algorithms, decision
  systems)

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Properties

• Learning, Flexibility, Adaptation, Explanation,
  Discovery
• Intelligent system, some AI tool agents
  (equilibrium, selling, e-commerce, trading ..),
  user profiling,
• (I)DM, (I)ML

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BI (IS) areas

• Support for BI/IS solutions BI/IS governance,
  BI/IS strategies, BI/IS maturity models, BI/IS
  success factors, and BI/IS performance
• Emerging trends in BI pervasive BI, BI 2.0
  (social media and BI), and mobile BI
• Real time data warehousing und operational BI
• Applications of BI, such as customer
  relationship management and business performance
  management
• Data warehousing and data integration
• Predictive and advanced analytics, and data
  visualization
• Data, text and web mining for BI
• Management of knowledge and business process
  improvement
• Social and behavioral issues , and social
  media usage
• Capturing and sharing knowledge in social
  networks and distributed contexts
• Design, development, adoption, usage, and
  impact of IS on KI
• Inter-organizational IS BI systems, such as
  in the supply chain and learning

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BI (IS) APPLICATIONS

• BUSINESS
• FINANCE
• ECONOMY Related to a person, institution,
  country, continent
• Anything of this related to IS, i.e. using
  AI methods
• RECOMMENDED METHODS FOR SEMINAL WORKDM on
  business-related dataagent modeling on a
  business process
• PRACTICAL EXAMPLESanalyze efficiency of tax
  systemspredict stock (share) valuespredict oil
  pricesdesign a model for bank loansis selling
  country assets beneficial or not?

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Intelligent systems

• Engineering, invisible intelligence
• Practical directions, real-life problems
• Verified AI methods rule-based systems, trees,
  expert systems, fuzzy systems, neural networks,
  genetic algorithms, hybrid systems
• Intelligent systems often simulate human
  bureaucrats, expert systems simulate experts

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Motivation / business

• People are expensive (to buy or maintain),
  computers cheap computers work 24 hours a day,
  no vacations, network accessibility is worldwide,
  only 3 microprocessors in computers, an average
  car 16 microprocessors, exponential trend
  (faster, cheaper, more applications)
• Intelligent systems are more friendly, more
  flexible than classical systems (not truly
  intelligent, just a bit more than classical)

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S. Goonatilake, P. TreleavenI. S. for Finance
and Business

• 20 years ago substantial increase in ISKiller
  applications - breakthrough
• Visa, 6 G trans. ann., 550G, security American
  Express, 15 gt 1.4
• typical lots of data, new AI and HW cap.
• quality improvement, lower costs,

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Killer application American Express, Visa

• Authorizers Assistant - an expert system
• before simple rigid rules, majority left to
  human supervisors, many people with different
  performance
• Then new an expert / intelligent system with
  many rules, copies expert supervisors, faster,
  cheaper, more equilibrated10 times better per
  one transaction
• (Visa - an neural network DM and ML prevail)

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Benefits

• The key question trust can IS be trusted -
  obviously good enough (actually as good as
  average humans)
• Intelligent systems enabled organizational
  changes in terms of HW, SW and humans
• Work done better and faster, more profits,
  cheaper transactions
• Less employed, more work done by computers
• Problem - unemployment

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Discussion

• BI IS/AI (DM) for business and economy
• BI combine advantages of computer systems (cost,
  availability) with IS methods, simulating some
  human properties (learning, adapting, reasoning),
  and achieve better cost/benefit for several tasks
  in BI
• How to use BI? IS/AI/DM (computer intelligence)
  BI problem additional knowledge (economic, BI)

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BI practical