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INTELLIGENT SYSTEMS BUSINESS MOTIVATION BUSINESS INTELLIGENCE

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Title: INTELLIGENT SYSTEMS BUSINESS MOTIVATION BUSINESS INTELLIGENCE


1
INTELLIGENT SYSTEMS BUSINESS MOTIVATIONBUSINESS
INTELLIGENCE
  • M. Gams

2
Intelligent systems, BI
IN. SOCIETY

ENGINEERING, TECHNOLOGY,BUSINESS, ECONOMY
ARTIFICIAL INTELLIGENCE
3
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.

4
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)

5
Properties
  • Learning, Flexibility, Adaptation, Explanation,
    Discovery
  • Intelligent system, some AI tool agents
    (equilibrium, selling, e-commerce, trading ..),
    user profiling,
  • (I)DM, (I)ML

6
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

7
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?

8
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

9
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)

10
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,

11
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)

12
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

13
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)

14
BI practical
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