INTELLIGENT SYSTEMS BUSINESS MOTIVATION

BUSINESS INTELLIGENCE

M. Gams

Intelligent systems, BI

ENGINEERING, TECHNOLOGY,BUSINESS, ECONOMY

ARTIFICIAL INTELLIGENCE

IN. SOCIETY

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.

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)

Properties Learning, Flexibility,

Adaptation, Explanation, Discovery

Intelligent system, some AI tool – agents (equilibrium, selling, e-commerce, trading ..), user profiling, …

(I)DM, (I)ML

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

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 WORK

DM on business-related dataagent modeling on a business process

PRACTICAL EXAMPLES

analyze efficiency of tax systemspredict stock (share) valuespredict oil pricesdesign a model for bank loansis selling country assets beneficial or not?

Intelligent systems

Engineering, invisible intelligencePractical directions, real-life problemsVerified 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

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)

S. Goonatilake, P. Treleaven:I. S. for Finance and Business

•20 years ago substantial increase in ISKiller applications - breakthrough

•Visa, 6 G trans. ann., 550G$, security; American Express, 15$ > 1.4$

•typical: lots of data, new AI and HW cap.

•quality improvement, lower costs,

Killer application American Express, Visa

Authorizer’s Assistant - an expert systembefore: 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)

BenefitsThe 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

Discussion

BI = IS/AI (DM) for business and economyBI 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)

BI practical