Transcript Business Intelligence - Bermanfaat Bagi Sesama

Business Intelligence
an overview
Nur Cahyo Wibowo, SKom, Mkom
Komputer & Masyarakat
Progdi Sistem Informasi UPNVJT
What is Business?



An organization that provides goods and
services to others who want or need them.
(Univ. of Minnesota)
An economic system in which goods and
services are exchanged for one another or
money. (Business Dictionary)
Kegiatan usaha yang terorganisasi untuk
menghasilkan barang atau jasa guna
memenuhi kebutuhan konsumen dan
bertujuan menghasilkan profit (laba).
The Nature of Intelligence









Learn from experience including by trial & error.
Apply knowledge acquired from experience to
another situation.
Handle complex situations.
Solve problems when important information is
missing is the essence of decision making.
Determining what is important.
The ability to reason and think.
Reacting quickly and correctly to a new
situation.
Understand and interpret visual images.
Being creative and imaginative.
What is AI?
Artificial Intelligence systems include
people, procedures, hardware,
software, data and knowledge needed
to develop computer systems and
machines that demonstrate
characteristics of intelligence
[Ralph Stair].
So, What is BI?



IT-enabled business decision making based on
simple to complex data analysis processes
(BI) applications are decision support tools that
enable real-time, interactive access, analysis and
manipulation of mission-critical corporate
information.
Technically:
• Database development and administration
• Data mining
• Data queries and report writing
• Data analytics and simulations
• Benchmarking of business performance
• Dashboards
• Decision support systems
Business Intelligence Systems


The purpose of a business intelligence
(BI) system is to provide the right
information, to the right user, at the right
time.
BI systems help users accomplish their
goals and objectives by producing insights
that lead to actions.
Source: www.kairon.com
Business Intelligence
Customer
Inventory
Marketing
Data Mart
OLAP
Credit
ETL
tools
Sales
Operation
External
Data
Warehouse
Finance
Data Mart
BI
Reports
Distribution
Data Mart
Pivot Table
Tecnologies Supporting BI








Database systems and database integration
Data warehousing, data stores and data marts
Enterprise resource planning (ERP) systems
Query and report writing technologies
Data mining and analytics tools
Decision support systems
Customer relation management software
Product lifecycle and supply chain management
systems
Business Intelligence Tools



Tools for searching business data in an attempt to
find patterns is called business intelligence (BI)
tools.
The processing of data is simple: Data are sorted
and grouped and simple totals and averages are
calculated.
Reporting tools are used to address questions like:
 What has happened in the past?
 What is the current situation?
 How does the current situation compare to the
past?
BI Tools Cont.



Data-mining tools process data using statistical
techniques, many of which are sophisticated and
mathematically complex.
Data mining involves searching for patterns and
relationships among data.
In most cases, data-mining tools are used to
make predictions.
 For example, we can use one form of
analysis to compute the probability that a
customer will default on a loan.
Data, Information, Knowledge

Data
• Items that are the most elementary
descriptions of things, events, activities, and
transactions
• May be internal or external

Information
• Organized data that has meaning and value

Knowledge
• Processed data or information that conveys
understanding or learning applicable to a
problem or activity
Why Data Warehousing?
Konsumen mana
yg memiliki
margin tinggi/rendah?
Siapa saja konsumen saya
dan produk apa saja yang
mereka beli?
Jalur distribusi apa
yang paling
efektif?
Promosi produk apa
yang paling berpengaruh
terhadap penghasilan
perusahaan?
Konsumen mana yang
senang mengikuti
berbagai kompetisi
perusahaan?
Apa dampak/pengaruh
produk/layanan baru
terhadap penghasilan
perusahaan dan margin?
Data Warehouses and Data
Marts




Basic reports and simple OLAP analyses can be
made directly from operational data.
Many organizations choose to extract operational
data into facilities called data warehouses and
data marts, both of which are facilities that
prepare, store, and manage data specifically for
data mining and other analyses.
Programs read operational data and extract, clean,
and prepare that data for BI processing.
The prepared data are stored in a data-warehouse
database using data-warehouse DBMS, which can
be different from the organization’s operational
DBMS.
Data Warehouses Versus Data
Marts




A data mart is a data collection, smaller than the
data warehouse, that addresses a particular
component or functional area of the business.
The data warehouse is like the distributor in the
supply chain and the data mart is like the retail
store in the supply chain.
Users in the data mart obtain data that pertain to a
particular business function from the data
warehouse.
It is expensive to create, staff, and operate data
warehouses and data marts.
On-Line Analytical Processing
(OLAP)


Literally, On-Line Analytical Processing. Designates a category of
applications and technologies that allow the collection, storage,
manipulation and reproduction of multidimensional data, with the
goal of analysis.
Example: http://perso.wanadoo.fr/bernard.lupin/english
OLTP VS OLAP
Reporting Systems


The purpose of a reporting system is to create
meaningful information from disparate data sources
and to deliver that information to the proper user
on a timely basis.
Reporting systems generate information from data
as a result of four operations:
• Filtering data
• Sorting data
• Grouping data
• Making simple calculations on the data
Digital Dashboard Example
Dashboard
Data Mining



The application of statistical techniques to find
patterns and relationships among data and to
classify and predict.
Data mining represents a convergence of
disciplines.
Data-mining techniques emerged from statistics
and mathematics and from artificial intelligence and
machine-learning fields in computer science.
Strategic, Tactical & Functional
Benefits of Business Intelligence
Referensi





David Kroenke, Business Intelligence and
Knowledge Management Chapter 9, Prentice Hall
2007.
Anonym, Business Intelligence, Bellevue College.
Turban, dkk, Decision Support Systems and
Intelligent Systems Chapter 5, Seventh Edition,
Prentice Hall 2005.
Henry Yan, Business Intelligence, ISRC
Technology Briefing October 26, 2006.
Hanim MA, Intro to Data Warehouse.