2. History
● Business Intelligence term first apparition on
1958 by Hans Peter Luhn, an IBM researcher
● Authomatic method to provide current
awareness services to scientists and engineers
● Current definition of Business Intelligence as a
combination of processes and technologies for
gathering, storing, analyzing and providing
access to informations to help enterprise users
to make conscious decisions
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3. Main concept
● Collect data from different sources
● Integrate and clean up data in a common, easy
to analyze repository
● Provide business related analysis for managers
and decision makers
● Focus on business, data integration, data
presentation
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4. Datawarehouse
● Bill Inmon: A collection of data in support of
decisional process
● End-user oriented
● Collected from different sources
● Time dependence
● Data is not editable
● In theory means a group of processes
● In the real world is often used for the database
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5. OLTP: On-Line Transaction Processing
● Commonly used in ERP, CRM systems and
database applications
● Focuson transaction level (one invoice, one
sales order, a search query, etc.)
● Updates and insertions are frequent
● Relational model with many tables, using
normalization rules
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6. OLAP: On-Line Analytical Processing
● A system designed for analysis prouposes
● Focused on the data exploration on the whole
● Data once added changes a lot less frequently
● 13 (12+0) rules of Dr. Codd (1993)
● Multidimensional view
● Intuitive data manipulation
● Dimensions, Facts, Hierarchy levels, Cardinality
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8. Relational OLAP
● Uses relational database schemas and SQL to
store and access OLAP cubes
● Reuse of RDBMS technology
● Many tools and vendors available
● SQL can be used directly by many tools
● Scalability
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10. Memory OLAP, Hybrid OLAP
● Memory OLAP uses optimized multidimensional arrays
● Requires pre-computation and storage of the cube
(processing)
● Often better in performances than ROLAP, better
caching, multidimensional indexing
● Compression techniques, statistical indexes
● Less scalable than ROLAP on high volume of data,
less tools and vendors available
● Hybrid OLAP (HOLAP) is the combination of ROLAP
and MOLAP
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11. Slowly Changing Dimensions
● In some Business Intelligence implementations data is
always added and almost never modified
● This makes possible to go back in the timeline
● For example if an employer was hired in a time period
you can analyze data as being in that period, counting
exactly the number of employes
● A common approach to ensure Slowly Changing
Dimesions is to add some special fields to the
database records, giving a time-related validity for
each record
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12. MDX
● Multidimensional Expressions (MDX) is a query
language for OLAP databases
● MDX is to OLAP as SQL queries are to OLTP
databases
● Powerfull on computing indexes and navigating
through OLAP dimensions
● SELECT
{[Measures].[Store Sales]} ON COLUMNS
{[Date].[2002], [Date].[2003]} ON ROWS
FROM Sales
WHERE ([Store].[USA].[CA])
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13. Features for a BI platform
● Data storage, data management
● Data Integration, process schedulement
● Querying and reporting
● On Line Analitycal Processing (OLAP)
● Documents management, versioning
● Statistical computations
● Microsoft Office or Open Office support
● Easy to use and end user self creation of
documents (indipendence from developers)
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19. SpagoBI (BI Suite)
● Engineering
Informatica (Italy)
● Integration of
components using
drivers
● Comprehensive
● Full Open Source
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20. Pentaho (BI Suite)
● Pentaho (USA)
● Acquisition instead of
integration
● Strong marketing
● Commercial and
Open Source
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21. JasperServer (BI Suite)
● JasperSoft (USA)
● Famous for
JasperReports
● Easy to use
● Commercial and
Open Souce
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22. Palo (In memory OLAP)
● Jedox (Germany)
● Interesting technology
(M-OLAP, GPU)
● Excel and OpenOffice
plugins
● Web spreadsheet and
reporting
● Open Source and
Commercial support
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23. Talend (Data Integration)
● Talend (France)
● „Cool Vendor“
Gartner for Data
Integration
● Data Integration, Data
Quality, Data
Management, ESB
● Open Source and
Commercial support
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