www.bilisim.com.tr

Business Intelligence System

September 2013

BI

www.bilisim.com.tr

Making Fact-based Desicions Making Fact-based Desicions

Challenges

More Data

More Users

Less Time

Challenges

More Data

More Users

Less TimeYet, their time for decision-making

is decreasingYet, their time for decision-making

is decreasing

Desicion-makers on all levels of management with different job

roles need to understand this data

Desicion-makers on all levels of management with different job

roles need to understand this data

Volume and complexity of data flowing into companies increasing

Volume and complexity of data flowing into companies increasing

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Implementing Business Intelligence in the Companies

Implementing Business Intelligence in the Companies

The organization hierarchy may not be suitable for a new BI implementation project.

IT departments may not have the required BI and data warehouse skills.

Limited IT budget.

Different OLTP systems from different vendors with little or no integration between them.

Unstructured data which are stored in e-mails, a high number of Excel Sheets and unconsolidated reports and query results from a number of OLTP systems

Challenges

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DATA SOURCES

Online Databases (OLTP), Semi-structured data like Excel files.

DATA SOURCES

Online Databases (OLTP), Semi-structured data like Excel files.

STAGING AREA

Data storing, cleansing, selecting, transforming, aggregating, integration operations

STAGING AREA

Data storing, cleansing, selecting, transforming, aggregating, integration operations

PRESENTATION LAYEROLAP Tools, Dashboards, Reports,Interactive Online Queries

PRESENTATION LAYEROLAP Tools, Dashboards, Reports,Interactive Online Queries

DATA WAREHOUSE / DATA MART

Metadata Repository, OLAP cubes

DATA WAREHOUSE / DATA MART

Metadata Repository, OLAP cubes

Data Extraction

Data Loading

Business Intelligence ApplicationsBusiness Intelligence Applications

Analysis

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The main components of a BI system The main components of a BI system

Business intelligence: set of tools and technologies that systematically exploit available data to retrieve information useful in supporting complex decision making processes

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bilişimBI’s Approach

Agile business intelligence

Simple and intuitive user interface.

No “high-tech terminology”, no “data warehouse

knowledge” needed to create multi-dimensional

analysis.

interactive dashboard-style communication.

All ETL (extract, transform, load) functionality

included. No additional license fees to be paid to

third-party software.

Speedy response with in-memory query execution.

The bilişimBI works seamlessly with bilişimERP.

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The Architecture of bilişimBI SolutionThe Architecture of bilişimBI Solution

DecisionsOptimizationData Mining

Data Exploration

Data Warehouse/Data Marts

Visual Query Tool(Real time data analysis)Visual Query Tool

(Real time data analysis)

Multidimensional Analysis

Tool

Multidimensional Analysis

Tool

ETL WizardETL Wizard

Data SourcesbilişimERPOperational

(OLTP) Data Personal semi-structured data

META DATA REPOSITORY

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Visualization.

Data Integration

Data Warehouse, Data Marts, OLAP Cubes

Stage 3

Advanced Analytics &

Data Mining

Stage 2

Strategic Decision Support Applications

Stage 1

Fundamental Data Warehouse & Visualization Functions

3 Staged Research & Development Project

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Performance Monitoring, Balanced

Scorecards

Performance Monitoring, Balanced

ScorecardsAnalytical WorkflowsAnalytical Workflows

Descriptive AnalyticsDescriptive Analytics

Dashboards, widgetsDashboards, widgets Mobile BIMobile BIOffice IntegrationOffice Integration

STRATEGIC DECISION SUPPORT APPLICATIONS

Time Series AnalysisTime Series Analysis

Will be ready by the end of 2014

Stage 2

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Case StudyCase Study

Product A Product B Product C Product D0

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Product A Product B Product C Product D0

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Case StudyCase Study

The Analysis of Product Costs

By clicking on product C…..

COST TYPE

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TOTAL COST ($)

Materials

External Operations

Internal Operations

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Case StudyCase Study

To achieve the required analysis:

1. Build the metadata. (A prerequisite of all the analysis tasks)

2. Create the domain of analysis

3. Specify the data tables of the domain.

4. Determine the measures.

5. Determine the criteria.

6. Save the analysis domain and schedule the ETL tasks.

7. Configure the analysis widget (Graph, table, etc.)

8. Use the interactive dashboard to see the results.

www.bilisim.com.trCase Study

Building the meta dataBuilding the meta data

www.bilisim.com.trCase Study

Creating the Analysis DomainCreating the Analysis Domain

You can update the existing Analysis simply by clicking on it.

You can create new analysis (ETL tasks) by using the Add button.

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What would you like to analyze?What would you like to analyze?

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What would you like to measure?What would you like to measure?

Probable facts are listed automatically.Probable facts are listed automatically.

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What are your analysis criteria?What are your analysis criteria?

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Save and ScheduleSave and Schedule

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Defining Data Quality RulesDefining Data Quality Rules

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Configure the dashboard settingsConfigure the dashboard settings

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Interactive DashboardInteractive Dashboard

Product A Product B Product C Product D0

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Internal Operations

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Collaboration with the IndustryCollaboration with the Industry

✔ Ability to see real-life analysis requirements

✔ High-quality OLTP data to work with

✔ Useful feedback in the early phases of the project

✔ Extensive testing

✔ Ability to verify the design desicions

✔ Motivated agile development with short iterations

✔ Guidence about the functionality of future releases

Benefits for the Software Developers

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• Leveraged the value of their online enterprise data by

applying data quality rules

• Eliminated most of their heavy Excel work

• Leveraged real-time insights in the context of their

industry and role by using our Visual Query Tool.

• They even created “what-if” simulations to fully

understand the business impact of their desicions.

Collaboration with the IndustryCollaboration with the Industry

Benefits for the Industry

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