Business Intelligence with SQL Server
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Transcript of Business Intelligence with SQL Server
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SQL Server 2008 for Business IntelligenceUTS Short Course
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Specializes in C# and .NET
(Java not anymore) Testing
Automated tests Agile, Scrum
Certified Scrum Trainer
Technology aficionado • Silverlight• ASP.NET• Windows Forms
Peter Gfader
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Attendance
You initial sheet
Hands On Lab
You get me to initial sheet
Homework
Certificate
At end of 5 sessions If I say if you have completed successfully
Admin Stuff
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Course Timetable & Materials
http://www.ssw.com.au/ssw/Events/2010UTSSQL/
Resources
http://sharepoint.ssw.com.au/Training/UTSSQL/
Course Website
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Course OverviewSession
Date Time Topic
1Tuesday14-09-2010
18:00 - 21:00
SSIS and Creating a Data Warehouse
2Tuesday21-09-2010
18:00 - 21:00
OLAP – Creating Cubes and Cube Issues
3Tuesday28-09-2010
18:00 - 21:00
Reporting Services
4Tuesday05-10-2010
18:00 - 21:00
Alternative Cube Browsers
5Tuesday12-10-2010
18:00 - 21:00
Data Mining
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What is… Business Intelligence Data Warehouse / Data Mart SSIS (DTS)
Steps in Creating a Data warehouse Analysis of Existing Data Creating Structures Clean and Load (Staging)
Session 1: Tonight’s Agenda
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Automating with SSIS
Creating a Data Warehouse
Hands on Lab - You!
Session 1: Tonight’s Agenda
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Business intelligence (BI) is a broad category of applications and technologies for gathering,
storing, analyzing, and providing access to data to help enterprise users make better business
decisions.
Reports + Interactivity
Business Intelligence Defined?
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OLTP - On Line Transaction Processing System
Transactions
Simple & Efficient
Optimized for 1 record at a time
Our traditional data store= OLTP
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Database
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BI on top of OLTP
OK with little data...
Reports on OLTP database
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BI on top of OLTP
OK with little data...
BI with little data???
Reports on OLTP database
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Reports on OLTP database
BI on top of OLTP
OK with little data
BI with little data???
SLOW with huge data
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A database
The answer is "a database", no matter what the question is
Solution?
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Database
Cleaned and Restructured for Analysis (normalized schemas)
Data warehouse
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Data Warehouse
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We can go further...
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OLAP Cubes
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Pre calculated Data structure
Fast analysis of data
Dimensions and Measures (aggregations)
Dimension Hierarchies
Slice and Dice Measures by Dimensions
OLAP Cubes
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Let's do it
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1. Create Data Warehouse
2. Copy data to data warehouse
3. Create OLAP Cubes
4. Create Reports
5. Do some Data Mining Discovering a Relationship that was not obvious Predict future events (e.g. targeting and forecasting)
Steps
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1. Create the Data Warehouse
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What do you want to get out of it?
How much stock do we need? When are our highest sales? How many bikes did we sell last June?
Identify Candidate Data
Look at the data, see what might be useful
Identify Dimensions and Measures
Year, Product, Employee, etc (Dimensions) Sales Amount, Quantity, etc (Measures)
Creating a Data Warehouse
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Build Structure
Facts (Measures) and Dimensions Snowflake Schema
Creating a Data Warehouse
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Theory
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2 types of columns
1.Numeric facts
2.Foreign keys to dimensions
Contains
1.Detail-level facts
or
1.Aggregated facts
Fact table
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Categorizes data
Small in size
Dimension Tables
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• Simplest schema for a data warehouse
• Center is a fact table
Star schema
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Variation of star schema
More complex
Dimensions are normalized
Snowflake schema
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Revenue is fact
Dimensions to see data
Example: Retail chain
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Creating a Data Warehouse - Snowflake schema
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SQL Server’s Own Data Warehouse
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2. Copy data to data warehouse
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Microsofts answer: SSIS
SQL Server Integration Services
Load Data
Extract, Transform (clean) and Load
Copy data to data warehouse
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Replaces DTS (Data Transform Services)
SQL Server Integration Services
Extract, Transform and Load (ETL) Moving Data Around
Automation
Batch Processing
Advanced error handling and programming control
What is SSIS?
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SQL Tasks Checking Integrity Clearing Stage Data Rebuilding Indexes Determining Surrogate Keys
Data Flow Tasks (ETL) Sources Transformations Destinations
SSIS Puts it all together Controls Sequencing and Conditional Flow Packages can be run as jobs in SQL Server
Automating with SSIS
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SSIS Designer
What can we do?
What can we import data from?
What can we export data to?
What can we do to the data?
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Almost anything you want!
Import data from one database to another FTP a file to a server Run SQL commands Send an email Call a web service Perform database maintenance tasks
What can we do?
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What can we import from?
ADO.NET
Excel
Flat File
OLE DB
Raw File
XML
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What can we export to?
Same as what we can import from plus:
Data Mining Model Training
Dimension Processing Partition Processing SQL Server
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Compare
Split
Filter
Convert
Group
Join
Aggregate
Sample
Sort
Pivot
What can we do to the data?
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What is SSIS?
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Use it to gather data from different datasources
Import data from an employee list stored in excel Export data to XML and mail it to another company
for them to use Pull accounting and salary info from MYOB,
performance information from TFS/CRM and use the data to generate KPI reports
So what can you do with this?
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Creating a Data Warehouse – Data Warehouse Architecture
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Current data
Short database transactions
Online update/insert/delete
Normalization is promoted
High volume transactions
Transaction recovery is necessary
Current and historical data
Long database transactions
Batch update/insert/delete
Denormalization is promoted
Low volume transactions
Transaction recovery is not necessary
OLTP OLAPvs
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The 5 Sessions
What is… Business Intelligence Data Warehouse/Data Mart SSIS
Steps in Creating a Datawarehouse Analysis of Existing Data Creating Structures Clean and Load (Staging)
Automating with SSIS
Creating a Data Warehouse
Summary
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Thank You!
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