I just finished the SQLPASS pre-conference from Brian Knight – Building a Microsoft Data Warehousing Platform, and I’m so pumped to do more BI! Reporting, Data Warehousing, Data Mining – all fun stuff.

In a gist, this is what we learned today (and it’s a lot of acronyms):
– SSIS, ETL
– SSAS
– Cubes, Data Warehouse
– Data Mining
– MDX and DMX (on a very very high level)

It was a lot of details and demos jammed in one day, but I won’t have it any other way, and overall the session was just great! Loved it!

Here are some bits and pieces of information / tips / useful sites / resources (probably mostly for my benefit, so I remember. But if you find it useful, then all the better):

• 65% of data warehousing projects fail, and one of the reasons for this is lack of communication. Business users want something, but devs deliver something else.
• Waterfall model for DW projects – hard to react. Agile is better – and Brian recommends 1 month iterations (ie complete deliverable cycle per month)
• Why data warehouse? Consolidate data, aggregates, reporting, analytics, archived data (ex if you need to keep data for years and years)
• Business Key = Alternate Key = PK from source
• Surrogate Keys – insulates data warehouse from source changes
• In one of Pragmatic Works’ projects, they lowered SSIS loading time from 4.5 hours to 3 mins – all about choosing “better” way. In SSIS most components are in memory and are synchronous.
  • Most SSIS components are synchronous – good for performance
  • Some are asynchronous and partially blocking, not so good – for example UNION ALL and MERGE – slight overhead
  • Some are asynchronous and fully blocking – not good at all – for example sort or aggregate transforms – but sometimes there are reasons to use these
• In BIDS, devenv.exe -NOSPLASH to prevent splash screen
• In SSIS – Protection Levels for Packages – EncryptSensitiveWithUserKey generally a bad idea because it associates the package with your profile; if you transfer package, might say package is corrupt. Best to Encrypt All With Password; ServerStorage relies on msdb
• Different types of dimensions
  • Type 0 – Changing Attribute – updates; no history kept
  • Type 1 – Fixed Attribute – cannot change under any circumstance; ignores change
  • Type 2 – helps track changes; biggest disadvantage is additional storage; it creates a new record per update
• Good practice – smaller packages; easier to change and maintain
• Slowly Changing Dimension Wizard (SCD) – data types need to be lined up, need to be very careful; easy to break; also when you need to customize later on and relaunch the wizard, previous customizations will be dropped. You should keep documentation on how to recreate your customizations
• Another problem with SCD – similar to a cursor, goes through row by row; alternative way is to create staging table first. Use T-SQL for what it’s good at, SSIS for what it’s good at. If you can do sorts in T-SQL, do the sorts in T-SQL
• Inferred members – data that not in source, but is in Fact; for example, if it takes 2 weeks to add a salesperson in HR, but salesperson already has sales from Day 1
• Better load – “Fast Load”; also configure “Maximum Insert Commit Size”
• Every member should has an unknown member
• ALWAYS alias your columns
• Alternatives to detecting updates – instead of specifying all columns in a multi OR expression, use CHECKSUM or HASHBYTES. Problem with CHECKSUM is it is not guaranteed to be unique. Ex.

  HASHBYTES('sha', ISNULL(col1, '') + ISNULL(col2, ''))

  So in your expression column can just have something similar to: (DT_WSTR, 64)yourhashcol_src != (DT_WSTR,64)yourhashcol_dw

• SQL Cache Transform – creates cache file, can be reused multiple times; 80% faster in SQL Server 2008; SQL Server 2005 was bad with threading
• Terminologies – data warehouse (SSAS 2008)
  • Measure Group = Fact Table
  • Attributes = Columns in a Dimension
  • Member = Row in an Attribute
• Hierarchies are shortcuts for end users; you can ultimately hide actual attributes (AttributeHierarchyVisible = True), and just expose the hierarchies
• Always reconnect to cube after dimension or attribute changes so changes are apparent
• Set up attribute relationships ex:

  Date SK -- Date -- Month -- Quarter -- Year 

  Note that uniqueness of quarter is really Year + Quarter.

• Set up constraints/uniqueness through the “Key Column”. Set up what’s being displayed to user using “Name Column”. You will probably need to explore your dimensions and see which attributes need this.
• For any time dimensions, add “Time Intelligence”. As a side effect, this automatically adds additional filters like “Yesterday”, “This Week”, “Last Week” etc in Excel
• “Mushroom Cloud” – Invalid queries, but you are getting invalid results. For example if you drag Product then EmployeeCount. This gives you the EmployeeCount value for Product.
• In Cube Editor, MeasureGroup, set IgnoreUnrelatedDimension = False helps prevent “mushroom clouds”; result will display blank instead of giving you invalid value
• Discretization Method – allows you to create dynamic buckets of data
  • Automatic
  • EqualAddress – your just specify number of groups
  • Clusters – groups based on your data
• HideMemberIf (trying to remember why this option was highlighted in the session)
• MDX is language for querying the cube/SSAS; used for creating KPIs, calculations
• Tuple in MDX points to a cell; you can work with six (6) different axes. Good book is MS Press MDX Step by Step
• When you want to show data, put in SELECT; if you don’t but you want to filter by it, put in WHERE
• Parenthesis in an MDX helps you represent a tuple
• SSRS and Excel can generate some MDX
• Calculations < Calculated Member does not store anything in the cube, just the metadata; actual calculations done on the fly
  • PRO: Only formula is stored in the cube; don’t need extra storage
  • CON: Only formula is stored in the cube; performance will be worse
• Usage Based Optimization : Go to SSMS < Connect to SSAS < Set CreateQueryLogTable = true; you can also choose to “Review Aggregation Usage”
• How to lock data in your cube : Go to your dimension then go to Role, and add roles/users
• Option: Enable Visual Totals – like an implicit WHERE; Off by default, which means users will still see all data even if data is locked down; for example, if user can only see US data, his/her totals should be just for US, but s/he will see US Totals, then a different Grand Total. Enable this to lock down these totals to only the data they can see
• Deployment wizard in SSAS – creates .asdatabase file that contains metadata required to deploy the cube
• You dont need to always process the whole cube; you can do incremental processing
• Partitioning in SSAS – in about 50K records, you will start to feel the slowness
• SQL Server Standard allows 3 partitions; SQL Server Enterprise allows any number
• New feature in SQL Server 2008 Enterprise – Proactive Caching
• In SQL Server 2008, you can use profiler on SSAS to deconstruct MDX queries. In Excel, you can also right click on some columns then check MDX
• There is an option to do offline OLAP : Excel < Options < OLAP Tools < Offline OLAP. You can get to your data, but actions and drillthrough are off
• Double hop issue in SSRS and SSAS when you build reports on top of the cube : check Kerberos, SPN
• You don’t need a cube to do data mining! You can also allow your users to do predictions based on flat tables or views.
• Sample data mining scenario: used to auto approve insurance claims; can be used for fraud detection; can be integrated with SSIS in conditional tasks
• For data mining structures, Decision Trees is the best way to start; as far as alogrithms go, you can even create your own, or purchase 3rd party algorithms
• Users can get/do data mining through Excel
• Users can do drillthroughs with data mining

Useful Resources / Sites

• pragmaticworks.com
• sqlshare.com
• ssas-info.com
• dtsxchange.com
• sqlserverdatamining.com
• Marco Russo’s Expert Cube Development with Microsoft SQL Server 2008 Analysis Services
• Brian Knight’s 24-Hour Trainer: Microsoft SQL Server 2008 Integration Services (Wrox Programmer to Programmer)
• MS Press Microsoft SQL Server 2008 MDX Step by Step (Step By Step (Microsoft))

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