Stephen Wynkoop

Demo: Capture perfmon counters to binary logs and at the same time capture SQL Profiler. Then you can load both into profiler and see both at the same time. Great for troubleshooting what might be causing a problem or what is happening at a particular point in time.

Historical only (not real-time)

When things go Wrong

• What changed?
• What were you doing?
• What were you seeing?
• Answer: NOTHING.

Add all the counters you need. Don’t be skimpy. Start broad and then narrow down. If you don’t record it, you can’t see it.

Intro to SSAS 2008

Marc Beacom

• www.MarcBeacom.com
• twitter.com/MarcBeacom

You can import an existing cube into BIDS which will essentially create a copy of the project that was used to create the cube. (Probably only to a certain extent)

PerformancePoint Services 101

Craig Utley

• Craig Utley, Mentor with Solid Quality Mentors
  • Consultant specializing in development with Microsoft technologies and data warehousing
  • Published author of books, whitepapers, articles, and courseware
  • Operator of LearnMicrosoftBI.com

Performance Point Services

Monitoring, Analytics and Planning

Planning being removed in the next version

• Monitoring: Scorecards and dashboards.
• Analytics: Drill up, drill down, slicing, dicing, etc…

Performance Point ships only with MOSS. With MOSS 2010, 64-bit only, no 32-bit.

KPI Sources are usually cubes but can be other sources including SQL Server, Excel and other sources.

No Pie Charts until next version.

Financial analytics with SQL Server Analysis Services

Donald Farmer

@donalddotfarmer

Need to listen to the Scottish Starbucks analogy again. It was a great analogy but want to be sure I didn’t miss something.

Financial Calculations

• Currency Conversions
• Time Intelligence
• Account Intelligence

Resources

http://www.microsoft.com/sqlserver/2008/en/us/analysis-services.aspx
http://sqlblog.com/blogs/mosha/default.aspx
http://www.sqlserveranalysisservices.com/default.htm
http://sqlcat.com/Default.aspx

Full SpectrumBusiness Intelligence

Donald Farmer

@donalddotfarmer

These slides are masterful is telling the verbal story Donald is presenting. I am putting up a few of the key slides that will server as good reference to me.

Thanks Donald!

Data quality is “fitness for purpose”. IT cannot tell you is a record is good.

TJ Belt

http://tjaybelt.blogspot.com
http://www.twitter.com/tjaybelt

You are on-call, maybe middle of the night and you get a call and there’s a problem. What do you do?

• What tasks were last performed by what persons?
• Start documenting incidents if you don’t already. Great for helping resolve things later down the road.
• Document, document, document

Items to be sure of and continuously check

• Scan OS error events
• Check on backups
• System specific output files (xml, reports, files)
• Log and data file sizes
• Space available / Free space on drives
• Replication health
• SQL Server logs
• Other notes of interest

Work to get your logs clean over time so that problems become more apparent and you will spend less time chasing red herrings.

“You only need one. Either a good backup or a good resume.”

Only notify on error, not on success. (Of course there may be exceptions)

• What are Microsoft SQL Server operators and how to define them (Part 1)
• Undocumented SQL Server 2005 Database Maintenance Plan Stored Procedures
• DB2 and the Procedural DBA, Part 1

Dimension Table ETL with SSIS

Erik Veerman
Mentor, Solid Quality Mentors
SQL Server MVP

Dimension tables contain the “text descriptors” or attributes. Also organized as hierarchies of categories, levels and members.

Slowly Changing Dimension (Ralph Kimball)

• Type 0:No change (Fixed Attribute)
• Type 1:The value is overwritten (Changing Attribute)
• Type 2:Slow changes. A new row is added (Historical Attribute)

Type 2 – New surrogate key and Start Time/End Time updates so to add the new record.

Inferred Members

• Missing dimension member during Fact load later becomes available in the Dimension source
• Also known as late arriving dimensions
• Fact load, placeholder record added to dimension table with new surrogate key generated
• Dimension process, for inferred members, all dimension attribute columns are updated with new values (type 2 attributes are handled as type 1)

Additional SSWUG Articles

• Troubleshooting SQL Server 2005 Integration Services
• MSDN Webcast Summary: Introducing SQL Server Integration Services for SQL Server 2005
• Tips for using SQL Server 2005 Integration Services (Part 3)

Fact Table ETL with SSIS

Erik Veerman
Mentor, Solid Quality Mentors
SQL Server MVP

Identify Dimension Surrogate Keys

• Locate dimension candidate keys in transaction source
• Validate uniqueness and data integrity
• Considering historical changes
  • Identifying current dimension record, combine business keys with current identifying meta data (data identifier or boolean)
  • Handle missing dimension records
• SSIS Data Flow Options
  • Lookup transformation
  • Merge Join transformation
  • Fuzzy Lookup transformation
• SSIS Control Flow Option
  • Execute SQL Task

• Fact ETL involves surrogate keys, grain changes, and measure calculations
• SSIS handles these through several out-of-the-box transformations

Loading a Data Warehouse with SSIS

Brian Knight
bknight@pragmaticworks.com
CEO, Pragmatic Works

Why Data Warehouse?

• Get users off of transactional systems
• Keeping more data online
• Easier reporting
• Consolidate data sources

Data Separated into fact and dimension tables

• Dimension tables answer the pivot or where clause
  • Make as wide and descriptive as possible
  • Surrogate keys operate as unique ID for each row
  • Keep surrogate keys as small as possible
• Fact tables answer the what or select statement
  • Intersect all dimension tables
  • Surrogate keys from each dimension in this table
  • Measures are the “what” like Price, Quantity, Duration

Additional Articles

• MSDN Webcast Summary: Introducing SQL Server Integration Services for SQL Server 2005
• SQL Server 2008 Katmai Change Data Capture (CDC)
• Troubleshooting SQL Server 2005 Integration Services

• http://Blogs.pragmaticworks.com/brian_knight
• http://www.twitter.com/brianknight

Live – SQL Server Analysis Services – Real World Performance Tuning (4hrs)

Ted Malone

(I only caught a few minutes here and there of this marathon live session, but the parts I caught were good. We’ll have to watch the on demand once it goes up.)

• Recommends looking at a product called Performance Advisor from SQL Century for getting performance insight into SSAS.

DBA Checklist

Buck Woody, Microsoft SQL Server Specialist

http://blogs.msdn.com/buckwoody
http://www.informit.com/guides/guide.aspx?g=sqlserver
http://edge.technet.com/People/BuckWoody/

SSMS

• Object Explorer: Right click to see additional columns including Last Backup.
• Standard Reports available via right click
• Log Viewer

oSQL or SQLCMD

PowerShell – Latest and greatest

Post Installation

Daily, Weekly, Monthly and Yearly

Recommends being alerted of both error AND success in order to know that maintenance task really did run.

Maintenance tasks

• Do not run the auto-shrink option in your tasks.

Take a baseline with PerfMon. Email him for a list of counters.

Keep a SQL Server run book containing all configuration changes.

Solving Business Pains with SQL Server Integration Services

Jason Strate

SQL Server MVP
Enterprise Consultant with Digineer
Working with SQL Server since 1997

feeds2.feedburner.com/StrateSql
twitter.com/StrateSQL

• Consolidate packages and deployment
• Use ForEachwith ADO Enumerator for non-file looping
• Expressions on connections increase flexibility of package
• Store config type info in tables for easy retrieval and looping

Add It Up – Analysis Services Aggregations

Craig Utley, Mentor with Solid Quality Mentors
–craig@solidq.com

LearnMicrosoftBI.com

• Hierarchies must be natural to create aggregations at various levels
  • This means creating attribute relationships
• ProcessFulland ProcessIndexesbuild indexes and aggregations
• ProcessUpdateperforms adds, updates, and deletes to a dimension table
  • If a change is detected, flexible aggregations are dropped
• ProcessAddonly adds new records so both flexible and rigid aggregations are kept

OLAP and Data Warehousing – Data Warehousing Solution Architecture (Part 2)

Avoiding Common Analysis Services Mistakes

Craig Utley, Mentor with Solid Quality Mentors
–craig@solidq.com

LearnMicrosoftBI.com

• Dimensions appear to be especially problematic for companies
• The first thing companies should do is correctlyidentify attribute relationships
  • Not identifying them is bad
  • Incorrectly identifying them is worse
• Attribute relationships with flexible relationship types can cause problems with non-unique attributes (eg. Date hierarchy)
• Decide when IgnoreUnrelatedDimensions should be true
• In MDX explicitly reference cells when possible
  • Products.Printersinstead of Dimensions(2).Printers
  • Products.Printersinstead of Products.CurrentMember

Live Session – DBA Survivor II

Thomas LaRock

http://thomaslarock.com/presentations

• Know your RAIDs.
• HA vs. DR – Two different things. Glad he is reminding folks of this!
• Networks – Don’t forget this can cause “performance” problems.
• DBA = Default Blame Accepter (I know Network admins that might argue about that.)
• Be Nice! – #1 rule?
• Email – DON’T DO THIS.  hehe
  • “I have never, nor will I now, tolerate your foolishness.”
  • “I am done with your useless babble.”
• Development
  • “A development server is a production server to a developer”
  • Ask them if it is OK to lock down that server, should fix that response.
  • Manage expectations
    • Be responsive AND responsible
      • Own success AND mistakes (Amen!)
    • Results, not effort
    • Tangible output
  • Get used to developers being needy – They are undo pressure to deliver products on time and under budget.
• Time Management
  • Get in a routine
  • To-Do List
  • Chunking – Write those 6 blog articles at once and schedule publication over the week.
  • Know when to say No

Oh yeah, the sessions. I almost forgot.

If you are interested in knowing what sessions I plan to attend, here is the list.

Day 1

• Scheduled
  • Solving Business Pains with SQL Server Integration Services
  • Avoiding Common Analysis Services Mistakes
  • Live Session – DBA Survivor
  • Live Q&A
• On-Demand
  • Enriching the Design of an Analysis Services Cube
  • Embedding Reporting Into Applications with the ReportViewer Control
  • Add It Up: Analysis Services Aggregations
  • Aggravating Aggregations
  • On Call Duties
  • Configuring the Business Data Catalog

Day 2

• Scheduled
  • DW Dimension Table ETL with SSIS
  • 7 Extraordinary Things To Do With Integration Services
  • DW Fact Table ETL with SSIS
  • SSAS Cube and Dimension Processing with SSIS
  • Q&A
• On Demand
  • DBA Checklist
  • Administrating SQL Server Integration Services (SSIS)
  • ESB Toolkit 2.0 Overview
  • Database Change Process
  • Loading a Data Warehouse in SSIS
  • Implementing Messaging Solutions Using ESB Toolkit 2.0

Day 3

• Scheduled
  • Intro to SSAS 2008
  • PerformancePoint Services 101
  • Financial analytics with SQL Server Analysis Services
  • Full Spectrum Business Intelligence – aligning IT and Business in the new world of data
  • Q&A
• On Demand
  • Data mining for DBAs
  • Introduction to Sketch flow
  • SQL Statement Tuning with Showplan
  • Live Session- Get jQuery().ready; with Rachel Appel
  • SQL Statement Tuning with Indexing Strategies

So, that’s the plan. Obviously all the on-demands won’t be able to be completed each day but hopefully within the next week I can get a look at each of them. There is always the hope of that one golden nugget out of each session.

Blessings.

Just like any other application, OLAP solutions designed and built in Visual Studio 2008 for SQL Server Analysis Service 2008 must be managed from source code to server. In this session, learn different methods for managing your OLAP solutions. Well cover TFS and VSS storage, manual deployment methods using the Visual Studio GUI, as well as command line build automation methods specific to SQL Server Analysis Services project deployments.

Building SSAS Solutions

• Visual Studio / BIDS
  • All BI Projects
  • Easy to use compared to older versions
  • Team Foundation Server / Team System

Building a Solution

• Source Control
  • Visual Source Safe
    • Long history
    • Easy to use
    • Best for small environments
    • Isolated Development
    • Administration
  • Team Foundation Server
    • Central Repository
    • Project Management
    • SQL Server Based Repository
    • Collaborative Development
  • Analysis Services Perspective
    • Team Development
    • Build Projects in BIDS
    • Manage Databases in SSMS
    • BEWARE!

Configuring Deployment

• Configure Project Environment
• Configure Source Control
• Create Project “Configurations”
• Define Targets
• Define Actions

Deployment Solutions

• Visual Studio / BIDS
  • Visual Deployment
  • Immediate Feedback
  • Multiple Configurations
  • Easy to Use
• Automating Builds
  • Msbuild.exe doesn’t work
  • Devenv.exe (Visual Studio Command Line)
  • *.asdatabasefiles = SSAS Deployment Wizard
  • Microsoft.AnalysisServices.Depoyment.exe
    • Must create an answer file using /a ONCE
    • Produces an xmlafile
  • Deploy xmlafile via ascmd.exe

Nothing too terribly new here, but a good reminder for some.

One of the problems that presents those new to Business Intelligence development is how to configure the development and production environments for maximum efficiency. This session will cover the installation and configuration of SSAS for both development and production environments. Attendees will leave this session with a good understanding of the options available and the specific needs in an SSAS environment.

Haha. Beer can aerodynamics analogy. Funny!

Better in 2008

• Innovative Cube Designer
• Best practice design alerts
• Enhanced dimension designs
• Enhanced aggregation designs

I like Ted. Introducing his dog via desktop picture. Nikki?

Installation

• Two important things to SSAS
  • Memory (RAM)
  • I/O
    • Separate channel for your OLAP data
• Add new features to existing SQL Server 2008 instance
• Add SSAS
• Service Accounts
  • Generally speaking: Use a domain service account (Check Carl Dubler’s guide)
• Add current user to the Administrators role
• Data Directories tab
  • Move folders into the appropriate locations based upon I/O channel decisions
• Proceed with the installation process.

Introduces new dog. Sasha! hehe

Configuration (In SSMS)

• Properties of Instance
  • Log\FlightRecorder
    • Captures trace info if stuff goes wrong
    • Enabled by default
    • FlightRecorderCurrrent.trc file
  • Memory
    • Personally Ted hates dynamic memory allocation.
    • If SQLServer and Analysis Services installed on the same box, you must set limits on SQL Server Memory
    • Books Online actually is very good on this topic
      • Planning & Architecture -> Physical Architecture topics are the ones
    • Set Low Memory Limit to 50% – Not a best practice but allows you to look at profiler, services, process and determine how to proceed.
    • While publishing cube, watch the msmdsrv.exe process to see memory utilization.

Books Online. Books Online. Books Online.

Is your customer looking for drag and drop reports or capabilities inside of Excel. SQL Server Analysis Services (SSAS) is the answer for you then. You’ll be amazed how quickly you can develop sophisticated reports after watching the basics of this session.

SSAS is its own server. It is not part of the SQL Server service.

• IIS
• XMLA between server and client

MDX – SQL Language for Cubes
BIDS – Building the Cubes
SSMS – Managing SSAS

Analysis Services

What are cubes?

• What are measures? (See Erik Veerman Dimensional modeling session)
  • The value you are measuring, e.g. the count of users with blue eyes, from WA state, etc.
  • The question you are trying to ask
• What are measure groups?
  • Groupings of these measures within your cube
  • Typically define them by your business problem (e.g. Sales, HR, etc.)
• Cubes are a grouping of measure groups.

Analysis Services Dimensions

What are dimensions and hierarchies? (See Erik Veerman Dimensional modeling session)

• What is a dimension?
  • It is what you want to categorize or pivot against
  • e.g. How many users are from WA state?
  • The dimension is geography, “WA” is the member
• •What is a hierarchy?
  • How do you want to organize the members of your dimension
  • e.g. Geography has numerous levels such as country, state, and city
  • Hierarchy is the organization of those levels such as City ->State ->Country

Concrete examples like these are helpful for my learning and understanding. Thanks!

User Interfaces

• Query language is MDX
• BIDS for developers
• Excel for most users is adequate or Reporting Services
• SharePoint for web users
• 3rdparty applications like Proclarity or Panorama
• Controls you can purchase and build into your own apps

Create User defined hierarchies.

• Remember that in 2008 the hierarchy can be thought of as reversed.
• Looks graphically like date -> month -> qtr -> year
  • Means: to get to a date you must go through year, qtr, month, date

Deal with problematic keys.

Most end users will use Excel. 2007 provides additional features.

Dimension Tables are one of the core components in a dimensional design and it is critical to design your dimension tables correctly in order to lay a solid foundation to a Business Intelligence system. This session dives into the dimension design techniques and considers the core components of a dimension table, surrogate keys, attributes, and hierarchies. In addition, we will consider advanced hierarchy types such as parent-child hierarchies, snowflake designs and unbalanced hierarchies. Finally, we will consider the best practices in tracking changes historically.

This session was intense so I just could not keep up with the slides. Here are just notes apart from the slides once I fell behind. Erik presents excellently and at a level appropriate for a 101 session without being condescending. Great job!

Dimensions (review from Dimensional Modeling 101 Session)

Dimensions – Qualitative
Facts (Measures) – Quantitative

• Dimensions (Qualitative information)
  • Business perspective from which data is looked upon
  • Collection of text attributes that are highly correlated
  • e.g. Product, Store, Time, Manager of Store
• Conformity (How Dimensions relate to each other)
  • Shared with multiple fact relationships
  • Provides data correlation
• Attributes (many times is related to a table column, not always)
  • Descriptive characteristics of an entity
  • Building blocks of dimensions, describe each instance
  • Usually text fields, with discrete values
  • e.g., the flavor of a product, the size of a product
• Hierarchies
  • drill-paths within the dimension
  • Allows top-down analysis
  • Natural groupings of data relationships
  • e.g., date hierarchy is most common. Year to qtr to month to day for example)
• Dimension Keys
  • Surrogate Keys (Primary key, DW created)
  • Candidate Business Keys/Alternate key (Source system keys, uniqueness)
• Dimension Granularity
  • Granularity in general is the level of detail of data contained in an entity (lowest level detail)
  • A dimensions granularity is the lowest level object which uniquely identifies a member
  • Typically the identifying name of a dimension

Name surrogate key with SK_
Dimension naming DIM_
Fact naming FACT_

http://www.codeplex.com/MSFTDBProdSamples to download the AdventureWorksDW example.

Hierarchies

ALL level is usually the top level

All -> Region -> Country -> City -> Office

Seeing one we could use would related to the various Bible translation project locations currently under way. Need to keep in mind project sensitivities.

A dimension can have multiple hierarchies.

Standard Hierarchies

• All levels have values.

Ragged Hierarchies

• Missing members at the mid-levels.
  • All -> Country -> State -> City and then you might be missing a state is the country is Israel since there are not states there.

Unbalanced Hierarchies

• Multiple grains in the hierarchy
• May not always be able to drill down to the lowest detail level since the branch may stop short. (Think Org Chart)

Demo: SSMS connected to a SSAS Cube

Product – Standard hierarchy

Sales Territory – example of unbalanced hierarchy

Employee – another example of an unbalanced hierarchy

Dimension Keys

Business Keys

• Column(s) identify the unique instance of a business record form the source system.
• You may have multiple records with the same Business Key. This is right as it allows historical tracking.
• Used in the process that ties fact records with dimension members
  • Business key is used to find the right surrogate key reference

Surrogate Keys

• • Defined the dimension’s primary key
  • Usually an integer
    • Important to pick the right column width.
    • 2,4,8 byte
      • SmallInt – 2 bytes go for up to around 10k records
      • BigInt – 8 bytes, for REALLY large dimensions
  • Consolidate multi-value business keys
  • Allows tracking of dimension history
  • Standardizes dimension tables
    • All are structured in the same way
      • Business Key
      • Surrogate key

Don’t put attributes and business keys in your fact table.

Design Practices

• Avoid smart keys
• Avoid production keys
• production may decide to reuse keys
• the company may acquire a competitor and thereby change the key building rules changed record, but deliberately not changed key

Types of Dimensions

Different dimensions types should be used in different scenarios.

Basic Dimension Types

• Standard Star dimension
  • Single table
  • Usually date
• Snowflake
  • More than one table in a cascading
• Parent Child (unbalanced hierarchy)
  • Self referencing surrogate to parent surrogate key relationship
  • Self referencing business key relationship
  • e.g. Org Chart, Chart of Accounts

Advanced Types

• Degenerate (Seldom used. Be careful)
  • Dimensions business key with no corresponding dimension table
  • Are embedded in the fact table
  • Typically use only when your Dim record count is about the same as the fact table record count.
  • Usually in line item oriented tables like sales tables
• Profile or Junk Dimensions
  • Convenient grouping of flags and attributes to get them out of the fact table into a useful dimensional framework.
  • Good for one-off lookups. Put them into a single dimension rather than a bunch of small dimensions
    • True/False type attributes
• Role Playing Dimension
  • A single dimension used for multiple purposes
  • Typical example is the date dimension or the geography dimension (outrigger)
• Time Dimension
  • Multiple calendars
    • Fiscal
    • Natural
  • Usually a single table

Tracking History

Industry best practices.

Changing Dimensions

• Slowly changing Dimensions
  • o – No change
    • Birthdate
  • 1 – Not interested in history (Updating a row/record)
  • 2 – Slow changes. Adds new row/record
  • 3 – Fast changes. Adds new column

• Rapidly changing Dimensions
  • Large dimensions
    • Limit type 2’s

Good example graphical slides of Type 1 versus Type 2

Getting There

• Understand dimension hierarchies and drill-paths
• Confirm historically tracked attribute req’s.
  • Don’t be afraid to push back a little
• Check source system data integrity, cleanliness
• Review current reports

DB –> SSIS –> Relational Data Warehouse –> SSAS (Cubes) –> SSRS

Data Sources

• SSAS Projects have one or more data sources that point to data in some physical format
• Data sources should impersonate a domain use with least privileges for the purpose of accessing data.

Data Source Views

• Are required as they are the only things cubes and dimensions can see
• DSV’s are logical representation of the schema for the dimensions and cubes
• You can create new logical primary keys, logical columns, and logical tables in a DSV
• Remember DSV’s are logical so your source data is not altered.

Demo Steps (Fairly Standard Project Creation Steps)

• Create New Project
• Create a new data source (Windows authentication, use specific domain account)
• Create new Data Source View
• Setup Named Calculations where needed
• Start Creating Dimensions
  1. Attribute Relationships
  2. KeyColumns
  3. NameColumns
• Create the Cube
  1. Cube has one or more Measures Groups à Measures
  2. Dimension Usage tab shows what dimensions are used for what measure groups.
  3. Create the aggregations
     • Aggregation usage (Typically use Default or Unrestricted)
       • Full – Must use this attribute
       • None – Never use this attribute
       • Unrestricted – Consider this attribute regardless but only use it if applicable.
     • Use 20% for the Set Aggregation Options as a starting point
     • Save it / Deploy later
• Build
• Deploy
• Processing (BIDS does all 3 by default)

Fact: Can use BIDS 2008 to target a 2005 version project

Creating a Dimension

1. Attribute Relationships
   1. Attribute Relationships are the most important step after creating multilevel hierarchies is to create attribute relationships wherever possible.
   2. Attribute relationships tell SSAS how attributes are related so itacan perform more efficient aggregations and queries.
2. KeyColumns and NameColumns
   1. Example: 4 quarters in a year, need to add year to the key to make each year/qtr unique.

All Dimensions must have a KeyColumn.

Attribute Relationship designer in 2008 looks good. Drag the child onto the parent to create the relationship structure. You can have multiple paths through the attribute relationships.

Set AttributeHierarchyVisible property to false if the attribute is also used in a multi-level hierarchy.

Set format strings in the cube measures

Set IgnoreUnrelatedDimensions to false – Fixes issue with repeating amounts when attribute doesn’t make sense.

Presenter: Ted Malone
http://portal.sqltrainer.com

Gotta love Ted. He’s been with SQL Server since Beta v1.0 on OS/2.

Ted’s presentation is about Agile development method using Visual Studio Team System. Hoping some methodologies can apply using other tools.

Ted on Why Team System: The tools are as important as the process. Tools should make the process invisible.

Typically in a project you are moving from a Product vision into a final Product.

Principles of Team System

• Value Up. Build bottom up, not top down
• Process per project. One size does not fit all
• Iteration. Plan to learn and grow
• Quality early and often. Automate quality development and testing (Like to know more on this for SQL BI projects)
• People first. Trust your people (or in my case, me. Haha) – Empower them with project transparency.

“Know that you’re not going to know something.” – I love that quote.

I like the consolidated work items (tasks) in the VS interface.

Need to learn more about the Scenario functionality of VS Team System. Interesting for automated testing?

Hmmm….ties into Sharepoint as a project status portal. Cool. Too bad we don’t have Team System nor Sharepoint. All of it gets way too expensive for a non-profit. Anyone doing automated testing or continuous integrated for SQL Server, SSAS, SSRS, SSIS using open source tools?

Funny…Ted’s desktop background is a dog. I presume his?

ConfigureSoft Software Development and Lifecycle Management Portal. Provides detailed recommendations for doing Agile/Lifecycle in VS Team System but also includes methodology etc… Is this a product or something that is downloaded and added to Sharepoint?