Presentacion realizada en el Hotel Aurola Holiday Inn en el Evento de Grupo Asesor - Comunidad Windows Eduardo Castro Martinez Costa Rica

1. Ing. Eduardo Castro, PhD
Grupo Asesor en Informática
ecastro@grupoasesor.net

2. Overview of SQL Server 2008
Major Enhancements from SQL Server
2008 to SQL Server 2008 R2

3. SQL Server 2008 is a very powerful tool of
Microsoft. SQL Server 2008 comes up with
many enhancements in Security, Availability,
Performance, Management, Storage,
Programmability, BI( Business Intelligence )
and SSRS (Reporting Services) .

4. New Editions
2 new premium editions to meet the needs of
large scale datacenters and data warehouses
New R2 Technologies
Application and Multi-Server Management
Managed Self-Service Business Intelligence
Master Data Services
StreamInsight Complex Event Processing
Technology

5. New R2 Solutions
PowerPivot for SharePoint
PowerPivot for Excel
Parallel Data Warehouse
Fast Track Data Warehouse

6. Building on the momentum of SQL Server
2008, “R2” improves IT efficiency by
reducing the time and cost of developing
and managing applications
Empowers end users to make better
decisions through Self-Service Business
Intelligence and enables organizations to
scale with confidence by providing high
levels of reliability, security and scalability
for business critical applications.

7. Report Builder 3.0 with support for geospatial
visualization
Application and Multi-server Management - SMP
scale up with support for up to 256 logical
processors.
This CTP provides the first opportunity to explore
some of the features of SQL Server 2008 R2 and
see how it all comes together to enhance
performance and scalability, enable self-service BI
and improve IT and developer efficiency.

8. SQL Server 2008 R2 comes up with two
new feature in scalability and performance
enhancements:
Support for More Than 64 CPUs- The number
of CPU cores that a server can use for
database operations been increased from 64
to 512.
Unicode Compression-Unicode data that is
stored in nvarchar(n) and nchar(n) columns is
now compressed by using an implementation
of the standard Compression Scheme for
Unicode(SCSU) algorithm.

9. Datacenter
Designed to deliver a high-performing data
platform that provides the highest levels of
scalability for large application workloads,
virtualization and consolidation
Key features new to Datacenter:
Application and Multi-Server Management for
enrolling, gaining insights and managing over
25 instances

10. High-scale complex event processing with
SQL Server StreamInsight
Supports more processors and up to 256
logical processors for highest levels of scale
Supports memory limits up to OS maximum

11. SQL Server 2008 R2 Parallel Data
Warehouse is a highly scalable data
warehouse appliance-based solution

12. Key features new to Parallel Data
Warehouse:
10s to 100s TBs enabled by MPP architecture
Advanced data warehousing capabilities like
Star Join Queries and Change Data Capture
Integration with SSIS, SSRS, and SSAS
Supports industry standard data warehousing
hub and spoke architecture and parallel
database copy

14.  Pre-configured For Each SQL Server Instance On Each
Compute Node.
 Drives Configured As RAID1 To Avoid Appliance Failover for a Single Drive
Failure
 IBM Compute Nodes Will Have 1 Lun (1 RAID1 Pair)
 Dell Compute Nodes Will Have 2 Lun’s (2 RAID1 Pairs)
 HP Compute Nodes Will Have 3 Luns’s (3 RAID1 Pairs)
 Tempdb:
 Sort-work Area For Data Loading Into Clustered Index Tables
 Spill Area For Hash Joins Not Fitting Into Memory

15. Pre-configured
4 RAID10 Pairs for Primary User Data
1 RAID10 Pair for Database Logs
2 LUN’s Are Spread Across Each RAID Pair
User Databases Are Separate Physical SQLServer
Databases
Staging Database (Optional) Used for Loading and to
Minimize Fragmentation

19. You can implement it simply when creating
table:
With (Data_Compression=ROW)
or after creating table:
Alter Table [Name] REBUILD
WITH(Data_Compression=ROW)

20. SQL Server 2008 R2 introduces the SQL
Server Utility for managing multiple
instances of the SQL Server Database
Engine.
In SQL Server Management Studio,
organizations will gain insights into their
growing applications and SQL Server
instances

21. Consolidation management
Use a new explorer in SQL Server
Management Studio to access the central
management for multi-server management and
at-a-glance dashboard views
Improve service levels
Set policies to define desired utilization
thresholds across target servers or applications
within a new central management point.
Identify issues with instances and applications

23. Ing. Eduardo Castro, PhD
Grupo Asesor en Informática
ecastro@grupoasesor.net

24. It also introduces a unit of management
called a data-tier application that provides
an application-based view for managing the
data-tier objects in the SQL Server Utility or
stand-alone instances of the Database
Engine.
R2 makes it easier for DBAs to move
databases around from server to server in
much the same way virtualization admins
move guest OS’s around between physical
hosts.

25. SQL Server 2008 R2 still has the same
concept of databases, but it’s added a new
level above databases called Data-Tier
Applications, abbreviated DAC
The DAC includes the database schema
plus some server-level objects required in
order to support the database, like logins.
The DAC does not include the data inside
your database.

26. For deployment best practices, you should
have any necessary data (configuration
tables, basic lookup tables) already scripted
out as part of your deployment strategy.
With the DAC approach, it makes sense to
put these scripts inside the database as
objects. For example, you might have a
stored procedure called usp_deploy that
populates all of the necessary configuration
tables via insert statements.

27. Developers create and update their
database schema, stored procedures,
functions, etc. inside Visual Studio,
packaging them into DAC Packs, and
handing them to the database administrator.

28. Ing. Eduardo Castro, PhD
Grupo Asesor en Informática
ecastro@grupoasesor.net

29. SQL Server installs by creating sysprep-ed
images of SQL Server standalone instances
that can be copied and quickly installed on
target systems.
Enables rapid provisioning and configuration
using prepared images stored in VHDMart
for Hyper-V deployments.

30. SQL Server 2008 Sysprep accomplishes the
install in two phases behind the scenes:
prepare and configure.
In SQL Server 2008 R2, two new SQL
Server setup actions are exposed to the
users: PrepareImage (also referred to as
“prepare”) and CompleteImage (also
referred to as “complete” or “configure”).

31. SQL Server PrepareImage takes about 30 minutes
for Engine and RS components, whereas
CompleteImage takes a few minutes.
Windows SysPrep process can be run in between
the two steps to create Windows OS image and
deploy to target computers, but is not a required
step.
These two steps can be run back-to-back on the
same computer. Sysprep will be able to save on
the average an estimated 30 minutes per install.

32. Empower your business units and users to
create and share BI solutions through
familiar and intuitive tools
SQL Server PowerPivot Add-in for
Excel(formerly known as "Gemini)
SharePoint 2010 based Operations Dashboard
SQL Server Reporting Services Report Builder
3.0
Rich visualization of geospatial data

33. So, what is PowerPivot then?
New client and server components for self-
service, managed BI
Client component lights up Excel 2010
Huge data capacities and mash-ups
In-memory SSAS data model
Server component lights up in SharePoint 2010
Integrated SSAS service to handle data models
Excel Services used to render spreadsheets

34. PowerPivot client tool
Add-in for Excel 2010
Provides SSAS engine, PowerPivot UI
Creates in-memory database model
Gather data for analysis
Load & Prepare Data option
Connect to data sources (lots of options)
Import data into PowerPivot tab
Select columns, filter data as needed

35. Describe how data is related
Inform PowerPivot of data relationships
Supports basic PK-FK type relationships
Create basic data model
Use expressions (DAX) to add calculations
Includes many Excel functions
Expressions based on columns, not cells

36. Use pivot-tables and pivot-charts
Updated task pane for selecting data
Data elements grouped by PowerPivot tab
Use as dimensions or measures as appropriate
New and updated visualizations
Slicers (excellent!)
Sparklines (excellent!)
Improved icon sets, data bar formatting
Improved chart options and performance

37. Ing. Eduardo Castro, PhD
Grupo Asesor en Informática
ecastro@grupoasesor.net

38. Master Data Services helps enterprises
standardize the data people rely on to make
critical business decisions.
With Master Data Services, IT organizations
can centrally manage critical data assets
companywide and across diverse systems,
enable more people to securely manage
master data directly, and ensure the integrity
of information over time.

40. Master Data Services is a Master Data
Management application that consists of the
following components and tools
Master Data Services Configuration Manager,
Master Data Manager
Master Data Services Web service

41. Master data hub that provides central
management of master data entities and
hierarchies and collections
Thin-client stewardship portal that provides
secure, role-based Web access to master
data
Versioning of all data entities and
hierarchies
Human workflow that notifies assigned
owners by e-mail of business rule violations

42. Flexible and extensible business rules that
safeguard the quality of data entered in the
master data hub
Support for a broad range of hierarchy and
attribute management strategies and
requirements
Comprehensive role-based security model
that enables fine-grained, secure access to
master data

44. Models are the highest level of data
organization in Master Data Services
Entities
Attributes and attribute groups
Hierarchies (derived and explicit)
Collections

45. Ing. Eduardo Castro, PhD
Grupo Asesor en Informática
ecastro@grupoasesor.net

46. Data volumes are exploding with event data
streaming from sources such as RFID,
sensors and web logs
The size and frequency of the data make it
challenging to store for data mining and
analysis.
The ability to monitor, analyze and take
business decisions in near real-time

47. SQL Server StreamInsight’s ability to derive
insights from data streams and act in near real
time provides significant business benefits. Some
of the possible scenarios include:
Algorithmic trading and fraud detection for financial
services
Industrial process control (chemicals, oil and gas) for
manufacturing
Electric grid monitoring and advanced metering for
utilities
Click stream web analytics
Network and data center system monitoring.

48. .NET
StreamInsight Application C#
Development LINQ
StreamInsight Application at Runtime
Event sources Event targets
Input StreamInsight Engine Output
Devices, Sensors Adapters Adapters Pagers &
Monitoring devices
Standing Queries KPI
` Dashboards,
Web servers SharePoint UI
Query Query
Logic Logic
Trading stations
Event stores &
Databases Query
Logic
Stock ticker, news feeds Event stores & Databases

50. Events
Represent the user payload along with temporal
characteristics
Streams
Sequence of events
Flows into (one or more) standing queries in StreamInsight
engine
Queries
Operate on event streams
Apply desired semantics on events
Adapters
Convert custom data from event sources to / from
StreamInsight events

51. Database Applications Event-driven Applications
Query Ad-hoc queries or Continuous standing
Paradigm requests queries
Latency Seconds, hours, days Milliseconds or less
Data Rate Hundreds of events/sec Tens of thousands of
events/sec or more
Event
request
output
input stream
response stream

52. Latency
Months
CEP Target Scenarios
Days
Hours Relational Database Applications
Operational Analytics
Applications, Logistics, etc.
Minutes Data Warehousing
Applications
Seconds Web Analytics Applications
100 ms Monitoring Manufacturing
Financial Trading
Applications Applications
< 1 ms Applications
0 10 100 1,000 10,000 100,000 ~1million
Aggregate Data Rate (Events/sec)

53. Analysis of Click Streams on MSN.com
Web Server log streamed into StreamInsight
Categorizing user behavior based on URL:
Click targets
Search keywords
Segmentation of user IDs into markets
Adapting navigational structure and ad placement in
real time
Patterns over time windows: user first clicks PageA,
then PageB, then PageC within X seconds
High performance requirements
Millions of online users
Low latency (seconds)
Possible late events

54. New Editions
2 new premium editions to meet the needs of
large scale datacenters and data warehouses
New R2 Technologies
Application and Multi-Server Management
Managed Self-Service Business Intelligence
Master Data Services
StreamInsight Complex Event Processing
Technology

55. New R2 Solutions
PowerPivot for SharePoint
PowerPivot for Excel
Parallel Data Warehouse
Fast Track Data Warehouse

56. SQL Server 2008 R2 High Availability and
Windows 2008 R2 Group Policy Changes
http://sqlwindows1209.eventbrite.com

57. Ing. Eduardo Castro, PhD
Grupo Asesor en Informática
ecastro@grupoasesor.net