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Agenda. Data and System Trends Challenges Observations Conclusion. 1983 CD ROMs. 2000’s Terabytes. 1990’s Gigabytes. 1982 3 ½ Floppy Disk. 1973 Winchester Drive. 1986 50 Megabytes . 1967 First Floppy Disk. 1972 5 ¼ Floppy. 1984 10 MB HD. The Big Trends. Storage. 2005.

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agenda
Agenda
  • Data and System Trends
  • Challenges
  • Observations
  • Conclusion
the big trends

1983CD ROMs

2000’sTerabytes

1990’sGigabytes

19823 ½ Floppy Disk

1973Winchester Drive

198650 Megabytes

1967First Floppy Disk

19725 ¼ Floppy

198410 MB HD

The Big Trends

Storage

2005

the big trends1
The Big Trends

Digitally Born Data

2005

increased data under management

1960’s

1970’s

1980’s

1990’s

2000’s

Increased Data Under Management

Conversations

Product Design Data

IWFiles

Pictures

Locations

ElectronicTrades

MasterFiles

Music

SalesData

GIS

MasterTapes

reengineering it efficiency where have the gains come from

1960’s

1970’s

1980’s

1990’s

2000’s

Reengineering IT: EfficiencyWhere have the gains come from?

Knowledge Retentionand Retrieval

Internet

Reporting

B2B Services

Reduce LatencyIn Human Processes

Communications

TransactionProcessing

XML

OLTP

DataProcessing

data moving upstream

Post Transactional

Pre-Transactional

Transactional

Summary

After the fact

Record of fact

Enables Analytics

Record of fact and intent

Enables deeper insight

Data Moving Upstream
the data monolith
Previous 30 years trended towards data consolidation

SOA, connected systems, common schema, pulling data apart

Data Distribution

Data Convergence

The Data Monolith

Data Processing

OLTP

EA

Internet

B2B Services

Devices

SOA

trends recap
Trends Recap…
  • Huge Gains in PSI
    • Processing
    • Storage
    • I/O
  • Exponential Improvement in all of the above
  • Data now online and available with schema
    • Need to derive value from it
  • Human costs now dominate solutions!
  • The data monolith is getting broken apart
challenges
Challenges
  • Data Challenges:
    • Programming
    • Distributing
    • Getting Value
    • Relating and Organizing
    • Sharing
challenge programming data
Challenge: Programming Data
  • Different Environments
    • Data query environment distinct from rest of program
      • No Intellisense, late bound, verbose…
      • T-SQL versus .NET Languages
  • “Impedance Mismatch” between code and database

Programming World

Database World

Transactions

Nulls - 3-value logic

Normalized Data

Declarative Queries

Transparency

Exception Handling

“Different” nulls

Objects

Imperative operations

Encapsulation

the linq project

<book>

<title/>

<author/>

<year/>

<price/>

</book>

SQL

WinFS

Objects

XML

TLN306 – Wed, 1:45PM

DAT323 – Thu, 2:15PM

DAT324 – Fri, 10:30AM

The LINQ Project

C#

VB

Others…

.NET Language Integrated Query

StandardQueryOperators

DLinq(ADO.NET)

XLinq

(System.Xml)

data access in apis today
Data Access in APIs Today

Queries in quotes

SqlConnection c = new SqlConnection(…);

c.Open();

SqlCommand cmd = new SqlCommand(

@"SELECT c.Name, c.Phone

FROM Customers c

WHERE c.City = @p0"

);

cmd.Parameters.AddWithValue("@po", "London");

DataReader dr = c.Execute(cmd);

while (dr.Read()) {

string name = dr.GetString(0);

string phone = dr.GetString(1);

DateTime date = dr.GetDateTime(2);

}

dr.Close();

Arguments loosely bound

Results loosely typed

Compiler cannot help catch mistakes

data access in dlinq
Data Access in DLinq

public class Customer

{

public int Id;

public string Name;

public string Phone;

}

Table<Customer> customers = db.Customers;

var contacts =

from c in customers

where c.City == "London"

select new { c.Name, c.Phone };

Classes describe data

Tables are collections

Query is natural part of the language

The compiler helps you out

architecture

Services:- Change tracking- Concurrency control- Object identity

SQL or Stored Procs

Rows

SQLServer

Application

DLinq(ADO.NET)

Architecture

from c in db.Customerswhere c.City == "London"select new { c.Name, c.Phone }

Objects

LINQ Query

SubmitChanges()

SQL Query

select Name, Phonefrom customerswhere city = 'London'

hello world dlinq style

Hello World “DLinq” Style

Dinesh Kulkarni

Program Manager

C#

ado net vnext

ADO.NET vNext

Pablo Castro

Program Manager

Dataworks

challenge distributing data
Challenge: Distributing Data
  • Need data everywhere
    • PDA → Desktop → App Server → Enterprise
  • Need synchronization/replication
  • Need reliable messaging between stores
  • Need reference data everywhere
    • Contacts
    • Catalogs
    • Price lists
challenge value from data
Challenge: Value From Data
  • Search versus Query
  • Information from existing data
    • Analytics
    • Reporting
  • Managing the data lifecycle
search versus query

Show pictures of people who attended Eric’s

2004 Birthday Party

Eric and Birthday

Query

Search

Search Versus Query
integrated offering

Office

SQL

Business Scorecarding(BSM)

AnalyticApplications

Portal(Office Server)

End-userTools

End-user Analysis(Excel + Excel Server)

Integrate(SSIS)

Analyze(SSAS)

Report(SSRS)

BIPlatform

Data Warehouse(SQL RDBMS)

DAT315 – Thu, 10:00AM

OFF 323 – Fri, 10:30AM

Integrated Offering
challenge exploiting rich data
Challenge: Exploiting Rich Data
  • How to get more value from rich data
  • As
    • Office documents content more accessible
      • New XML formats for Office “12”
    • More intrinsic metadata becomes available
    • We enable data sharing
challenges exploiting rich data
Challenges: Exploiting Rich Data
  • Unify
    • It’s not just about files
  • Organize
    • It’s not just about folders (or tables)
  • Explore
    • It’s not just about search
  • Innovate
    • It’s about a platform
what is winfs
What is WinFS?

DAT 209 – Wed, 1:45PM

DAT 209 – Thu, 5:15PM

DAT 310 – Wed, 3:15PM

DAT 312 – Wed, 5:00PM

ADO.NET

Unified API

ADO.NET support – query, update, app logic, language integrated query, …

It’s Still a File System

FS Semantics, Security, Manageability, Backwards Compatible with Win32

Operations

Backup/Restore, AV, …

Sync

Multi-master Sync

New Windows Types

“Everyday info” schemas + ISV extensions

Structured “Item” Store

Files & Folders  Items & Associations

Integrated storage components

Leverage investments in DB technologies, CLR, NTFS support

Query

Logic

Update

“DLinq”

WinFS

Services

Schemas

SyncAdapters, …

SyncAdapters, …

SyncAdapters, …

People

Mail

OperationsBackup, AV,…

OperationsBackup, AV,…

OperationsBackup, AV,…

Tasks

Media

File Services Metadata Handlers,…

File Services Metadata Handlers,…

File Services Metadata Handlers,…

Docs

Item Data Model

Item

Association

Extension

Database

Engine

NTFS

CLR

winfs

WinFS

Shishir Mehrotra

Lead Program Manager

WinFS

conclusion
Conclusion
  • Data Management value moving -
    • From: base services – store, query, retain
    • To: semantic services – mine, analyze, repurpose
  • We can make it much easier to program against data
  • We will make it much easier for you to:
    • Interact with data
    • Program against data
    • Derive value from data
slide26

© 2005 Microsoft Corporation. All rights reserved.

This presentation is for informational purposes only. Microsoft makes no warranties, express or implied, in this summary.