Data-Ed: Get the Most Out of Your Tools: Data Management Technologies

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PRODUCED BYDATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060

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11/06/12 © Copyright this and previous years by Data Blueprint - all rights reserved!

Welcome!

Date: November 13, 2012Time: 2:00 PM ETPresenter: Dr. Peter Aiken

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Get the Most out of Your Tools: Data Management Technologies

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PRODUCED BY DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060

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Meet Your Presenter: Dr. Peter Aiken

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•  Internationally recognized thought-leader in the data management field – 30 years of experience

•  Recipient of multiple international awards

•  Founder, Data Blueprint http://datablueprint.com

•  7 books and dozens of articles •  Experienced w/ 500+ data management

practices in 20 countries •  Multi-year immersions with organizations

as diverse as the US DoD, Deutsche Bank, Nokia, Wells Fargo, the Commonwealth of Virginia and Walmart

DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION

Data Management Technologies

Data Management Technologies

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Outline1. Data Management Overview2. Data Management Tools Overview3. Data Technology Architecture4. CASE Tools5. Repositories6. Profiling/Discovery Tools7. Data Quality Engineering Tools8. Data Life Cycle9. Other Technologies10.Q&A

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Tweeting now: #dataed

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The DAMA Guide to the Data Management Body of Knowledge

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Data Management Functions

Published by DAMA International• The professional

association for Data Managers (40 chapters worldwide)

DMBoK organized around • Primary data

management functions focused around data delivery to the organization

• Organized around several environmental elements

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The DAMA Guide to the Data Management Body of Knowledge

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Environmental Elements

Amazon:http://www.amazon.com/DAMA-Guide-Management-Knowledge-DAMA-DMBOK/dp/0977140083Or enter the terms "dama dm bok" at the Amazon search engine

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What is the CDMP?• Certified Data Management

Professional• DAMA International and ICCP• Membership in a distinct group made

up of your fellow professionals• Recognition for your specialized

knowledge in a choice of 17 specialty areas

• Series of 3 exams• For more information, please visit:

– http://www.dama.org/i4a/pages/index.cfm?pageid=3399

– http://iccp.org/certification/designations/cdmp

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#dataed

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Data Management

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Data Management

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Manage data coherently.

Share data across boundaries.

Assign responsibilities for data.Engineer data delivery systems.

Maintain data availability.

Data Program Coordination

Organizational Data Integration

Data Stewardship Data Development

Data Support Operations

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Data Management

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Tools and Methods Are Required!

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Sample Existing Environment

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RDBMS 1

FinanceHR

RDBMS 2

MarketingR

&D #

1

R&D

#2

R&D #3 NetworkDatabase

BackOfficeApplications

ManufacturingSystems Flat Files

LogisticsSystems Flat Files

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As Is InformationRequirementsAssets

As Is Data Design Assets As Is Data Implementation Assets

Exi

stin

gN

ewReverse Engineering

To Be Data Implementation Assets

To BeDesign Assets

To Be Requirements Assets

Forward engineering

Reengineering is typically the problem solution…

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Example Query Outputs

Bibiana Duet's

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Data Management Technologies• Managing data technology should follow the

same principles and standards for managing any technology

• Leading reference model for technology management is the Information Technology Infrastructure Library (ITIL):

http://www.itil-officialsite.com/home/home.asp

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from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International

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Understanding Data Technology RequirementsNeed to understand:• How the technology works• How it provides value in the context of a particular

business• Requirements of a data technology before determining

what technical solution to choose for a particular situation

Suggested questions:• What problem does this data technology mean to solve?• What sets this data technology apart from others?• Are there specific hardware/software/operating systems/

storage/network/connectivity requirements?• Does this technology include data security functionality?

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Defining Data Technology Architecture• Data technology is part of the overall technology

architecture• It is also often considered part of the enterprise’s

data architecture• Data technology architecture addresses 3

questions:

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– What technologies are standard/required/preferred/acceptable?

– Which technologies apply to which purposes and circumstances?

– In a distributed environment, which technologies exist where, and how does data move from one node to another?


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Data Technology Architecture, cont’dData technologies to be included in the technology architecture:• Database management systems (DBMS) software• Related database management utilities• Data modeling and model management software• Business intelligence software for reporting and analysis• Extract-transform-load (ETL) and other data integration

tools• Data quality analysis and data cleansing tools• Metadata management software, including metadata

repositories

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Data Technology Architecture, cont’d

• The technology roadmap for the organization consists of technology objectives as well as reviewed, approved, and published technology architecture components

• This strategic roadmap can be used to inform and direct future data technology research and project work

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Polling Question #1

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What is one important thing to understand about technology?

a) It is sometimes freeb) Buying the same technology

that everyone else is using, and using it in the same way will create business value

c) It should always be regarded as the means to an end, rather than the end itself

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Data Technology Architecture, cont’d• It is important to understand several things

about technology:– It is never free. Even open-sourced

technology requires care and feeding.– It should always be regarded as the means to

an end, rather than the end itself.– Most importantly: Buying the same technology

that everyone else is using, and using it in the same way, does not create business value or competitive advantage.

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Computer Aided Software/Systems Engineering Tools• Scientific application of a set of tools and methods

to a software system which is meant to result in high-quality, defect free, and maintainable software products

• Refers to methods for the development of information systems together with automated tools that can be used in the software development process

• CASE functions include analysis, design, and programming

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Source: http://en.wikipedia.org/wiki/

Computer-aided software engineering (CASE) is the scientific application of a set of tools and methods to a software system which is meant to result in high-quality, defect-free, and maintainable software products. It also refers to methods for the development of information systems together with automated tools that can be used in the software development process.

CASE Tools

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CASE Tools: Example(s)• Microsoft

– Visio

– Powerpoint

– Excel

• ERwin

• ER/Studio

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List of CASE Tools: http://www.unl.csi.cuny.edu/faqs/software-enginering/tools.html

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Figure 18.2 Sample budget for implementing a $2500/seat CASE technology can be $2.5 million over a 5-year period

[adapted from Huff "Elements of a Realistic CASE Tool Adoption Budget" © 1992 Communications of the ACM]

$187K =$2500/seat× 75 seats

$360K = training$500K = workstations$150K = assessment costs$910K = total initial investment

$150K = in-house support $ 55K = hardware and software maintenance $ 60K = ongoing training and misc. $265K = annual additional investment × 5 years $1325K investment over 5 years

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CASE Tool: "Taxonomy"

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[adapted from Joanes Assessment and Control of Software © 1994 Prentice-Hall]

• Senders—flows from the CASE effort that can inform the re-architecting effort.

• Receivers —flows from the project that can inform the CASE effort.

• Senders and receivers —some elements, such as restructuring and reengineering, are both senders and receivers.

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CASE-based XML Support

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http://www.visible.com

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A variety of CASE-based methods and technologies can access and update the metadata

metadata

XMLIntegration

Additional metadata uses accessible via: web; portal;

XML; RDBMS

Everything must "fit" into one CASE technology

Changing Model of CASE Tool Usage

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Limited access from outside the CASE technology environment

CASE tool-specific

methods and

technologies

Limited additionalmetadata use

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Repositories have been difficult to "sell"21 September 1999Michael Blechar, Lisa Wallace Management Summary Most executive and IS managers view an IT metadata repository as

an esoteric technology that is not directly related to the business. However, as will be seen, an IT metadata repository can substantially help IS organizations support the applications, which in turn support the business. An IT metadata repository is a pre-built system and reference database where the IS organizations can track and manage the information about the applications and databases they build and maintain; think of it as the inventory and change impact reporting system for IS. These repositories track metadata such as the descriptions of jobs, programs, modules, screens, data and databases, and the interrelationships between them. Metadata differs from the actual data being described. Metadata is information about data. For example, the metadata descriptions in the repository tell one that the field "customer number" appears in Databases A, B and F ...

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[From gartner.com]

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What tools do you use?

45%

23%

13%

9%7%

2% 1% 1% 1% 1%

None HomeGrown Other CA Platinum Rochade UniversalRepository

DesignBank DWGuide InfoManager InterfaceMetadata

Tool

• Almost one in four organizations (23%) is building their own repository technology

Repository Technologies in Use

Number Responding=181

• Almost one in two organizations (45%) doesn't use repository technology

• The "traditional" players (CA & Rochade) are in use in 16% of organizations surveyed

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Repository Evolution

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Traditional

§ Passive Analysis

§ Relational & Data Warehouse

§ Batch & Reports

§ Optional not critical

§ Proprietary & OIM

Evolving§ Standards – investment

protection: MOF

§ Openness, Simplification & Choice: XMI

§ Diverse metadata management (including messaging)

§ Real time and ad hoc for decision support

§ Daily business value within a production architecture

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"However, due to cost (these tools start at about $150,000, but frequently exceed $1 million) and being slow to market in terms of support for new service-oriented architectures (SOAs), CA and ASG have opened the door to smaller competitors"

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Metadata Repositories 2004

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IBM AD/CycleBusiness Goals ModelDefines the mission of the enterprise, its long-range goals, and the business policies and assumptions that affect its operations.Business Rules ModelRecords rules that govern the operation of the business and the Business Events that trigger execution of Business Processes.

Enterprise Structure ModelDefines the scope of the enterprise to be modeled. Assigns a name to the model that serves to qualify each component of the model.

Extension Support ModelProvides for tactical Information Model extensions to support special tool needs.

Info Usage ModelSpecifies which of the Entity-Relationship Model component instances are used by other Information Model components.

Global Text ModelSupports recording of extended descriptive text for many of the Information Model components.

DB2 ModelRefines the definition of a Relational Database design to a DB2-specific design.

IMS Structures ModelDefines the component structures and elements and the application program views of an IMS Database.

Flow ModelSpecifies which of the Entity Relationship Model component instances are passed between Process Model components.

Applications Structure ModelDefines the overall scope of an automated Business Application, the components of the application and how they fit together.

Data Structures ModelDefines the data structures and their elements used in an automated Business Application.

Application Build ModelDefines the tools, parameters and environment required to build an automated Business Application.

Derivations/Constraints ModelRecords the rules for deriving legal values for instances of Entity-Relationship Model components, and for controlling the use or existence of E-R instance.

Entity-Relationship ModelDefines the Business Entities, their properties (attributes) and the relationships they have with other Business Entities.

Organization/Location ModelRecords the organization structure and location definitions for use in describing the enterprise.

Process ModelDefines Business Processes, their sub processes and components.

Relational Database ModelDescribes the components of a Relational Database design in terms common to all SAA relational DBMSs.

Test ModelIdentifies the various file (test procedures, test cases, etc.) affiliated with an automated business Application for use in testing that application.

Library ModelRecords the existence of non-repository files and the role they play in defining and building an automated Business Application.

Panel/Screen ModelIdentifies the Panels and Screens and the fields they contain as elements used in an automated Business Application.

Program Elements ModelIdentifies the various pieces and elements of application program source that serve as input to the application build process.

Value Domain ModelDefines the data characteristics and allowed values for information items.

Strategy ModelRecords business strategies to resolve problems, address goals, and take advantage of business opportunities. It also records the actions and steps to be taken.Resource/Problem Model

Identifies the problems and needs of the enterprise, the projects designed to address those needs, and the resources required.

Process Model

Extension Support Model

Application Structure

Model

DB2 Model

Relational Database

Model

Global Text Model

Strategy Model

Derivations/ Constriants

Model

Application Build Model

Test Model Panel/ Screen Model

IMS Structure Model

Data Structure

Model

Program Elements

Model

Business ModelGoals

Organization/ LocationModel

Resource/ Problem

Model

Enterprise Structure

Model

Entity- Relationship

Model

Info Usage Model

Value Domain Model

Flow Model

Business Rules Model

LibraryModel

IBM's AD/Cycle Information Model

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Implementing Metadata Repository Functionality

• "The repository" does not have to be an integrated solution– it must be an easily integrateable solution

• Repository functionality (does not equal a) repository– metadata must easily evolve to repository solution

• Multiple repositories are not necessarily bad– as interim solutions, Excel has been working quite well

• Minimal functionality includes ability to create, read, update, delete, and evolve metadata items

• Remember the 1st law of data management– In order to manage metadata, you need metadata

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Data Discovery Technologies

• Data analysis software technologies deliver up to 10X productivity over manual approaches

• Based on a powerful computing technology that allows data engineers to quickly form candidate hypotheses with respect to the existing data structures

• Hypotheses are then presented to the SMEs (both business and technical) who confirm, refine, or deny them

• Allows existing data structures to be inferred at rate that is an order of magnitude more effective than previous manual approaches

• Pioneers include Evoke->CSI, Metagenix->Ascential->IBM, Sypherlink

Profiling Discovery Analysis

- datablueprint.com 11/15/2012 © Copyright this and previous years by Data Blueprint - all rights reserved!

How has this been done in the past?

Old• Manually• Brute force• Repository

dependent• Quality

indifferent• Not repeatable

New• Semi-automated• Engineered• Repository

independent• Integrated quality• Repeatable• Currency• Accuracy

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Select an Attribute toget a list of values

Double-click a value to see rows with that value

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Data Quality Engineering Tools4 categories of activities:

1) Analysis2) Cleansing3) Enhancement4) Monitoring

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Principal tools:1) Data Profiling2) Parsing and

Standardization3) Data Transformation4) Identity Resolution and

Matching5) Enhancement6) Reporting


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DQ Tools: (1) Data Profiling

• Need to be able to distinguish between good and bad data before making any improvements

• Data profiling is a set of algorithms for 2 purposes:– Statistical analysis and

assessment of the data quality values within a data set

– Exploring relationships that exist between value collections within and across data sets

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DQ Tools: (2) Parsing &

Standardization• Data parsing tools enable

the definition of patterns that feed into a rules engine used to distinguish between valid and invalid data values

• Actions are triggered upon matching a specific pattern

• When an invalid pattern is recognized, the application may attempt to transform the invalid value into one that meets expectations


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DQ Tools: (3) Data Transformation

• Upon identification of data errors, trigger data rules to transform the flawed data

• Perform standardization and guide rule-based transformations by mapping data values in their original formats and patterns into a target representation

• Parsed components of a pattern are subjected to rearrangement, corrections, or any changes as directed by the rules in the knowledge base

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DQ Tools: (4) Identify Resolution

& Matching2 basic approaches to matching:• Deterministic

– Relies on defined patterns and rules for assigning weights and scores to determine similarity

– Predictable– Only as good as anticipations of the

rules developers• Probabilistic

– Relies on statistical techniques for assessing the probability that any pair of record represents the same entity

– Not reliant on rules– Probabilities can be refined based on

experience -> matchers can improve precision as more data is analyzed


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DQ Tools: (5) Enhancement

Definition:• A method for adding value to

information by accumulating additional information about a base set of entities and then merging all the sets of information to provide a focused view

Examples of data enhancements:• Time/date stamps• Auditing information• Contextual information• Geographic information• Demographic information• Psychographic information

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DQ Tools: (6) Reporting

Good reporting supports:• Inspection and monitoring of

conformance to data quality expectations

• Monitoring performance of data stewards conforming to data quality SLAs

• Workflow processing for data quality incidents

• Manual oversight of data cleansing and correction

Associate report results w/:• Data quality measurement• Metrics• Activity


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Traditional Quality Life Cycle

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Data Life Cycle Model

MetadataCreation

DataAssessment

Metadata Refinement

Data Refinement

DataManipulation

Data Creation

DataUtilization

MetadataStructuring

Data Storage

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Startingpointfor newsystemdevelopment

data performance metadata

data architecture

dataarchitecture and

data models

shared data updated data

correcteddata

architecturerefinements

facts &meanings

Metadata &Data Storage

Starting pointfor existingsystems

Metadata Refinement• Correct Structural Defects• Update Implementation

Metadata Creation• Define Data Architecture• Define Data Model Structures

Metadata Structuring• Implement Data Model Views• Populate Data Model Views

Data Refinement• Correct Data Value Defects• Re-store Data Values

Data Manipulation• Manipulate Data• Updata Data

Data Utilization• Inspect Data• Present Data

Data Creation• Create Data• Verify Data Values

Data Assessment• Assess Data Values• Assess Metadata

Extended data life cycle model with metadata sources and uses

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Other Technologies Data Integration Definition:• Pulling together and reconciling dispersed data for

analytic purposes that organizations have maintained in multiple, heterogeneous systems. Data needs to be accessed and extracted, moved and loaded, validated and cleaned, standardized and transformed.

• Other tools include:– Servers

– EII technologies

– Portals

– Conversion tools

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Source: http://www.information-management.com

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Polling Question #2

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Which is not a strategic technology trend in 2013?

a) Hybrid IT and Cloud Computing

b) App and Cloud Computingc) Personal Cloud

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Top 10 Strategic Tech Trends in 20131. Mobile device Battles- By 2013 mobile phones will overtake

PCs as the most common Web access device worldwide.

2. Mobile Applications and HTML5- For the next few years, no single tool will be optimal for all types of mobile application so expect to employ several.

3. Personal Cloud- The personal cloud will gradually replace the PC as the location where individuals keep their personal content.

4. Enterprise APP Stores- Enterprises face a complex app store future as some vendors will limit their stores to specific devices and types of apps forcing the enterprise to deal with multiple stores.

5. The Internet of Things- The Internet of Things (IoT) is a concept that describes how the Internet will expand as physical items such as consumer devices and physical assets are connected to the Internet.

Source: http://www.gartner.com/it/page.jsp?id=2209615

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Top 10 Strategic Tech Trends in 2013

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6. Hybrid IT and Cloud Computing- As staffs have been asked to do more with less, IT departments must play multiple roles in coordinating IT-related activities, and cloud computing is now pushing that change to another level.

7. Strategic Big Data- Big Data is moving from a focus on individual projects to an influence on enterprises’ strategic information architecture.

8. Actionable Analytics- Analytics is increasingly delivered to users at the point of action and in context.

9. In Memory Computing- In memory computing (IMC) can also provide transformational opportunities.

10.Integrated Ecosystems- The market is undergoing a shift to more integrated systems and ecosystems and away from loosely coupled heterogeneous approaches.

Source: http://www.gartner.com/it/page.jsp?id=2209615

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XML Integration Server Requirements• Traditional Integration with Existing Systems

– Message Oriented Middleware– “EAI” Adapters

• Validation– Using XML Schema or DTD

• Query Multiple Integration Points using XQuery• Ease of Defining Mappings

– XML to Existing Systems– Existing Systems Creating XML

• APIs for XML

Adapted from Steve Hamby "Understanding XML Servers" DAMA/Metadata Conference April 2003, Orlando, FL

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XML Server Types: Integration, Mediation, Repository

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XML Mediation Server Requirements• XML Standards Based

– Ensures eXtensibility– Changing documents / applications– Transformation to new outputs

• Validation– Using XML Schema or DTD– Business Rules

• Integration with Existing Systems / Integration Servers

• Ease of Defining Rules via GUI for Business User– IT Should Not Have to be Involved

Adapted from Steve Hamby "Understanding XML Servers" DAMA/Metadata Conference April 2003, Orlando, FL

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XML Server Types(Integration, Mediation, Repository)

XML Repository Server Requirements• XML Optimization

– Document Instance• XML Storage

– Stores Document in Native Format

• Better performance• Non-repudiation

– Compression

• XML Standards Support– Faster Development– Ensures Extensibility

• Support Data Access Security at Node levelAdapted from Steve Hamby "Understanding XML Servers" DAMA/Metadata Conference April 2003, Orlando, FL

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Portal Options

[Adapted from Terry Lanham Designing Innovative Enterprise Portals and Implementing Them Into Your Content Strategies Lockheed Martin’s Compelling Case Study Web Content II: Leveraging Best-of-Breed Content Strategies - San Francisco, CA 23 January 2001]

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Top Tier Demo

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Portals as a Data Quality Tool

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Meta-Matrix Integration Example

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ItemField

• Data extraction and conversion software solutions for transforming complex, unstructured data formats into XML for Enterprise Application Integration – RTF

– HTML

– HL7

– Positional (Offset-Based) reports

– TAB-delimited and other delimited reports

– EDI

• Binary documents are automatically converted to a suitable text for parsing for:– Microsoft Word documents

– Microsoft Excel documents

– PDF documents

– COBOL programs

Tamino

BizTalk

http://www.itemfield.com/

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More Data Management Tools

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More Data Management Tools

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Questions?

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It’s your turn! Use the chat feature or Twitter (#dataed) to submit

your questions to Peter now.

+ =

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December Webinar:Show Me the Money: The Business Value of Data and ROIDecember 11, 2012 @ 2:00 PM – 3:30 PM ET(11:00 AM-12:30 PM PT)

Sign up here:• www.datablueprint.com/webinar-schedule • www.Dataversity.net

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