See the full webinar at: http://embt.co/1DezC5C Data assets are often hidden treasures in the chaotic landscape of multiple databases. You may be wondering how to analyze and understand your physical database artifacts and put them into meaningful data models with extended metadata that can be used for initiatives such as Master Data Management. We’ll take a look at how to discover and map your data landscape with a live demonstration of ER/Studio Data Architect capabilities including: + Reverse engineering + Naming standards + Attachments + Universal mappings Let us show how you to take advantage of the tool that’s at your fingertips. These features can enable you to better understand and proactively manage your data environment bringing order to chaos.

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Digging Deep
Discover & Excavate Your Data Artifacts
Ron Huizenga & Rob Loranger

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Agenda
• Complex data landscape
• Artifact discovery and identification
• Conquer complexity
– Approach
– Tools
– Techniques for different platforms
• Derive understanding from naming and classification
• Business meaning and value
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Evolution of Systems: Analogy
Evolution:
• 38 years of construction
• 147 builders
• No Blueprints
• No Planning
Result:
• 7 stories
• 65 doors to blank walls
• 13 staircases abandoned
• 24 skylights in floors
• 160 rooms, 950 doors
• 47 fireplaces, 17 chimneys
• Miles of hallways
• Secret passages in walls
• 10,000 window panes (all bathrooms are fitted with windows)
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Complex Data Landscape
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• Comprised of:
– Proliferation of disparate systems
– Mismatched departmental solutions
– Many database platforms
– Big data platforms
– ERP, SAAS
– Obsolete legacy systems
• Compounded by:
– Poor decommissioning strategy
– Point-to-point interfaces
– Data warehouse, data marts, ETL …

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Artifact Discovery and Identification
• Identify candidate databases
• Reverse engineer existing databases into models
• Apply naming standards (comprehension)
• Classify through metadata
• Analyze redundancies & gaps
• Data lineage / chain of custody
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ER/Studio – Tools to Conquer Complexity
• True multi-level sub-models (hierarchy)
• Reverse engineering (extensive list of platforms)
• Comprehensive metadata extensions (attachments)
• Naming standards
• Universal mappings
• Business glossaries
• Macros
• Data lineage
• Business Architect – data context (processes)
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Reverse Engineering & MetaWizard
• The ability to create a data model by connecting to an
existing data store
– Native connector
• Relational
• Big data
– ODBC
– Can also be SQL script rather than direct connection
– Other models and metadata repositories
• Vital to map & analyze complex data landscapes
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Native Support for Big Data
• Ability to model big data constructs
– Nested objects
– Nested object arrays
• Natively reverse engineer big data platforms
– Internal to tool as opposed to MetaWizard
• Forward engineering
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ER/Studio Native Big Data Support
• MongoDB
– Diagramming
– Reverse & Forward Engineering (JSON, BSON)
– MongoDB certification for 2.x and 3.0
• Certified for HDP 2.1
– Forward and reverse engineering
– Hive DDL
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Hive & ER/Studio
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Containment Relationship: Array of Nested Objects
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db.patron.insert(
{
"_id" :
ObjectId("5367ddc4228cd006ab2bc60c"),
name: "Joe Bookreader",
address: [
{
street: "123 Fake Street",
city: "Faketon",
state: "MA"
},
{
street: "1 Someother Street",
zip: "12345"
} ]
})
db.book.insert([
{
title: "MongoDB: The Definitive Guide",
author: [ "Kristina Chodorow", "Mike Dirolf" ],
published_date: ISODate("2010-09-24"),
pages: 216,
language: "English",
publisher_id: ObjectId("5367dd99228cd006ab2bc60b"),
available: 3,
checkout: [ { by: ObjectId("5367ddc4228cd006ab2bc60c"), date: ISODate("2012-10-
15") } ]
},
{
title: "50 Tips and Tricks for MongoDB Developer",
author: [ "Kristina Chodorow" ],
published_date: ISODate("2011-05-06"),
pages: 68,
language: "English",
publisher_id: ObjectId("5367dd99228cd006ab2bc60b")
}])

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ER/Studio – Big Data Notation Enhancement
• Physical Model
– Objects instead of tables
• Nested Objects
– “is contained in”
relationship type
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What about ERP and SAAS?
• Cryptic table and column
names
• Internal data dictionaries
• Thousands of tables
• Often don’t implement
referential integrity in the
database
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Safyr – Technology Partnership
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Safyr: How it works
ERX
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ER/Studio

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Comprehension: Naming Standards
• Extremely important
– Define, apply, enforce
• Real world objects
• Typically comprised of
– Business terms
– Abbreviation for each
– Template (specify order)
– Case, prefixes, suffixes
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Naming Standards Setup/Usage
• Typical use case
– Logical -> physical
• Entity name -> table name
• Attribute name -> column name
• Landscape Mapping
– Physical -> logical
– Table name -> entity name
– Column Name -> attribute name
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Naming Standards
Real-time update while
typing
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Classification Through Metadata: Attachments
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Correlation & Duplication: Universal Mappings
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Business Meaning: Glossary/Terms
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Glossary Integration
• Associate ER/Studio Data Architect objects to Team
Server glossary terms
– Model, submodel
– Entity, Table
– Attribute, Column
– Domain
– View
• Push terms to glossary
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Data Lineage
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Data Source Mapping
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Demo
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Thank you! You have chosen … wisely.
• Learn more about the ER/Studio product family:
http://www.embarcadero.com/data-modeling
• Trial Downloads:
http://www.embarcadero.com/downloads
• To arrange a demo, please contact Embarcadero
Sales: sales@embarcadero.com, (888) 233-2224
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