erwin® Data Modelerby Quest®

At a glance

Data modeling is a proven technology for visuallydesigning, documenting and deploying
high-quality data sources as well as analyzing
metadata and database schema to understandcomplex data structures. erwin has been the mosttrusted name in data modeling for more than 30years and continues to be foundational for an agile
enterprise data capability. Use it to discover anddocument any and all enterprise data assets fromany location for consistency, clarity and artifact
reuse across large-scale data integration, masterdata management, metadata management, NoSQL,
cloud migration, business intelligence and analytics
initiatives – all while seeding data governance andintelligence efforts.

Key features
erwin Data Modeler remains the gold standard indata modeling and comes in three versions to meet
specific customer requirements.
erwin Data Modeler Standard Edition includes thesekey features:• Native, JDBC and ODBC connectivity — Support
a wide array of DBMS targets, including relational,NoSQL, big data and cloud databases.
• Modern, configurable workspace — Users cancustomize the modeling canvas and optimize
access to the features and functionality theyuse most.
• Visualization of complex data structures —Automatically generate data models to visualize awide range of enterprise sources through a singleinterface.

• Database design generation — Deploy database
schema directly from visual models, increasing
efficiency and reducing errors.
• Schema migration — Auto-document and transform
schema from one DBMS to another to support
re-platforming as well as NoSQL (Cassandra,Couchbase, MongoDB) and cloud databasemigrations (e.g., Snowflake, MariaDB, etc).

Benefits:• Master hybrid data architectures andinfrastructure to accelerate data-centricinnovation.
• Increase design quality and consistency
to reduce analysis, development andmaintenance costs.
• Automate the documentation andmigration of schema between databasetechnologies and deployment platforms.
• Centralize model development forconsistency, governance andmaximum reuse.
• Accelerate data source analysis and target
schema design cycles in BI/analytics,
master data management and data
warehouse/data lake initiatives.
• Reduce data silos by implementing design
and metadata management standards
to simplify integration and improveenterprise collaboration.

• RE Scheduler — Automate the offline reverseengineering of databases into data models somodelers can focus on other activities.
• Standards definition — Increase quality andefficiency with reusable standards, including model
templates, domains, automation macros, naming
standards and datatype standards.
• Model and database comparison — TheComplete Compare facility automates bidirectional
synchronization of models, scripts and databases;
compares one item with the other; displays any
differences, and permits selective updates,generating ALTER scripts when necessary. Quick
Compare templates automate and standardize
comparison criteria for added efficiency
and consistency.

• Collaborative modeling with conflict resolution —Team members can work together more efficiently
via concurrent model access with optional modellocking, multi-user collision resolution, andindependent model merge.
• Change management and audit
capabilities — Controlling and tracking changes
is critical to maintaining quality, consistency andaudit compliance. Specific features include change
impact analysis, version management and undo/
redo capability over the lifespan of a model.
• DevOps capabilities — Greater accuracy,traceability, time savings and better collaboration isexperienced as data modelers stay within the tool
and, with one click, push data definition language(DDL) to GitHub/Git repository via Mart.

• Design transformations — Customize and automate
super-type/sub-type relationships between logicaland physical models and de-normalize ERD models
into JSON/document models.

• User permission and model security
management — Control model assets by managing
user profiles and security settings, including
authentication via LDAP.

• Model exchange — Import/export models to/from awide variety of data management environments forstandardization and reuse across data management
and governance efforts.

• Web-based model and repository
administration — An intuitive, web-based console
allows administrators to manage marts, models,users, profiles, permissions, session locks,
connections and more.

• Reporting and publication — The Report
Designer’s intuitive point-and-click interface andODBC query tool create PDF, HTML and text-based
reports for both diagrams and metadata.
erwin Data Modeler Workgroup Edition adds
the following model management and modelercollaboration features:• Centralized model management repository
available on-premises or as a SaaS subscription
model — Store and provision data models, naming
standards glossaries and standards templates
in a shared repository for managed access,collaboration and cross-model analysis, andgoverning modeling practices and processes.

• erwin Data Modeler Connect for DataIntelligence — Automatically harvest erwin data
models and naming standards from the erwin Data
Modeler Mart for ingestion and cataloging in erwin
Data Intelligence.
erwin Data Modeler Navigator Edition provides
read-only access for a wide range of roles for greatercollaboration through the following key features:• Visualization and navigation of data models — Seedata models in a secure, read-only environment
for easy viewing and understanding of databasestructures and business definitions.

• Impact analysis — View and test the impact ofchanges to data models in a secure, read-onlyenvironment before changes are implemented.
• Enterprise-wide view of data assets — With accessto the erwin Data Modeler Workgroup Edition
model repository, users can obtain a central view ofall enterprise data assets.

Critical differentiators• Visual design, documentation and analysis of any
data source from anywhere — Unify enterprisedata management by harmonizing platform
inconsistencies for a single source of truth.
• Modern, customizable modeling environment —Automate complex and time-consuming tasks formore effective database design, standardization,deployment and maintenance. The configurable
workspace enables users to customize themodeling canvas and optimize access to featuresand functionality to improve productivity.
• Breadth of DBMS integrations andmetadata bridges — Design, auto-document,engineer and transform schema for all major cloudand on-premises database platforms using models
rich in metadata, thanks to built-in interfaces. erwin
Data Modeler also provides out-of-the-box bridges
for metadata exchange and transformation fromother modeling environments, data management
platforms and metadata exchange formats.

• Model and database comparisons —The Complete Compare facility, with Quick Compare
templates, automates bidirectional synchronizationof models, scripts and databases to keep model
contents up to date. Without such automation, thistask is time-consuming and error-prone.
• Roundtrip engineering — Forward- and reverseengineering of database code from relationaland NoSQL models reduces the time and costs
associated with error-prone manual development
processes and ensures models are an accurate
depiction of what has been deployed to support
more efficient and effective model-driven
development.
• Data catalog and business glossary
integration — erwin Data Modeler is an essential
source of metadata and the best way to view
metadata. It’s a critical enabler of data governanceand intelligence, so we’ve enabled metadatafrom erwin data models to be auto harvested andthen ingested into our data catalog and businessglossary, part of the erwin Data Intelligence Suite.

About Quest
Quest creates software solutions that make thebenefits of new technology real in an increasingly
complex IT landscape. From database and systems
management, to Active Directory and Office 365
management, and cyber security resilience, Quest
helps customers solve their next IT challenge now.
Quest Software. Where next meets now.

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