Where data management and data governance meet

Organizations are flooded with more and more data, so they’re investing in ways to derive meaningful insights from it – and turn them into actions that improve the bottom line. But solving this data dilemma is easier said than done without the right approach and technology.

While data management drives the design, deployment and operation of systems that deliver operational and analytical data assets, data governance delivers these data assets within a business context, tracks their physical existence and lineage, and maximizes their security, quality and value. Both disciplines require a real-time, accurate picture of the data landscape, but creating and maintaining this metadata landscape is challenging and often leads to inaccurate/faulty insights and analysis.

But erwin can help you:

  • Discover data: Identify and integrate metadata from various data management silos.
  • Harvest data: Automate the collection of metadata from various data management silos and consolidate it into a single source.
  • Structure and deploy data sources: Connect physical metadata to specific business terms and definitions and reusable design standards.
  • Analyze metadata: Understand how data relates to the business and what attributes it has.
  • Map data flows: Identify where to integrate data and track how it moves and transforms.
  • Govern data: Develop a governance model to manage standards and policies and set best practices.
  • Socialize data: Enable stakeholders to see data in one place and in the context of their roles.

Our “EDGE” Is Your Edge

The erwin EDGE Platform creates an “enterprise data governance experience” that brings together both IT and the business for data-driven insights, agile innovation, regulatory compliance and business transformation. Because we own every critical piece of the data management and data governance lifecycle, we can help you automate and accelerate your speed to accurate, actionable information in context to achieve your strategic objectives:

From our perspective, data governance drives everything so it’s the hub of our EDGE platform. By integrating it with our other core capabilities into a single solution, we’ve taken the most comprehensive approach to managing – and extracting value from – the entire data management and data governance lifecycle. We identify how data flows through and impacts the business, align this business view with a technical picture of the data management infrastructure, and synchronize efforts across the business and IT so all domains are unified and mutually supportive.

Define application capabilities and interdependencies within the context of their connection to enterprise strategy to prioritize technology investments.

Define, map and analyze workflows and build models to drive process improvements, including determining where controls are needed for greater security, compliance and overall risk management.

Design and deploy new databases with “any data” from “anywhere” for data integration, master data management, Big Data and business intelligence and analytics.

Map and transform data elements from source to target to determine data lineage, deploy data warehouses and other Big Data solutions, and harmonize data integration across platforms.

Know what data exists and where it’s located, understand what it means in common, standardized terms so it can be transformed into useful information, and control its quality and security.

Benefits of Integrated, Persona-Based Data Governance

Whether you’re a data scientist, data steward, ETL developer, enterprise architect, business analyst, risk manager, chief data officer or chief executive – you use data to do your job, but you need it to be current and accurate. Thanks to the broadest set of metadata connectors and automated code generation, sensitive data discovery, data mapping and cataloging tools for data preparation, modeling and governance, every stakeholder can discover, understand, govern and socialize data assets.

The persona-based erwin EDGE Platform provides the most agile, efficient and cost-effective means of launching and sustaining a comprehensive data governance initiative. Its components and the roles that use them are then integrated and enabled by cross-platform capabilities:

  • Impact analysis: See how changes to the data design will impact enterprise operations
  • Lineage: Understand where data came from and what happened to it along the way
  • AI and Machine Learning: Use artificial intelligence and automation to maintain an efficient and cost-effective data governance framework
  • Data Transformation: Change instance data for data integration, aggregation and harmonization
  • Data Quality: Integrate data quality metrics and artifacts with metadata quality and standardization capabilities for a consistent data landscape
  • Metadata Ingestion and Translation: Automatically collect and organize key metadata for an accurate depiction of data at rest and data in motion
  • Workflow and Collaboration: Manage the workflows and interactions of different stakeholders through pre-defined, configurable roles and processes
  • Socialization and Discovery: Enable stakeholders to form communities based on areas of common interest to share insights and collaborate