erwin Data Intelligence

erwin Data Intelligence by Quest combines data catalog and data literacy capabilities for greater awareness of and access to available data assets, guidance on their use, and guardrails to ensure data policies and best practices are followed. Automatically harvest, transform and feed metadata from a wide array of data sources, operational processes, business applications and data models into a central catalog. Then, make it accessible and understandable via role-based, contextual views so stakeholders can make strategic decisions based on accurate insights. erwin Data Intelligence supports enterprise data governance, digital transformation and any effort that relies on data for favorable outcomes.

Why erwin for Your Data Intelligence Platform?

Data is all erwin does. It’s all erwin has ever done, and erwin is pretty darn good at it. Comprised of erwin Data Catalog by Quest and erwin Data Literacy by Quest with built-in automation, erwin Data Intelligence gives organizations an accurate picture of their metadata landscapes. Such visibility reduces friction in data accessibility and utility, improves overall quality, underpins governance and accelerates digital transformation as more individuals become data literate and intelligent. With erwin Data Intelligence, you can automate the discovery and assessment of enterprise data assets. In fact, erwin is the only software provider with an automated, metadata-driven approach to meeting enterprise data requirements.

Who needs erwin Data Intelligence?

The right data points — or facts — lead to information, and information — or context — leads to intelligence. When you know what you need to know – or discover what you don’t know – you can move in the right direction. But the lack of visibility and control over “data at rest” in databases, data lakes and data warehouses and “data in motion” as it’s integrated with and used by key applications means organizations spend a lot more time searching for data instead of analyzing it for meaningful insights.

In fact, data professionals spend 85 percent of their time looking for, preparing and protecting data and only 15 percent on analysis, according to IDC. So if data pros are hampered in data analysis, what does that say about the rest of us?

From data analysts, data architects and data stewards to chief executives and business users, erwin Data Intelligence is used by many across the organization to understand, govern, deliver and leverage enterprise data to its fullest advantage. As companies increasingly recognize the role data can play in their evolution, the number of roles requiring more timely, accurate access to data intelligence increases. The convergence of exploding data production, scalable big data computation, and advanced analytics, machine learning and artificial intelligence have given rise to citizen analysts: business-oriented problem-solvers charged with understanding how to apply analytical techniques to massive data sets to identify emergent business opportunities.

Additionally, the prevalence of chief data officers (CDOs) continues to grow to better harmonize data management, governance and consumption efforts to overcome the opaqueness, complexity and siloed nature of enterprise data. Enterprises today must have visibility of their data (and metadata) landscape to harvest, curate and publish data assets available for analysis and reporting. Plus both IT and citizen analysts need access with an understanding of how different data assets can be used along with guidelines for adhering to data policies that best protect the organization.

Benefits of erwin Data Intelligence

erwin Data Intelligence improves data awareness, capability and knowledge to support data governance and business enablement.

Visualization of Any Data From Anywhere

See structured or unstructured enterprise data regardless of location – in a relational or NoSQL database, a data warehouse, whether on-premises or in the cloud – within a single interface.z

Centralized Model Development & Management

An integrated view of conceptual, logical and physical data models helps business and technical stakeholders understand data structures and meaning.

Agile Application Development

Consolidate and build applications with hybrid architectures, including traditional, NoSQL and Big Data, in the cloud and on-premises.

Reduced Risks and Costs

Automation and standardization of data definitions and structures reduces risks and costs, plus you can test changes and new applications before they go into production.

Automated Data Model & Database Schema Gneration

Automatically generate data models and database designs to increase efficiency and reduce errors.

Data Literacy, Collaboration & Accountability

Improve data intelligence and decision-making across the enterprise by maximizing the ability of stakeholders to use, understand and trust relevant data.

Increased Data Quality

By using data models to define and deploy enterprise data standards, you’ll realize more consistency and higher quality in data management.

Successful Cloud Adoption

Automated schema engineering and deployment accelerates and ensures successful adoption of cloud platforms, like Snowflake and Microsoft Azure, including auto documenting existing schema into reusable models.

erwin Data Intelligence Suite Capabilities

Data intelligence refers to the analysis of relevant data in various forms to derive meaningful insights that support strategic decision-making. What could your organization accomplish by automating the collection of data intelligence and putting it into the hands of users who can work together to bring valid ideas across the finish line? erwin Data Intelligence brings together the power of data cataloging, data stewardship, and self-service data discovery in a single software suite.

Discover Data

Identify and interrogate metadata from various data management silos.

Structure and Deploy Data Sources

Connect physical metadata to specific data models, business terms, definitions and reusable design standards.

Map Data Flows and Harvest Data

Identify where to integrate data and document data lineage to understand how it moves and transforms. Automate the collection of metadata from various data management silos and consolidate it into a single source.

Analyze Metadata

Understand how data relates to the business and what attributes it has.

Govern Data

Develop a governance model to manage standards, policies and best practices and associate them with physical assets.

Socialize Data

Empower stakeholders to see data in one place and in the context of their roles.

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