erwin Expert Blog

The Data Governance (R)Evolution

Data governance continues to evolve – and quickly.

Historically, Data Governance 1.0 was siloed within IT and mainly concerned with cataloging data to support search and discovery. However, it fell short in adding value because it neglected the meaning of data assets and their relationships within the wider data landscape.

Then the push for digital transformation and Big Data created the need for DG to come out of IT’s shadows – Data Governance 2.0 was ushered in with principles designed for  modern, data-driven business. This approach acknowledged the demand for collaborative data governance, the tearing down of organizational silos, and spreading responsibilities across more roles.

But this past year we all witnessed a data governance awakening – or as the Wall Street Journal called it, a “global data governance reckoning.” There was tremendous data drama and resulting trauma – from Facebook to Equifax and from Yahoo to Aetna. The list goes on and on. And then, the European Union’s General Data Protection Regulation (GDPR) took effect, with many organizations scrambling to become compliant.

So where are we today?

Simply put, data governance needs to be a ubiquitous part of your company’s culture. Your stakeholders encompass both IT and business users in collaborative relationships, so that makes data governance everyone’s business.

Data Governance is Everyone's Business

Data governance underpins data privacy, security and compliance. Additionally, most organizations don’t use all the data they’re flooded with to reach deeper conclusions about how to grow revenue, achieve regulatory compliance, or make strategic decisions. They face a data dilemma: not knowing what data they have or where some of it is—plus integrating known data in various formats from numerous systems without a way to automate that process.

To accelerate the transformation of business-critical information into accurate and actionable insights, organizations need an automated, real-time, high-quality data pipeline. Then every stakeholder—data scientist, ETL developer, enterprise architect, business analyst, compliance officer, CDO and CEO—can fuel the desired outcomes based on reliable information.

Connecting Data Governance to Your Organization

  1. Data Mapping & Data Governance

The automated generation of the physical embodiment of data lineage—the creation, movement and transformation of transactional and operational data for harmonization and aggregation—provides the best route for enabling stakeholders to understand their data, trust it as a well-governed asset and use it effectively. Being able to quickly document lineage for a standardized, non-technical environment brings business alignment and agility to the task of building and maintaining analytics platforms.

  1. Data Modeling & Data Governance

Data modeling discovers and harvests data schema, and analyzes, represents and communicates data requirements. It synthesizes and standardizes data sources for clarity and consistency to back up governance requirements to use only controlled data. It benefits from the ability to automatically map integrated and cataloged data to and from models, where they can be stored in a central repository for re-use across the organization.

  1. Business Process Modeling & Data Governance

Business process modeling reveals the workflows, business capabilities and applications that use particular data elements. That requires that these assets be appropriately governed components of an integrated data pipeline that rests on automated data lineage and business glossary creation.

  1. Enterprise Architecture & Data Governance

Data flows and architectural diagrams within enterprise architecture benefit from the ability to automatically assess and document the current data architecture. Automatically providing and continuously maintaining business glossary ontologies and integrated data catalogs inform a key part of the governance process.

The EDGE Revolution

 By bringing together enterprise architecturebusiness processdata mapping and data modeling, erwin’s approach to data governance enables organizations to get a handle on how they handle their data and realize its maximum value. With the broadest set of metadata connectors and automated code generation, data mapping and cataloging tools, the erwin EDGE Platform simplifies the total data management and data governance lifecycle.

This single, integrated solution makes it possible to gather business intelligence, conduct IT audits, ensure regulatory compliance and accomplish any other organizational objective by fueling an automated, high-quality and real-time data pipeline.

The erwin EDGE creates an “enterprise data governance experience” that facilitates collaboration between both IT and the business to discover, understand and unlock the value of data both at rest and in motion.

With the erwin EDGE, data management and data governance are unified and mutually supportive of business stakeholders and IT to:

  • 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 data: Connect physical metadata to specific business terms and definitions and reusable design standards.
  • Analyze data: 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.

If you’ve enjoyed this latest blog series, then you’ll want to request a copy of Solving the Enterprise Data Dilemma, our new e-book that highlights how to answer the three most important data management and data governance questions: What data do we have? Where is it? And how do we get value from it?

Solving the Enterprise Data Dilemma

erwin Expert Blog

Getting started with business process modeling: Why am I doing this?

Getting started with business process modeling is better done sooner rather than later. Especially since business processes modeling is essential to a data strategy.

erwin Expert Blog

Basics of Business Process Modeling

Business process modeling is becoming progressively more relevant. Everyday businesses aspire to make organizational changes that will boost their firms and drive them forward.

However to make a change that will really make a difference, you need to have a clear understanding as to what your business currently does – in every area.

As companies move expand quickly, few truly understand the way things are done, and that’s where business process modeling  is vital.

It’s a concept that some aren’t familiar with, so below we’ve summed up some of the frequently asked questions to get you started.

What is business process modeling?

A business process is an activity or set of activities designed to achieve a specific goal, and your organization has thousands of them!

For example, if your company delivers goods to customers, the business process is the numerous steps and actions taken to get the items from your warehouse to the customer.

If you don’t understand what your business processes are, there is a real risk that members of your organization all do things differently – some effectively and efficiently, but others in more time-consuming ways that don’t benefit  your business.

By modeling your business processes, you can know the activities being undertaken and identify the best way to do each one.

What are the benefits of business process modeling?

Most organizations understand what they need to do to get the results that they want, at least at a basic level. But clunky processes, inefficient teams, lack of information and poor communication frequently get in the way.

Employees who spend time fighting fires, hunting for data and reacting to unnecessary roadblocks are prevented from executing your strategic objectives. This is a huge factor in lethargic time to markets and stops businesses from effectively moving forward.

The aim of business process modeling is to standardize your processes and the ways in which people communicate, as well as to improve knowledge sharing.

By doing so, you have a much better understanding of what everyone is doing, you share best practices more effectively, and can implement business changes easier.

How can erwin help with business process modeling?

Working with the chief operational officer, the operations team and others, erwin’s consultants can assist in business process modeling by documenting existing business processes, designing an improved process flow, and building a plan for moving forward with organizational change.

erwin can help you do this simply and swiftly, so you don’t miss out on opportunities for growth. Our workshop approach – with our people and tools – lets us hold up a mirror and do a quick assessment.

We can capture the models and show you a picture of your organization far faster than you can and often in a way you’ve never seen before, giving a third-party objective perspective vital to moving your business forward.

If you would like help you with your business process modeling, get in touch with us today.

Importance of Governing Data