Tag: enterprise architecture

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Takeaways from Forrester’s Latest Report on Enterprise Architecture Management Suites

Forrester recently released its “Now Tech: Enterprise Architecture Management Suites for Q1 2020” to give organizations an enterprise architecture (EA) playbook.

It also highlights select enterprise architecture management suite (EAMS) vendors based on size and functionality, including erwin.

The report notes six primary EA competencies in which we excel in the large vendor category: modeling, strategy translation, risk management, financial management, insights and change management.

Given our EA expertise, we thought we’d provide our perspective on the report’s key takeaways and how we see technology trends, business innovation and compliance driving companies to use EA in different ways.

Enterprise Architecture Management Systems (EAMS)

Improve Enterprise Architecture with EAMS

To an EA professional, it may seem obvious that tools provide “a holistic view of business demand impact.” Delivery of innovation at speed is critical, but what does that really mean?

Not only should EA be easy to adopt and roll out, artifacts should be easy to visualize quickly and effectively by various stakeholders in the format they need to make decisions rapidly.

For “EA stakeholders to be more productive and effective,” not only is a central repository a necessity but collaboration and a persona-driven approach also are critical to the organization’s adoption of EA.

Just as an ERP system is a fundamental part of business operations, so is an enterprise architecture management suite. It’s a living, breathing tool that feeds into and off of the other physical repositories in the organization, such as ServiceNow for CMDB assets, RSA Archer for risk logs, and Oracle NetSuite and Salesforce for financials.

Being able to connect the enterprise architecture management suites to your business operating model will give you “real-time insights into strategy and operations.”

And you can further prove the value of EA with integrations to your data catalog and business glossary with real-time insights into the organization’s entire data landscape.

enterprise architecture innovation management

Select Enterprise Architecture Vendors Based on Size and Functionality

EA has re-emerged to help solve compliance challenges in banking and finance plus drive innovation with artificial intelligence (AI), machine learning (ML) and robotic automation in pharmaceuticals.

These are large organizations with significant challenges, which require an EA vendor to invest in research and development to innovate across their offerings so EA can become a fundamental part of an organization’s operating model.

We see the need for a “proprietary product platform” in the next generation of EA, so customers can create their own products and services to meet their particular business needs.

They’re looking for product management, dev/ops, security modeling, personas and portfolio management all to be part of an integrated EA platform. In addition, customers want to ensure platforms are secure with sound coding practices and testing.

Determine the Key Enterprise Architecture Capabilities Needed

With more than 20 years of EA experience, erwin has seen a lot of changes in the market, many in the last 24 months. Guess what? This evolution isn’t slowing down.

We’re working with some of the world’s largest companies (and some smaller ones too) as they try to manage change in their respective industries and organizations.

Yesterday’s use case may not serve tomorrow’s use case. An EA solution should be agile enough to meet both short-term and long-term needs.

Use EA Performance Measures to Validate Enterprise Architecture Management Suite Value

EA should provide a strong ROI and help an organization derive value and successful business outcomes.

Additionally, a persona-based approach that involves configuring the user interface and experience to suit stakeholder needs eases the need for training.

Formalized training is important for EA professionals and some stakeholders, and the user interface and experience should reduce the need for a dedicated formal training program for those deriving value out of EA.

Why erwin for Enterprise Architecture?

Whether documenting systems and technology, designing processes and value streams, or managing innovation and change, organizations need flexible but powerful enterprise architecture tools they can rely on for collecting the relevant information for decision-making.

Like constructing a building or even a city – you need a blueprint to understand what goes where, how everything fits together to support the structure, where you have room to grow, and if it will be feasible to knock down any walls if you need to.

Without a picture of what’s what and the interdependencies, your enterprise can’t make changes at speed and scale to serve its needs.

erwin Evolve is a full-featured, configurable set of enterprise architecture tools, in addition to business process modeling and analysis.

The combined solution enables organizations to map IT capabilities to the business functions they support and determine how people, processes, data, technologies and applications interact to ensure alignment in achieving enterprise objectives.

See for yourself why we were included in the latest Forrester EAMS report. We’re pleased to offer you a free trial of erwin Evolve.enterprise architecture business process

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erwin Expert Blog

The Value of Enterprise Architecture to Innovation and Digital Transformation

The value of enterprise architecture to innovation management and digital transformation is clear.

Innovation management is about quickly and effectively implementing your organization’s goals through the adoption of innovative ideas, products, processes and business models.

Most organizations are beginning to realize that to drive business growth and maintain a competitive advantage, innovation needs to be uncovered, documented and socialized rapidly but with care to ensure maximum value.

The process of innovation needs to be managed and governed in the organization because it’s an important facet of a company’s overall function. And ultimately, it is a process in which the business and IT need to collaborate to drive the transformation.

Enterprise Architecture

How Enterprise Architecture Guides Innovation and Transformation

Once you develop a good idea, you need to understand how to implement it successfully, which is why enterprise architecture (EA) is a perennial innovation tool.

Investment in a particular idea requires a degree of confidence that a product, service, IT component or business process is going to make it to market or positively change the business.

Conversely, IT requires traceability back to the innovation that drove it. Without such traceability, it’s difficult to see the value of IT and how it drives the business. And to make it all work seamlessly, it needs to be the business of both those who innovate and those who manage EA.

  • Get the eBook: Enterprise Architecture and Innovation Management

Without EA and an enterprise architecture tool, decision-making expanding from the right ideas and requirements is much more of a lottery.

And while there are more and more projects in progress and a rise in agile development approaches, companies simply do not invest enough time in combining innovation and EA.

DevOps and continuous delivery are prime candidates for connection to innovation management. In the context of speed and time to market, where the frequency, capability and release cycles are key to competitive advantage, EA’s support of decision-making allows innovative ideas to be implemented without costly mistakes.

Strategic Enterprise Architecture Planning Creates Digital Leaders

Innovation management and digital transformation go hand in hand these days, and EA teams can play an integral role, according to a study from McKinsey and Henley Business School.

The study highlighted the need for enterprise architects to facilitate digital transformation by managing technological complexity and setting a course for the development of their companies’ IT landscapes.

One of the stunning results of the study was that 100 percent of respondents from companies that identified themselves as “digital leaders” said their architecture teams develop and update models of what the business’s IT architecture should look like in the future.

In contrast, just 58 percent of respondents from other companies said they adhere to this best practice.

There are three broad states of EA maturity within most enterprises. Where does yours land?

1. Under design

  • Does not exist (or is covered by IT)
  • Information barely managed (or managed on an ad-hoc basis)
  • Knowledge resides mainly in people and disparate other media

2. Existing but needs improvement

  • Efforts have been made to collate and manage information
  • In disparate media, but usually more organized
  • A potential attempt at solutioning has been made
  • Some (manual) reporting is possible

3. Mature and works great!

  • Distinct function within the organization
  • Initial data aggregation and collation is completed
  • There is an EA solution deployed and used
  • Dashboards and reports are available

See also:

Enterprise Architecture Turns Around Inefficiencies

Envision a scenario in which you’re part of the EA team at an energy company with 30,000 wind turbines. When engineers inspect the wind turbines, they record the results on paper forms.

An administrator then uses this paperwork to enter information into the database so repairs can be scheduled. This manual, low-tech approach that relies on good penmanship equates to losing 10 days per year due to manual paperwork that delays necessary repairs; and work-order entry makes up about 25 percent of an admin’s day.

How could technology be used to improve this process? Is there an opportunity for digital transformation? Yes.

By deploying tablets in the field, engineers would be able to review the specs and history of each wind turbine in real time, note the necessary repairs, and then specify the work orders onsite. By driving the innovation process with EA, it’s possible to:

  • Demonstrate how different types and groups of users collaborate within the tool from ideation through execution.
  • Graphically illustrate the ideas, people and support for categories of ideation and innovation
  • Leverage mode 2 activities, such as business scenario planning, persona profiles and strategic value assessments as part of the process.
  • Manage iterative solution or application development projects, leveraging methods such as Kanban, agile, scrum or lean, which help the IT organization pursue a DevOps approach.

Enterprise Architecture at the Heart of Innovation

erwin’s technology roadmap is defined largely by our customers, their needs and requirements, and the trends and initiatives that matter most to their businesses. They are constantly evolving, and so are we.

That’s why we’ve released erwin Evolve, a full-featured, configurable set of EA and business process modeling and analysis tools.

With erwin Evolve, you can map IT capabilities to the business functions they support and determine how people, processes, data, technologies and applications interact to ensure alignment in achieving enterprise objectives.

Such initiatives may include innovation management and digital transformation, as well as cloud migration, portfolio and infrastructure rationalization, and regulatory compliance among other use cases.

Click here to test drive erwin Evolve today.

enterprise architecture business process

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erwin Expert Blog Enterprise Architecture

Change Management: Enterprise Architecture for Managing Change

As organization’s technologies and digital strategies mature, enterprise architecture for change management is becoming increasingly relevant. 

Enterprise architecture’s holistic view of the organization is perfect for understanding how an organization’s assets are interconnected. 

This understanding is crucial when an organization is looking to change from within. But it is perhaps even more crucial still, when external factors and disruption force an organization into change.

Ch-ch-ch-ch-changes …

Organizations in every industry are navigating digital transformation, so change management is an important element to consider as part of those efforts.

And organizations that embrace change often achieve greater success.

Whether in the early stages of implementing a digital strategy or in the midst of a new technology deployment, change management plays a crucial role.

What Is Change Management?

Change management describes the process(es) an organization will undertake to ensure changes to business operations, systems and other assets cause as little disruption as possible.

For example, a change in systems might require employees to be retrained, taking them away from more immediate, value-creating tasks.

A systems change also could disrupt business operations more directly – if it turns out a new system is incompatible with the current technology infrastructure.

Why Is Change Management Important?

Organizations are faced with constant change. Even industries historically resistant to it, such as financial services and healthcare, are now transforming proactively and at a rapid rate.

Successfully implementing and managing any change, but especially those involving technology, requires an understanding of how it will impact the business – particularly when there are impacts outside the intended goal.

While good ideas help a business grow, sometimes their implementations cause stumbles. Most often that’s because there’s a disconnect between an innovative idea and how it becomes reality.

Such disconnects result in redundant technology and processes, inefficient use of resources, and/or missed opportunities.

With effective change management, organizations usually realize faster implementations and lower costs. An organization with a better understanding of a proposed change is less likely to run into the problems that can derail new initiatives.

Smart change management also can help organizations future-proof their operations, anticipating issues such as systems becoming redundant or outdated earlier than expected.

Change Management and Enterprise Architecture

In large organizations, enterprise architecture (EA) has long been recognized as an effective mechanism for change management. It facilitates an organization’s efforts in assessing the impact of change and making recommendations for target states that support business objectives.

New solution architectures also are being used to successfully assess solution alternatives to support these target states.

EA often delivers the business use cases that justify the incorporation of ideas into operations. However, organizations may find its success limited if the EA function continues to operate in an ivory tower.

Historically, the EA group often has been disconnected from business stakeholders as well as the IT project teams assigned to deliver the solution. This disconnect can lead to the EA team suffering from a lack of commitment from the wider organization and thus their recommendations are ignored.

As a result, ideas are adopted without rigorous scrutiny, including the impacts of their execution and potential ripple effects on other projects.

What’s needed is an integrated approach that marries the EA team’s knowledge with a process for managing ideas and innovation.

change management enterprise architecture

Using Enterprise Architecture to Manage Ideation Through Implementation

A strategic planning approach – from assessment and impact and investment analysis through delivery – ensures ideas are captured, analyzed and shared in a structured process.

Feedback is provided to the originator, and the right stakeholders are involved in making the right decisions about IT projects based on sound business cases. Then both communities feel empowered to make changes.

An integrated, strategic planning environment brings a federated view of information from across the organization so that it can be shared. It helps organizations analyze and prioritize ideas, feed them into EA for analysis, and compile a business case.

With all stakeholders reviewing information and providing feedback on proposed projects, everyone can understand how the new ideas fit into the corporate strategy and have a voice in systematically managing the changes.

Plus they can be executed in near real time, allowing the organization to react quickly to seize market advantage.

Organizations looking to adopt such an approach to change management would benefit from an enterprise architecture tool.

erwin Evolve is one such enterprise architecture tool and a solution addressing both enterprise architecture and business process modeling and analysis use cases.

Users employ erwin Evolve to effectively tame complexity, manage change and increase operational efficiency. Its many benefits include:

  • Creation & Visualization of Complex Models: Harmonize EA/BP modeling capabilities for greater visibility, control and intelligence in managing any use case.
  • Powerful Analysis: Quickly and easily explore model elements, links and dependencies, plus identify and understand the impact of changes through intuitive impact analysis.
  • Documentation & Knowledge Retention: Capture, document and publish information for key business functions to increase employee education and awareness and maintain institutional knowledge, including standard operating procedures.
  • Democratization & Decision-Making: Break down organizational silos and facilitate enterprise collaboration among those both in IT and business roles for more informed decisions that drive successful outcomes.
  • Agility & Efficiency: Achieve faster time to actionable insights and value with integrated views across initiatives to understand and focus on business outcomes.
  • Lower Risks & Costs: Improve performance and profitability with harmonized, optimized and visible processes to enhance training and lower IT costs.

Recent enhancements include web-based diagramming for non-IT users, stronger document generation and analytics, TOGAF support, improved modeling and navigation through inferred relationships, new API extensions, and modular packaging so customers can choose the components that best meet their needs.

Try erwin Evolve now with a free, cloud-based trial – your work will be saved and carried over when you buy.

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Enterprise Architecture and Business Process Modeling Tools Have Evolved

Enterprise architecture (EA) and business process (BP) modeling tools are evolving at a rapid pace. They are being employed more strategically across the wider organization to transform some of business’s most important value streams.

Recently, Glassdoor named enterprise architecture the top tech job in the UK, indicating its increasing importance to the enterprise in the tech and data-driven world.

Whether documenting systems and technology, designing processes and value streams, or managing innovation and change, organizations need flexible but powerful EA and BP tools they can rely on for collecting relevant information for decision-making.

It’s like constructing a building or even a city – you need a blueprint to understand what goes where, how everything fits together to support the structure, where you have room to grow, and if it will be feasible to knock down any walls if you need to.

 

Data-Driven Enterprise Architecture

 

Without a picture of what’s what and the interdependencies, your enterprise can’t make changes at speed and scale to serve its needs.

Recognizing this evolution, erwin has enhanced and repackaged its EA/BP platform as erwin Evolve.

The combined solution enables organizations to map IT capabilities to the business functions they support and determine how people, processes, data, technologies and applications interact to ensure alignment in achieving enterprise objectives.

These initiatives can include digital transformation, cloud migration, portfolio and infrastructure rationalization, regulatory compliance, mergers and acquisitions, and innovation management.

Regulatory Compliance Through Enterprise Architecture & Business Process Modeling Software

A North American banking group is using erwin Evolve to integrate information across the organization and provide better governance to boost business agility. Developing a shared repository was key to aligning IT systems to accomplish business strategies, reducing the time it takes to make decisions, and accelerating solution delivery.

It also operationalizes and governs mission-critical information by making it available to the wider enterprise at the right levels to identify synergies and ensure the appropriate collaboration.

EA and BP modeling are both critical for risk management and regulatory compliance, a major concern for financial services customers like the one above when it comes to ever-changing regulations on money laundering, fraud and more. erwin helps model, manage and transform mission-critical value streams across industries, as well as identify sensitive information.

Additionally, when thousands of employees need to know what compliance processes to follow, such as those associated with regulations like the General Data Protection Regulation (GDPR), ensuring not only access to proper documentation but current, updated information is critical.

The Advantages of Enterprise Architecture & Business Process Modeling from erwin

The power to adapt the EA/BP platform leads global giants in critical infrastructure, financial services, healthcare, manufacturing and pharmaceuticals to deploy what is now erwin Evolve for both EA and BP use cases. Its unique advantages are:

  • Integrated, Web-Based Modeling & Diagramming: Harmonize EA/BP capabilities with a robust, flexible and web-based modeling and diagramming interface easy for all stakeholders to use.
  • High-Performance, Scalable & Centralized Repository: See an integrated set of views for EA and BP content in a central, enterprise-strength repository capable of supporting thousands of global users.
  • Configurable Platform with Role-Based Views: Configure the metamodel, frameworks and user interface for an integrated, single source of truth with different views for different stakeholders based on their roles and information needs.
  • Visualizations & Dashboards: View mission-critical data in the central repository in the form of user-friendly automated visualizations, dashboards and diagrams.
  • Third-Party Integrations: Synchronize data with such enterprise applications as CAST, Cloud Health, RSA Archer, ServiceNow and Zendesk.
  • Professional Services: Tap into the knowledge of our veteran EA and BP consultants for help with customizations and integrations, including support for ArchiMate.

erwin Evolve 2020’s specific enhancements include web-based diagramming for non-IT users, stronger document generation and analytics, TOGAF support, improved modeling and navigation through inferred relationships, new API extensions, and modular packaging so customers can choose the components that best meet their needs.

erwin Evolve is also part of the erwin EDGE with data modeling, data catalog and data literacy capabilities for overall data intelligence.

enterprise architecture business process

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A Guide to Enterprise Architecture Tools

Enterprise architecture tools are becoming more important than ever.

The International Enterprise Architecture Institute (IEAI) defines enterprise architecture (EA) as “the analysis and documentation of an enterprise in its current and future states from an integrated strategy, business and technology perspective.”

In the era of data-driven business, such perspective is critical.

IT has graduated from a support department to a proactive, value-driving function. As such, fostering alignment between IT and the wider organization has become more important than ever.

As the IEAI’s definition indicates, enterprise architecture tools are key drivers in ensuring such alignment because they help organizations understand their systems, applications and assets from a holistic, top-down perspective.

An organization can better identify gaps in its current architecture to better understand how to reach the desired future-state objectives and architecture.

Enterprise Architecture Tools

EA also enables a better understanding of change, or impact analysis – which is essential considering the agile, data-driven landscape and its state of flux.

Enterprise architecture tools allow an organization to map its applications – complete with their associated technologies and data – to the business functions they power.

For this reason, enterprise architecture tools also are key to a data governance initiative, and part of the technologies used as data governance tools.

EA leads to a greater understanding of the interdependencies of its data assets and enables an organization to better plan, budget and execute new strategy and ideas.

In addition to better impact analysis and ensuring IT-business alignment, enterprise architecture tools help organizations:

  • Model and integrate complex strategy, process, application, data and technology architectures
  • Collaborate with all stakeholders on innovation and transformation initiatives
  • Retain organizational knowledge

Enterprise architecture initially was housed within IT and therefore acted in an enterprise support role as well.

However, this led to the perception (and arguably, a reality) of enterprise architecture operating in an ivory tower, siloed from the wider business.

As problematic as that was in the years prior to the data-driven business surge, such problems have intensified in its wake.

Changing such a perception is critical for organizations looking to implement or mature an EA initiative.

Enterprise architecture tools with a greater emphasis on collaboration have been an excellent driver of such change.

With such enterprise architecture tools in place, organizations and their enterprise architects can employ more proactive, business outcome-oriented and value-driving applications for EA.

The Changing Role of the Enterprise Architect

The centralization of enterprise architecture has presented enterprise architects with new opportunities.

The role itself has become less pigeon-holed since outgrowing its IT silo. In fact, the enterprise architecture role itself has become less definable.

Now, organizations tend to organize enterprise architects in whatever way best serves their goals.

In an enterprise architecture team, each team member often will have some role-specific knowledge and then take the lead in managing that particular area.

For example, cases have been made for enterprise architects taking a seat at the security table.

And considering the growing importance of EA in the constantly changing data-driven business landscape, strong arguments can be made for enterprise architects reporting directly to the C-suite.

Like the tech industry in general, the only constant in enterprise architecture is change. Roles and titles will continue to evolve to meet new challenges in the face of digital transformation.

In recent years, enterprise architects and enterprise architecture tools are increasingly more involved in ideation and innovation management.

Marcus Blosch, Vice President Analyst at Gartner, spoke to this: “By 2021, 40 percent of organizations will use enterprise architects to help ideate new business innovations made possible by emerging technologies.”

But changes to the way EA is applied require enterprise architects to change also. Thus, enterprise architects now have to ensure they’re not solely focussed on the standard EA framework.

Although such an approach might be useful to enterprise architects, it doesn’t necessarily translate to the wider business.

Enterprise architects adopting a more business-outcome approach to the way they work helps them better demonstrate the value of EA people outside its echo chamber.

Additionally, enterprise architects must recognize that today their work is never “finished.”

Too many enterprise architecture initiatives stall because of what we call “analysis paralysis.”

In a blog for Medium, Believe Success defined analysis paralysis as “an anti-pattern, the state of over-analyzing (or over-thinking) a situation so that a decision or action is never taken, in effect paralyzing the outcome.”

To avoid such a state, enterprise architects in the data-driven world must adopt a “just enough” approach to enterprise architecture.

The “just-enough” approach ensures EA is always focused on improving operations for the right business outcomes, not bogged down in analysis and jargon that does not translate to the wider organization.

As part of our wider Enterprise Data Governance Experience (EDGE) platform, erwin provides enterprise architecture tools tailor-made to meet the needs of the modern enterprise architect, as outlined above.

Click here for a free, full-featured, cloud-based trial of erwin EA powered by Casewise.

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Data Governance Makes Data Security Less Scary

Happy Halloween!

Do you know where your data is? What data you have? Who has had access to it?

These can be frightening questions for an organization to answer.

Add to the mix the potential for a data breach followed by non-compliance, reputational damage and financial penalties and a real horror story could unfold.

In fact, we’ve seen some frightening ones play out already:

  1. Google’s record GDPR fine – France’s data privacy enforcement agency hit the tech giant with a $57 million penalty in early 2019 – more than 80 times the steepest fine the U.K.’s Information Commissioner’s Office had levied against both Facebook and Equifax for their data breaches.
  2. In July 2019, British Airways received the biggest GDPR fine to date ($229 million) because the data of more than 500,000 customers was compromised.
  3. Marriot International was fined $123 million, or 1.5 percent of its global annual revenue, because 330 million hotel guests were affected by a breach in 2018.

Now, as Cybersecurity Awareness Month comes to a close – and ghosts and goblins roam the streets – we thought it a good time to resurrect some guidance on how data governance can make data security less scary.

We don’t want you to be caught off guard when it comes to protecting sensitive data and staying compliant with data regulations.

Data Governance Makes Data Security Less Scary

Don’t Scream; You Can Protect Your Sensitive Data

It’s easier to protect sensitive data when you know what it is, where it’s stored and how it needs to be governed.

Data security incidents may be the result of not having a true data governance foundation that makes it possible to understand the context of data – what assets exist and where, the relationship between them and enterprise systems and processes, and how and by what authorized parties data is used.

That knowledge is critical to supporting efforts to keep relevant data secure and private.

Without data governance, organizations don’t have visibility of the full data landscape – linkages, processes, people and so on – to propel more context-sensitive security architectures that can better assure expectations around user and corporate data privacy. In sum, they lack the ability to connect the dots across governance, security and privacy – and to act accordingly.

This addresses these fundamental questions:

  1. What private data do we store and how is it used?
  2. Who has access and permissions to the data?
  3. What data do we have and where is it?

Where Are the Skeletons?

Data is a critical asset used to operate, manage and grow a business. While sometimes at rest in databases, data lakes and data warehouses; a large percentage is federated and integrated across the enterprise, introducing governance, manageability and risk issues that must be managed.

Knowing where sensitive data is located and properly governing it with policy rules, impact analysis and lineage views is critical for risk management, data audits and regulatory compliance.

However, when key data isn’t discovered, harvested, cataloged, defined and standardized as part of integration processes, audits may be flawed and therefore your organization is at risk.

Sensitive data – at rest or in motion – that exists in various forms across multiple systems must be automatically tagged, its lineage automatically documented, and its flows depicted so that it is easily found and its usage across workflows easily traced.

Thankfully, tools are available to help automate the scanning, detection and tagging of sensitive data by:

  • Monitoring and controlling sensitive data: Better visibility and control across the enterprise to identify data security threats and reduce associated risks
  • Enriching business data elements for sensitive data discovery: Comprehensively defining business data element for PII, PHI and PCI across database systems, cloud and Big Data stores to easily identify sensitive data based on a set of algorithms and data patterns
  • Providing metadata and value-based analysis: Discovery and classification of sensitive data based on metadata and data value patterns and algorithms. Organizations can define business data elements and rules to identify and locate sensitive data including PII, PHI, PCI and other sensitive information.

No Hocus Pocus

Truly understanding an organization’s data, including its value and quality, requires a harmonized approach embedded in business processes and enterprise architecture.

Such an integrated enterprise data governance experience helps organizations understand what data they have, where it is, where it came from, its value, its quality and how it’s used and accessed by people and applications.

An ounce of prevention is worth a pound of cure  – from the painstaking process of identifying what happened and why to notifying customers their data and thus their trust in your organization has been compromised.

A well-formed security architecture that is driven by and aligned by data intelligence is your best defense. However, if there is nefarious intent, a hacker will find a way. So being prepared means you can minimize your risk exposure and the damage to your reputation.

Multiple components must be considered to effectively support a data governance, security and privacy trinity. They are:

  1. Data models
  2. Enterprise architecture
  3. Business process models

Creating policies for data handling and accountability and driving culture change so people understand how to properly work with data are two important components of a data governance initiative, as is the technology for proactively managing data assets.

Without the ability to harvest metadata schemas and business terms; analyze data attributes and relationships; impose structure on definitions; and view all data in one place according to each user’s role within the enterprise, businesses will be hard pressed to stay in step with governance standards and best practices around security and privacy.

As a consequence, the private information held within organizations will continue to be at risk.

Organizations suffering data breaches will be deprived of the benefits they had hoped to realize from the money spent on security technologies and the time invested in developing data privacy classifications.

They also may face heavy fines and other financial, not to mention PR, penalties.

Gartner Magic Quadrant Metadata Management

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Very Meta … Unlocking Data’s Potential with Metadata Management Solutions

Untapped data, if mined, represents tremendous potential for your organization. While there has been a lot of talk about big data over the years, the real hero in unlocking the value of enterprise data is metadata, or the data about the data.

However, most organizations don’t use all the data they’re flooded with to reach deeper conclusions about how to drive revenue, achieve regulatory compliance or make other strategic decisions. They don’t know exactly what data they have or even where some of it is.

Quite honestly, knowing what data you have and where it lives is complicated. And to truly understand it, you need to be able to create and sustain an enterprise-wide view of and easy access to underlying metadata.

This isn’t an easy task. Organizations are dealing with numerous data types and data sources that were never designed to work together and data infrastructures that have been cobbled together over time with disparate technologies, poor documentation and with little thought for downstream integration.

As a result, the applications and initiatives that depend on a solid data infrastructure may be compromised, leading to faulty analysis and insights.

Metadata Is the Heart of Data Intelligence

A recent IDC Innovators: Data Intelligence Report says that getting answers to such questions as “where is my data, where has it been, and who has access to it” requires harnessing the power of metadata.

Metadata is generated every time data is captured at a source, accessed by users, moves through an organization, and then is profiled, cleansed, aggregated, augmented and used for analytics to guide operational or strategic decision-making.

In fact, data professionals spend 80 percent of their time looking for and preparing data and only 20 percent of their time on analysis, according to IDC.

To flip this 80/20 rule, they need an automated metadata management solution for:

• Discovering data – Identify and interrogate metadata from various data management silos.
• Harvesting data – Automate the collection of metadata from various data management silos and consolidate it into a single source.
• Structuring and deploying data sources – Connect physical metadata to specific data models, business terms, definitions and reusable design standards.
• Analyzing metadata – Understand how data relates to the business and what attributes it has.
• Mapping data flows – Identify where to integrate data and track how it moves and transforms.
• Governing data – Develop a governance model to manage standards, policies and best practices and associate them with physical assets.
• Socializing data – Empower stakeholders to see data in one place and in the context of their roles.

Addressing the Complexities of Metadata Management

The complexities of metadata management can be addressed with a strong data management strategy coupled with metadata management software to enable the data quality the business requires.

This encompasses data cataloging (integration of data sets from various sources), mapping, versioning, business rules and glossary maintenance, and metadata management (associations and lineage).

erwin has developed the only data intelligence platform that provides organizations with a complete and contextual depiction of the entire metadata landscape.

It is the only solution that can automatically harvest, transform and feed metadata from operational processes, business applications and data models into a central data catalog and then made accessible and understandable within the context of role-based views.

erwin’s ability to integrate and continuously refresh metadata from an organization’s entire data ecosystem, including business processes, enterprise architecture and data architecture, forms the foundation for enterprise-wide data discovery, literacy, governance and strategic usage.

Organizations then can take a data-driven approach to business transformation, speed to insights, and risk management.
With erwin, organizations can:

1. Deliver a trusted metadata foundation through automated metadata harvesting and cataloging
2. Standardize data management processes through a metadata-driven approach
3. Centralize data-driven projects around centralized metadata for planning and visibility
4. Accelerate data preparation and delivery through metadata-driven automation
5. Master data management platforms through metadata abstraction
6. Accelerate data literacy through contextual metadata enrichment and integration
7. Leverage a metadata repository to derive lineage, impact analysis and enable audit/oversight ability

With erwin Data Intelligence as part of the erwin EDGE platform, you know what data you have, where it is, where it’s been and how it transformed along the way, plus you can understand sensitivities and risks.

With an automated, real-time, high-quality data pipeline, enterprise stakeholders can base strategic decisions on a full inventory of reliable information.

Many of our customers are hard at work addressing metadata management challenges, and that’s why erwin was Named a Leader in Gartner’s “2019 Magic Quadrant for Metadata Management Solutions.”

Gartner Magic Quadrant Metadata Management

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Top Use Cases for Enterprise Architecture: Architect Everything

Architect Everything: New use cases for enterprise architecture are increasing enterprise architect’s stock in data-driven business

As enterprise architecture has evolved, so to have the use cases for enterprise architecture.

Analyst firm Ovum recently released a new report titled Ovum Market Radar: Enterprise Architecture. In it, they make the case that enterprise architecture (EA) is becoming AE – or “architect everything”.

The transition highlights enterprise architecture’s evolution from being solely an IT function to being more closely aligned with the business. As such, the function has changed from EA to AE.

At erwin, we’re definitely witnessing this EA evolution as more and more as organizations undertake digital transformation initiatives, including rearchitecting their business models and value streams, as well as responding to increasing regulatory pressures.

This is because EA provides the right information to the right people at the right time for smarter decision-making.

Following are some of the top use cases for enterprise architecture that demonstrate how EA is moving beyond IT and into the business.

Enterprise Architecture Use Cases

Top 7 Use Cases for Enterprise Architecture

Compliance. Enterprise architecture is critical for regulatory compliance. It helps model, manage and transform mission-critical value streams across industries, as well as identify sensitive information. When thousands of employees need to know what compliance processes to follow, such as those associated with regulations (e.g., GDPR, HIPAA, SOX, CCPA, etc.) it ensures not only access to proper documentation but also current, updated information.

The Regulatory Rationale for Integrating Data Management & Data Governance

Data security/risk management. EA should be commonplace in data security planning. Any flaw in the way data is stored or monitored is a potential ‘in’ for a breach, and so businesses have to ensure security surrounding sensitive information is thorough and covers the whole business. Security should be proactive, not reactive, which is why EA should be a huge part of security planning.

Data governance. Today’s enterprise embraces data governance to drive data opportunities, including growing revenue, and limit data risks, including regulatory and compliance gaffes.

EA solutions that provide much-needed insight into the relationship between data assets and applications make it possible to appropriately direct data usage and flows, as well as focus greater attention, if warranted, on applications where data use delivers optimal business value.

Digital transformation. For an organization to successfully embrace change, innovation, EA and project delivery need to be intertwined and traceable. Enterprise architects are crucial to delivering innovation. Taking an idea from concept to delivery requires strategic planning and the ability to execute. An enterprise architecture roadmap can help focus such plans and many organizations are now utilizing them to prepare their enterprise architectures for 5G.

Mergers & acquisitions. Enterprise architecture is essential to successful mergers and acquisitions. It helps alignment by providing a business- outcome perspective for IT and guiding transformation. It also helps define strategy and models, improving interdepartmental cohesion and communication.

In an M&A scenario, businesses need to ensure their systems are fully documented and rationalized. This way they can comb through their inventories to make more informed decisions about which systems to cut or phase out to operate more efficiently.

Innovation management. EA is crucial to innovation and project delivery. Using open standards to link to other products within the overall project lifecycle, integrating agile enterprise architecture with agile development and connecting project delivery with effective governance.

It takes a rigorous approach to ensure that current and future states are published for a wider audience for consumption and collaboration – from modeling to generating road maps with meaningful insights provided to both technical and business stakeholders during every step.

Knowledge retention. Unlocking knowledge and then putting systems in place to retain that knowledge is a key benefit of EA. Many organizations lack a structured approach for gathering and investigating employee ideas. Ideas can fall into a black hole where they don’t get feedback and employees become less engaged.

When your enterprise architecture is aligned with your business outcomes, it provides a way to help your business ideate and investigate the viability of ideas on both the technical and business level.

If the benefits of enterprise architecture would help your business, here’s how you can try erwin EA for free.

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erwin Expert Blog Enterprise Architecture

Top 3 Benefits of Enterprise Architecture

Benefits of Enterprise Architecture

Enterprise architecture (EA) benefits modern organizations in many ways. It provides a holistic, top down view of structure and systems, making it invaluable in managing the complexities of data-driven business.

Once considered solely a function of IT, enterprise architecture has historically operated from an ivory tower. It was often siloed from the business at large, stifling the potential benefits of the holistic view it could have provided.

Now, the growing importance of EA is reflected in its evolving position in the business. Instead of being considered just a function of IT, EA now plays a leading role in bridging the gap between IT and the business.

The practice has evolved in approach, too. In the past, enterprise architecture has played a foundational, support role – largely focused with “keeping the lights on.”

Today its scope is more progressive and business outcome-focused to identify opportunities for growth and change.

As a matter of fact, Gartner has said that EA is becoming a “form of internal management consulting” because it helps define and shape business and operating models, identify risk and opportunities, and create technology roadmaps to suit.

Analyst firm Ovum also recognizes EA’s evolution, referring to today’s EA as AE, or “architect everything,” further demonstrating its newfound scope.

 

Top Three Enterprise Architecture Benefits

Of course, enterprise architecture can’t sit at the strategy table without results. Following are what we believe to be the top three benefits of enterprise architecture:

1. Manage complexity

Modern organizations are a complicated mesh of different systems and applications of varying degrees of importance and prominence.

The top-down, holistic view of an organization provided by enterprise architecture means that organizations are more able to efficiently and confidently assess such assets. For example, impact analysis might identify areas where an organization can streamline its tech stack and cut costs.

It might uncover redundancies where multiple applications address the same process.

Alternatively, impact analysis might find that a seemingly less prominent application is actual integral to operations in circumstances where leadership are considering phasing it out.

In short, enterprise architecture helps business and IT leaders capture, understand and articulate opportunities, challenges and risks – including security.

2. Supporting the creation of actionable, signature-ready EA deliverables

As well as assessing an organization’s current capabilities, the holistic, top-down view provided by enterprise architecture also helps identify gaps.

A better understanding of its enterprise architecture means an organization can make more informed investment decisions. Of course, this means organizations have a better understanding of what they should invest in.

However, it also helps them better understand when, as more pressing concerns can be identified and roadmaps can be created to reflect an organization’s priorities. 

This approach helps an organization meet its current operational demands and opportunities, whilst navigating and mitigating disruptions. It can also ensure it does this in accordance with the longer-term strategic vision of the organization.

3. Increasing agility and speeding time to value

In the era of rapidly evolving technology and rampant – often disruptive – digital transformation, the need for enterprise architecture tools is abundantly clear. Organizations with a healthy understanding of their enterprise architecture are better equipped to evaluate and implement new technology in a timely and efficient manner. 

EA tools accelerate analysis and decision support for alternative investment, rationalization, and optimization opportunities and plans and for assessing risk, change and the impact on the organization.

Maturing Enterprise Architecture

To reap such benefits of this new approach to EA, many organizations will have to work to mature their practices.

To be effective, business outcome-focused enterprise architecture needs to be consistent. It needs to be communicable and discernible. It needs to be up to date and accurate.

For many organizations, these standards have been impossible to meet as their enterprise architectures are burdened by the use of systems that were not built for purpose.

Basic visualization tools, spreadsheets and even word processors have typically played stand-in for dedicated EA solutions. The non-purpose-built systems lacked the industry standards needed to accurately capture and align business and IT elements and how they link together.

Additionally, collaboration was often marred by issues with outdated, and even disparate file versions and types. This being due to business’ lacking the systems necessary to continuously and methodically maintain models, frameworks and concepts as they evolve.

Therefore, a key milestone in maturing a modern enterprise architecture initiative, is developing a single source of truth, consistent across the enterprise. This requires the implementation of a dedicated, centralized and collaborative enterprise architecture tool, be that on-premise, or via the cloud.

Of course, such a tool should cover enterprise architecture’s legacy capabilities and expectations. Those include support for industry standard frameworks and notation, the ability to perform impact analysis and the streamlining of systems and applications.

But to mature the practice, organizations should implement an EA tool with a shared, centralized metadata repository and role-based access.

It should have the ability to share an integrated set of views and information on strategy, business capabilities, applications, information assets, technologies, etc., to help provide stakeholders with a thorough understanding of the enterprise.

Once this milestone has been met, organizations can really begin to enjoy the benefits of enterprise architecture, in the modern, data-driven business context.

If the benefits of enterprise architecture would help your business, and you’d like to be the next erwin EA success story, try erwin’s enterprise architecture and business process modeling software for free.

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Business Process Can Make or Break Data Governance

Data governance isn’t a one-off project with a defined endpoint. It’s an on-going initiative that requires active engagement from executives and business leaders.

Data governance, today, comes back to the ability to understand critical enterprise data within a business context, track its physical existence and lineage, and maximize its value while ensuring quality and security.

Free Data Modeling Best Practice Guide

Historically, little attention has focused on what can literally make or break any data governance initiative — turning it from a launchpad for competitive advantage to a recipe for disaster. Data governance success hinges on business process modeling and enterprise architecture.

To put it even more bluntly, successful data governance* must start with business process modeling and analysis.

*See: Three Steps to Successful & Sustainable Data Governance Implementation

Business Process Data Governance

Passing the Data Governance Ball

For years, data governance was the volleyball passed back and forth over the net between IT and the business, with neither side truly owning it. However, once an organization understands that IT and the business are both responsible for data, it needs to develop a comprehensive, holistic strategy for data governance that is capable of four things:

  1. Reaching every stakeholder in the process
  2. Providing a platform for understanding and governing trusted data assets
  3. Delivering the greatest benefit from data wherever it lives, while minimizing risk
  4. Helping users understand the impact of changes made to a specific data element across the enterprise.

To accomplish this, a modern data governance strategy needs to be interdisciplinary to break down traditional silos. Enterprise architecture is important because it aligns IT and the business, mapping a company’s applications and the associated technologies and data to the business functions and value streams they enable.

Ovum Market Radar: Enterprise Architecture

The business process and analysis component is vital because it defines how the business operates and ensures employees understand and are accountable for carrying out the processes for which they are responsible. Enterprises can clearly define, map and analyze workflows and build models to drive process improvement, as well as identify business practices susceptible to the greatest security, compliance or other risks and where controls are most needed to mitigate exposures.

Slow Down, Ask Questions

In a rush to implement a data governance methodology and system, organizations can forget that a system must serve a process – and be governed/controlled by one.

To choose the correct system and implement it effectively and efficiently, you must know – in every detail – all the processes it will impact. You need to ask these important questions:

  1. How will it impact them?
  2. Who needs to be involved?
  3. When do they need to be involved?

These questions are the same ones we ask in data governance. They involve impact analysis, ownership and accountability, control and traceability – all of which effectively documented and managed business processes enable.

Data sets are not important in and of themselves. Data sets become important in terms of how they are used, who uses them and what their use is – and all this information is described in the processes that generate, manipulate and use them. So unless we know what those processes are, how can any data governance implementation be complete or successful?

Processes need to be open and shared in a concise, consistent way so all parts of the organization can investigate, ask questions, and then add their feedback and information layers. In other words, processes need to be alive and central to the organization because only then will the use of data and data governance be truly effective.

A Failure to Communicate

Consider this scenario: We’ve perfectly captured our data lineage, so we know what our data sets mean, how they’re connected, and who’s responsible for them – not a simple task but a massive win for any organization. Now a breach occurs. Will any of the above information tell us why it happened? Or where? No! It will tell us what else is affected and who can manage the data layer(s), but unless we find and address the process failure that led to the breach, it is guaranteed to happen again.

By knowing where data is used – the processes that use and manage it – we can quickly, even instantly, identify where a failure occurs. Starting with data lineage (meaning our forensic analysis starts from our data governance system), we can identify the source and destination processes and the associated impacts throughout the organization.

We can know which processes need to change and how. We can anticipate the pending disruptions to our operations and, more to the point, the costs involved in mitigating and/or addressing them.

But knowing all the above requires that our processes – our essential and operational business architecture – be accurately captured and modelled. Instituting data governance without processes is like building a castle on sand.

Rethinking Business Process Modeling and Analysis

Modern organizations need a business process modeling and analysis tool with easy access to all the operational layers across the organization – from high-level business architecture all the way down to data.

Such a system should be flexible, adjustable, easy-to-use and capable of supporting multiple layers simultaneously, allowing users to start in their comfort zones and mature as they work toward their organization’s goals.

The erwin EDGE is one of the most comprehensive software platforms for managing an organization’s data governance and business process initiatives, as well as the whole data architecture. It allows natural, organic growth throughout the organization and the assimilation of data governance and business process management under the same platform provides a unique data governance experience because of its integrated, collaborative approach.

Start your free, cloud-based trial of erwin Business Process and see how some of the world’s largest enterprises have benefited from its centralized repository and integrated, role-based views.

We’d also be happy to show you our data governance software, which includes data cataloging and data literacy capabilities.

Enterprise Architecture Business Process Trial