Creating an EDGE - Enterprise Data Governance Experience
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Industry is challenged to ride the Big Data tidal wave. The average organization doesn’t use half of its structured data in decision-making, and less than one percent of unstructured data is analyzed or used at all, according to Harvard Business Review. That’s a lot of untapped, ungoverned data assets and therefore unmitigated risks and missed opportunities. However, if data is accessible, reliable and actionable, it can drive serious results – from regulatory compliance (think GDPR) to topline revenue. So, forget everything you know about data governance as it’s been practiced until now. It’s time to adopt a persona-based approach that joins IT and business functions to ensure organizational objectives are met with everyone – from executives on down – invested in and accountable for data use. Creating such an end-to-end enterprise data governance experience makes data governance everyone’s business. Then they can manage data’s downsides while maximizing its upsides for optimal organizational performance.
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Join Bob Seiner for a webinar that focuses on the governance of metadata following the non-invasive approach. In this session, Bob will share tips and techniques for assuring that the appropriate metadata is being collected and utilized to support your Data Governance program.
In this webinar, Bob will discuss:
Concepts of Non-Invasive Metadata Governance
Metadata as a valuable data resource
Aligning Data Governance with Metadata Governance
Implementing effective Metadata Governance tools
Maximizing metadata resources with accountability
The Essentials of Data Governance in the New Normal
This document provides an overview of data governance and how to implement it within an organization. It discusses why data governance is important, especially in a post-COVID era, and the impacts of not having it. It defines the key components of a data governance organizing framework including strategy, directives, organization, technology, measurement, and change management. It then discusses how to practically implement data governance using an agile embedded approach and considering it as a business capability. Critical success factors and 5 key takeaways are also presented.
Slides: Powering a Sustainable Data Governance Program – Learnings & Best Pra...
This document summarizes a presentation about E.ON Energy's data governance program. E.ON implemented a metadata management platform and data governance practices to address issues like limited data access, lack of a data catalog, and inefficient data usage. Initial results included defining data domains, connecting systems, training users, and standardizing reporting. The program aims to accelerate value from data, ensure compliance, demand trusted insights, and foster collaboration across the organization. Senior leaders must engage to support such initiatives, and building a data-driven culture is key to success.
Data Governance Best Practices and Lessons Learned
Best practices and lessons learned are powerful tools used to assess an organization’s readiness and initial activities associated with delivering a Data Governance program. There are two criteria to determine if something is best practice for your organization. And the definition of data governance best practice is best way to learn from others and begin with the end in mind.
Bob Seiner will share industry data governance best practices in this month’s installment of the RWDG webinar series. Learn how to use the best practices defined in this webinar to address opportunities to improve your organization’s data governance implementation. Attend this webinar and learn that assessing your organization may not be as difficult as you think.
During this webinar Bob will discuss:
How to define data governance best practices for your organization
Criteria used to determine if a practice is best practice
How to assess your organization against industry best practice
Assessing risks associated with best practice gaps
Addressing opportunities to improve gaps uncovered in the assessment
Big Data Strategies – Organizational Structure and Technology
Many CDOs and Data Scientists came into being as part of a Big Data program. In many shops Big Data is the core driver for better Data Governance (DG) and Data Management (DM), and the sole evidence of the value of DM and DG. Big Data is also leaving the “hype cycle” and becoming embedded as part of the DM tool kit.
This webinar will review what is working and what is not working in the Big Data realm. John and Kelle will not only address the technology progress, but also the organizational and management lessons learned, and will present what works and what does not.
In this webinar we will cover:
The state of Hadoop, MapReduce and the other “old” big data technologies
New technologies and approaches
An overview of organization and management of big data functions
Data Governance and Metadata Management
Metadata is a tool that improves data understanding, builds end-user confidence, and improves the return on investment in every asset associated with becoming a data-centric organization. Metadata’s use has expanded beyond “data about data” to cover every phase of data analytics, protection, and quality improvement. Data Governance and metadata are connected at the hip in every way possible. As the song goes, “You can’t have one without the other.”
In this RWDG webinar, Bob Seiner will provide a way to renew your energy by focusing on the valuable asset that can make or break your Data Governance program’s success. The truth is metadata is already inherent in your data environment, and it can be leveraged by making it available to all levels of the organization. At issue is finding the most appropriate ways to leverage and share metadata to improve data value and protection.
Throughout this webinar, Bob will share information about:
- Delivering an improved definition of metadata
- Communicating the relationship between successful governance and metadata
- Getting your business community to embrace the need for metadata
- Determining the metadata that will provide the most bang for your bucks
- The importance of Metadata Management to becoming data-centric
Enterprise Data World Webinar: How to Get Your MDM Program Up & Running
How to get your MDM program up & running”
This session will deliver a Master Data Management primer to introduce:
Master vs Reference data
Multi vs Single domain MDM solutions
A MDM reference architecture and
MDM implementation architectures
This will be illustrated with a real world example from describing how to identify & justify the appropriate data subjects areas that are right for mastering and how to align an MDM initiative with in-flight business initiatives and make the business case.
RWDG Slides: Data Architecture Is Data Governance
Data Architecture and Data Governance are the same thing! Aren’t they?
Most people would say that this line of thinking is absurd — or even worse. There is NO WAY that they are the same thing. Or are they?
This RWDG webinar with Bob Seiner and his special guest Anthony Algmin looks at the disciplines of Data Governance and Data Architecture and explores how much they are the same … and how they are different. The speakers will let you draw your own conclusion, but they will get you thinking about whether Data Architecture and Data Governance are two sides of the same coin.
In this webinar, Bob and Anthony will discuss:
• What is meant by the saying two sides of the same coin … and how it relates
• The similarities between Data Architecture and Data Governance
• The differences between the two
• How to use Data Architecture to sell Data Governance … and the other way around
• Deciding if the two disciplines are the same … or different
RWDG Slides: Stay Non-Invasive in Your Data Governance Approach
There are three distinct approaches to implement Data Governance. The Command-and-Control Approach, the Traditional (if you build it they will come) Approach and the Non-Invasive Data Governance Approach. Some organizations select a single approach for their program while others select to follow a hybrid method.
Bob Seiner will provide information about each approach and indicate how the Non-Invasive Approach can follow the path of least resistance with the greatest success. You may be surprised to learn that many of your present activities can be leveraged to address Stewardship, Metadata, and governed processes – all directed at staying as non-invasive as possible.
In this webinar, Bob will discuss:
- A Data Governance framework completed in a Non-Invasive way
- How the three approaches differ and when to use each
- Sticking to a single approach versus implementing a hybrid model
- How to sell Data Governance as something you are already doing
- Using the Non-Invasive Approach to win friends and influence people.
Data-Ed Webinar: The Seven Deadly Data Sins - Emerging from Management Purgatory
While wrath and envy are best left for human resources to address, overcoming the numerous obstacles that often inhibit successful data management must be a full organizational effort. The difficulty of implementing a new data strategy often goes underappreciated, particularly the multi-faceted nature of the challenges that need to be met. Deficiencies in organizational readiness and core competence represent clearly visible problems faced by data managers, but beyond that there are several cultural and structural barriers common to virtually all organizations that must be eliminated in order to facilitate effective management of data.
In this webinar, we will discuss these barriers—the titular “Seven Deadly Data Sins”, and in the process will also:
Elaborate upon the three critical factors that lead to strategy failure
Demonstrate a two-stage data strategy implementation process
Explore the sources and rationales behind the “Seven Deadly Data Sins”, and recommend solutions and alternative approaches
DataEd Slides: Exorcising the Seven Deadly Data Sins
The difficulty of implementing Data Strategy concepts often goes underappreciated, especially the multifaceted nature of the challenges that need to be met. Deficiencies in organizational readiness and core competence represent clearly visible problems faced by data managers, but beyond that there are several cultural and structural barriers common to virtually all organizations that must be eliminated in order to facilitate effective management of data.
In this webinar, we will discuss these barriers—the titular “Seven Deadly Data Sins”—and in the process will also:
- Elaborate on the three critical factors that lead to strategy failure
- Demonstrate a two-stage Data Strategy implementation process
- Explore the sources and rationales behind the “Seven Deadly Data Sins,” and recommend solutions and alternative approaches
RWDG Webinar: Mastering and Master Data Governance
Master Data and Data Governance are connected at the hip. Master Data implies that the data in the MDM resource is well defined, quality produced and effectively used. Data Governance for MDM is put in place to assure that these three things are handled properly. We can learn important lessons from Master Data Governance that will help us in Mastering Data Governance.
In this month’s RWDG webinar, Bob Seiner will focus on using the governance of Master Data initiatives to put effective Data Governance practices in place across the entire organization. Master Data requires all of the core components of a Data Governance program that can be leveraged in ways that will interest MDM and DG practitioners alike.
This webinar will cover:
• The connection between MDM and Data Governance
• Components of MDM that Require Data Governance
• Leveraging Master Data Governance for the Greater Good
• Mastering the Master Data Governance Roles
• The Role of MDM in Enterprise Data Governance
RWDG Slides: Build an Effective Data Governance Framework
Data Governance frameworks are used to structure the core components of a Data Governance program. Frameworks add significant value for those organizations getting started and improve or address missing components for programs already in place.
This month’s RWDG webinar with Bob Seiner will focus on dissecting a common Data Governance framework and customizing the framework to match the needs of your organization. Frameworks can be complex to describe but, in this case, the framework will become the self-describing face of your program.
In this webinar, Bob will share:
- A customizable Data Governance framework
- Five core components of a Data Governance framework
- Five perspectives for addressing each component
- Using a framework to select an approach to Data Governance
- Detailed descriptions of each component from each perspective
The future of bi isn't a bi tool
Business data has changed radically. Enterprises today use thousands of SaaS applications and business systems that create more data than ever imagined, resulting in a struggle for users to gain holistic and actionable insights. Organizations need a solution to simplify the end to end workflow-- from data prep and governance to visualization, delivery, and action. This webinar will reveal a proven solution with real world examples and how it creates future opportunities for your organization.
Real-World Data Governance Webinar: Big Data Governance - What Is It and Why ...
Big Data is all the rage. Everybody is asking about Big Data, researching Big Data, considering Big Data, some are even doing Big Data. Certainly many people are asking questions about Big Data Governance. We have some answers for them.
This Real-World Data Governance webinar with Bob Seiner will focus on the strength of Big Data Governance as a concept and a practice and will highlight how the concepts of each, Big Data and Data Governance, both benefit and hurt each other.
This session will include:
Defining Big Data Governance
Ways to Govern Big Data
Making the Connection for IT and Business People
Determining the Vitality of Big Data Governance
Considerations for Big Data Governance
Data Insights and Analytics Webinar: CDO vs. CAO - What’s the Difference?
At one time, there were well-stated distinctions between the Chief Data Officer and Chief Analytics Officer roles. But not today. In some organizations, this role confusion actually causes serious concerns.
John and Kelle will revisit the definitions, suggest where lack of clarity first began, and discuss how best to manage the role distinctions going forward.
This webinar will address:
Differences in the CAO and CDO roles
CDOs who aren’t responsible for all organizational data
Why role clarity matters
Organizational success without one or both roles
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Working together, these roles can accelerate faster access to approved, relevant and higher quality data – and that means more successful use cases, faster speed to insights, and better business outcomes. However, both new information and tools are required to make the shift from defense to offense, reducing data drama while increasing its value.
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You’ll be educated, entertained and inspired by this panel and their expertise in using the data trifecta to innovate more often, operate more efficiently, and differentiate more strategically.
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With technological innovation and change occurring at an ever-increasing rate, it’s hard to keep track of what’s hype and what can provide practical value for your organization. Join this webinar to see the results of a recent DATAVERSITY survey on emerging trends in Data Architecture, along with practical commentary and advice from industry expert Donna Burbank.
Data Governance Trends - A Look Backwards and Forwards
As DATAVERSITY’s RWDG series hurdles into our 12th year, this webinar takes a quick look behind us, evaluates the present, and predicts the future of Data Governance. Based on webinar numbers, hot Data Governance topics have evolved over the years from policies and best practices, roles and tools, data catalogs and frameworks, to supporting data mesh and fabric, artificial intelligence, virtualization, literacy, and metadata governance.
Join Bob Seiner as he reflects on the past and what has and has not worked, while sharing examples of enterprise successes and struggles. In this webinar, Bob will challenge the audience to stay a step ahead by learning from the past and blazing a new trail into the future of Data Governance.
In this webinar, Bob will focus on:
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- How trials and tribulations evolve to success
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- The great Data Governance tool explosion
- The future of Data Governance
Data Governance Trends and Best Practices To Implement Today
1) The document discusses best practices for data protection on Google Cloud, including setting data policies, governing access, classifying sensitive data, controlling access, encryption, secure collaboration, and incident response.
2) It provides examples of how to limit access to data and sensitive information, gain visibility into where sensitive data resides, encrypt data with customer-controlled keys, harden workloads, run workloads confidentially, collaborate securely with untrusted parties, and address cloud security incidents.
3) The key recommendations are to protect data at rest and in use through classification, access controls, encryption, confidential computing; securely share data through techniques like secure multi-party computation; and have an incident response plan to quickly address threats.
2023 Trends in Enterprise Analytics
It is a fascinating, explosive time for enterprise analytics.
It is from the position of analytics leadership that the enterprise mission will be executed and company leadership will emerge. The data professional is absolutely sitting on the performance of the company in this information economy and has an obligation to demonstrate the possibilities and originate the architecture, data, and projects that will deliver analytics. After all, no matter what business you’re in, you’re in the business of analytics.
The coming years will be full of big changes in enterprise analytics and data architecture. William will kick off the fifth year of the Advanced Analytics series with a discussion of the trends winning organizations should build into their plans, expectations, vision, and awareness now.
Data Strategy Best Practices
Too often I hear the question “Can you help me with our data strategy?” Unfortunately, for most, this is the wrong request because it focuses on the least valuable component: the data strategy itself. A more useful request is: “Can you help me apply data strategically?” Yes, at early maturity phases the process of developing strategic thinking about data is more important than the actual product! Trying to write a good (must less perfect) data strategy on the first attempt is generally not productive –particularly given the widespread acceptance of Mike Tyson’s truism: “Everybody has a plan until they get punched in the face.” This program refocuses efforts on learning how to iteratively improve the way data is strategically applied. This will permit data-based strategy components to keep up with agile, evolving organizational strategies. It also contributes to three primary organizational data goals. Learn how to improve the following:
- Your organization’s data
- The way your people use data
- The way your people use data to achieve your organizational strategy
This will help in ways never imagined. Data are your sole non-depletable, non-degradable, durable strategic assets, and they are pervasively shared across every organizational area. Addressing existing challenges programmatically includes overcoming necessary but insufficient prerequisites and developing a disciplined, repeatable means of improving business objectives. This process (based on the theory of constraints) is where the strategic data work really occurs as organizations identify prioritized areas where better assets, literacy, and support (data strategy components) can help an organization better achieve specific strategic objectives. Then the process becomes lather, rinse, and repeat. Several complementary concepts are also covered, including:
- A cohesive argument for why data strategy is necessary for effective data governance
- An overview of prerequisites for effective strategic use of data strategy, as well as common pitfalls
- A repeatable process for identifying and removing data constraints
- The importance of balancing business operation and innovation
Who Should Own Data Governance – IT or Business?
The question is asked all the time: “What part of the organization should own your Data Governance program?” The typical answers are “the business” and “IT (information technology).” Another answer to that question is “Yes.” The program must be owned and reside somewhere in the organization. You may ask yourself if there is a correct answer to the question.
Join this new RWDG webinar with Bob Seiner where Bob will answer the question that is the title of this webinar. Determining ownership of Data Governance is a vital first step. Figuring out the appropriate part of the organization to manage the program is an important second step. This webinar will help you address these questions and more.
In this session Bob will share:
- What is meant by “the business” when it comes to owning Data Governance
- Why some people say that Data Governance in IT is destined to fail
- Examples of IT positioned Data Governance success
- Considerations for answering the question in your organization
- The final answer to the question of who should own Data Governance
Data Management Best Practices
This document summarizes a research study that assessed the data management practices of 175 organizations between 2000-2006. The study had both descriptive and self-improvement goals, such as understanding the range of practices and determining areas for improvement. Researchers used a structured interview process to evaluate organizations across six data management processes based on a 5-level maturity model. The results provided insights into an organization's practices and a roadmap for enhancing data management.
MLOps – Applying DevOps to Competitive Advantage
MLOps is a practice for collaboration between Data Science and operations to manage the production machine learning (ML) lifecycles. As an amalgamation of “machine learning” and “operations,” MLOps applies DevOps principles to ML delivery, enabling the delivery of ML-based innovation at scale to result in:
Faster time to market of ML-based solutions
More rapid rate of experimentation, driving innovation
Assurance of quality, trustworthiness, and ethical AI
MLOps is essential for scaling ML. Without it, enterprises risk struggling with costly overhead and stalled progress. Several vendors have emerged with offerings to support MLOps: the major offerings are Microsoft Azure ML and Google Vertex AI. We looked at these offerings from the perspective of enterprise features and time-to-value.
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Creating an EDGE - Enterprise Data Governance Experience
- 1. Creating an EDGE: An Enterprise Data Governance Experience
- 2. Today’s Speakers © 2017 erwin. All rights reserved. 2 Mariann McDonagh CMO, erwin Inc. Jamie Knowles Product Director, erwin Inc. https://www.linkedin.com/in/mariannmcdonagh/ https://www.linkedin.com/in/jamieknowlesltd/@mcdonaghmariann
- 3. The Data Wave Is HERE In 2015 and 2016, more data was created than the previous 5,000 years of humanity. In 2017, we will create even more data in one year alone. BY 2020 37 billion new things will be connected 1.5 GB of traffic per day per internet user 4 TB of data per day for autonomous vehicles 1 PB of data per day to run a smart factory 5 TB of data per flight for airplanes © 2017 erwin. All rights reserved. 3
- 4. The Value Of Data Is Proliferating Exponentially © 2017 erwin. All rights reserved. 4 Retailers that leverage the full power of big data could increase their operating margins by as much as 60%. Estimates suggest that by better integrating big data, healthcare could save as much as $300 billion a year. For a typical Fortune 1000 company, a 10% increase in data accessibility will result in more than $65 million in additional net income. But less than 0.5% of all data is ever analyzed and used.
- 5. FOR COMPANIES THAT HOLD PERSONAL DATA AND DO NOT HAVE A GRASP ON INFORMATION PRIVACY & SECURITY SO IS THE POTENTIAL RISK GDPR is here with Potential Penalties of up to 4% of ANNUAL TURNOVER © 2017 erwin. All rights reserved. 5
- 6. Companies Must Manage Data In The Context Of Their Strategic Goals © 2017 erwin. All rights reserved. 6 Improved Decision Making Increased Customer satisfaction Compliance, Privacy & security Operational Efficiency Revenue growth DATA GOVERNANCE IS THE KEY VISIBIL ITY AN D C O N TR O L U N L O C KS BU SIN ESS VAL U E O F D ATA
- 7. What Is Data Governance? © 2017 erwin. All rights reserved. 7 Data in Context What do we have? What does it mean? Where did it come from? Is it secure? What rules or restrictions apply? How accurate is it? Where is it? Who is accountable? Who is using it? How is it used? How can I access it? HOW CAN ORGANIZATIONS BENEFIT? Reduce Data-Related Risks Optimize Business Operations Increase Use of Trusted Data
- 8. What Are Some Of The Challenges To Holistic Data Governance © 2017 erwin. All rights reserved. 8 Assessing the current state Planning the way forward Balancing control & agility Enabling accountability Overcoming silos Proving value Iterating success
- 9. What Are The Critical Facets Of An Enterprise DG Experience? © 2017 erwin. All rights reserved. 9 REGULATORY PEACE OF MIND VISIBILITY ACROSS DOMAINS AN INTEGRATED ECOSYSTEM ANY DATA ANYWHERE STAKEHOLDER EMPOWERMENT
- 10. What Are The Key Bodies Of Knowledge Required For Successful DG? © 2017 erwin. All rights reserved. 10 DG Hub Business Glossary Data Dictionary Data Usage Meaning of data Business Term Code Set Business Use Measures and Mechanisms Workflow Issue Audit KPI Detailed descriptions of data assetsFile Database Document BI Report Atomic dataData Element Rules and policies that govern data Policy Rule Ownership High level designs Data Flow Lineage Impact Catalogs of data driven assets Role System Location Data Store Process Business IT
- 11. Who Are The Key Stakeholders And How Can DG Help Them? © 2017 erwin. All rights reserved. 11 DATA OWNERS STEWARDS CUSTODIANS (IT) CONSUMERS
- 12. How Does Data Governance Relate To Other Disciplines? © 2017 erwin. All rights reserved. 12 Enterprise architecture Business process modeling Data modeling Enterprise security …
- 13. What Should Organizations Look For In DG Technology? © 2017 erwin. All rights reserved. 13 Understand Data Dictionary Data Quality Data Usage Discover Reference Data Business Glossary Socialize Data Sets Data Issues Impact & Lineage Govern Policies and Rules DGOM Collaboration Workflow Collaboration Shared Services Integration
- 14. In Closing … DG 1.0 has left the market wanting more Successful DG requires a different approach that empowers the enterprise Readiness is key to success DG should be measured and measurable in the context of the business © 2017 erwin. All rights reserved. 14
- 15. Questions?
- 16. Take the Next Step: Visit erwin.com © 2017 erwin. All rights reserved. 16 Download our ebook