Noreen Kendle, Principal Consulting Analyst
Noreen Kendle is a Principal Consulting Analyst with TechVision Research. She is a recognized leader in the field of Information-Data Strategies, which includes Information Asset Management, Data Governance/Information Ownership, Information Policies & Standards, Business Data Architecture, Meta-Information, Enterprise Data Design, Information Quality, Data Valuation, Enterprise Foundational Data, Data Globalization, and Business Intelligence Strategies.
She has held enterprise information leadership and practitioner positions within large global organizations for over 30 years including Delta Air Lines, AT&T, Masco, Travelport, and The Home Depot, as well as data industry consultant/advisor for Gartner and Burton Group.
Noreen has been instrumental in the development of Enterprise Information and Business Data Architecture Frameworks, as well as their implementation in support of the management of information-data as a corporate asset. As an innovative thought leader of Enterprise Information-Data Strategies she holds a patent and is a respected speaker/author.
She also provides acclaimed workshops on all aspects of information architecture and data strategies including planning, roadmaps and governance.
- Data governance and architectures
- Enterprise Architecture (EA)
- Business Data Architecture (BDA)
Recently Published Research
Fixing the Fundamentals - The Business Blueprint
Data - The Fundamentals are Broken
In this report we have identified the broken fundamentals of data and five basic steps organizations can take to address these broken fundamentals. These include: establishing the business to data connection; using a business blueprint; creating a data oversight framework; establishing an enterprise data construction practice; building the data asset management infrastructure; and, standing-up a data asset management practice focused on enterprise foundational data. In the end, if organizations do not fix the fundamentals, they will never be able to effectively clean, identify, integrate, manage, and utilize their data assets for even basic operations, let alone take advantage of the full power of those assets for true business intelligence, risk avoidance, predictive analytics, artificial intelligence, and data monetization. Information is truly powerful, but only if the data is right.
TechVision CrossTalk Report: Identity and Data Governance
What are the connections between identity and data in the enterprise? When one protects identity, they are really protecting data: data that is a representation of the identity. Unfortunately, as discussed in this new CrossTalk report by TechVision Research most organizations don’t have data management and even when they do have data management, the identity data is usually left out of the discussion. At TechVision Research we continually see data mismanagement undermining all aspects of the business function. As Noreen Kendle has experienced “data mess-up is equal opportunity across all types of data, including identity data.” Noreen goes on to say “I’ve seen companies overwrite big text fields with identity-related information primarily because they don’t want to stop and enhance the database schema and structures: this includes credit card numbers, social security numbers, etc.” Obviously, this is a huge privacy issue because the fields are not identified as identity fields and the IT staff is oblivious to the situation. Bill Bonney speaks from experience building an IdM practice as he “agrees that overloading is an issue.” But, as Bill likes to point out, “It’s not just overloading, it’s making assumptions about what is in a field and assumptions about how the field is evaluated and before you know it you have sub-processes built up around a falsely validated field.” This establishes a false foundation that eventually causes the entire trust chain to break. As Bill states, “inevitably, someone will use the data based on how it was first created (the field label of record).” This is a symptom of a far greater problem. There is a huge assumption made by IT staff and the identity management tools they use that the data fields are accurately representing the data stored in the field. This just isn’t so! Given this reality of identity and data mismanagement in the enterprise, this report focuses on the following key concerns:
- The evolution of identity data as its own domain
- The impact of silos on identity data management
- The potential of virtual directories as an identity data management approach
- The impact of data reuse on identity and the resulting authenticity decay
- Identity data governance: is built on a foundation of quicksand
There are things organizations can be doing today to address these concerns. Specifically, this report discusses a five-step program for identity data governance based upon the team’s experience working with data and identity in F1000 enterprise.
Fixing the Fundamentals –Data Strategy
To get anywhere one has to know where they are going. Similarly, a data strategy defines the desired state for an organization’s data assets – the organization’s data vision. Yet, even with a formal data strategy in hand, many organizations make little progress achieving this vision. Most data strategies lack a method to achieve the data vision. This leads to a continuous cycle of data chaos. A realistic data strategy begins with a Data Oversight Framework defining the path, the plan and the data infrastructure necessary to actually achieve the data strategy. This report outlines the process necessary to achieve a realistic (real world) data strategy, starting with a Data Oversight Framework . This report covers:
- How to define an enterprise data vision and know what one looks like
- How to develop a Data Oversight Framework and the infrastructure to support it
- How to combine the Data Oversight Framework and data vision to establish a successful, sustainable and defensible data strategy
- Experience defining and implementing data strategies at Fortune 500 companies
Fixing the Fundamentals - Data Asset Management
- Establishing the difference between getting the data right and keeping it right
- The steps to creating a Data Asset Management Framework including the tools required to manage data as a strategic business asset
- Examples of successful Data Asset Management Frameworks
- Lessons-learned and best practices establishing Data Asset Management Frameworks at Fortune 500 companies
Fixing the Fundamentals –Data Design Practice
Enterprises face a terrible data design situation: their current data systems are in a state that is often too difficult and too expensive to correct or in many cases that is impossible to change. At TechVision Research our experience shows that rather than continually chasing the data challenges of existing systems it’s often better for the enterprise to proactively focus on the architecture and design of future data systems with the goal of getting the data right in the first place. This approach requires a change in typical data architecture and design approaches used today. When it comes to data design, unless we change how we are doing things, we will continue to get the same results. The report defines and discusses a proactive data design practice that covers the identification, architecture, design, and deployment of data structures/systems throughout the organization including the organization’s meta-information. This proven practice uses the Business Blueprint as the foundation for all of the organization’s data and data structures to form a holistic data infrastructure tying all of the organizations data systems together. As discussed in this report, using the Business Blueprint as the foundation and applying the data design practice throughout the enterprise establishes an appropriate data infrastructure to assure data consistency going forward. This data infrastructure may be utilized by Data Integration, Data Asset Management, Information Security, and Business Intelligence functions within the organization. Developing this data infrastructure is critical for integrating, managing, securing and gaining intelligence from the organization’s data assets. Without the proper data infrastructure, doing this is difficult at best and more likely it’s impossible. This report covers:
- How to make the decision when to continue to invest in legacy data architecture and design and when to shift the focus to future data systems
- How to change data design practices that are entrenched in the organizational zeitgeist and retool to get the data right
- How to develop a proactive data design practice covering the identification, architecture, design and deployment of data structures/systems
- How to use the Business Blueprint as the foundation to achieving enterprise-wide data consistency
- Using the data infrastructure as a vehicle to integrate, manage, secure and leverage the organization’s data assets