2. IASA is
a non-profit professional association
run by architects
for all IT architects
centrally governed and locally run
technology and vendor agnostic
3. Information Architecture
Module 0: Course Intro, Architecture Module 3: Data Integration
Fundamentals Introduction: Data, Lesson 1: Integrating at the Company Level
Information and Knowledge Lesson 2: Data Characteristics
Lesson 3: Data Integration at the System level
Module 1: Information for Business
Lesson 1 – Information as Strategy Module 4: Data Quality and Governance
Lesson 1 – Data and Information Quality
Lesson 2 – Relating Information to Value
Lesson 2: Data Compliance
Lesson 3 – Information Scope and Lesson 3 – Data and Information Governance
Module 5: Advanced Information Management
Module 2: Information Usage Lesson 1: Data Warehousing
Lesson 1 – Who Uses Your Information Lesson 2: Business Intelligence
Lesson 2 – How, When, Where and Why Lesson 3: Data Security and Privacy
is Information Used Lesson 4: Metadata and Taxonomy Management
Lesson 3 – Form Factors Lesson 5: Knowledge Management
Lesson 4 – Usage Design 1
Module 6: Architecture throughout the Lifecycle
Lesson 5 – Quality Attributes for
Lesson 6 – Data Tools and Frameworks
18. Iasa Architect Services
Adopt Iasa Standards – Skills taxonomy, role descriptions,
Set your goals for value
Assess your current team – gap analysis
Develop and educate people
Certify employees and vendors
19. •December 6th – 7th, 2012 // Austin, TX
•Training: Dec. 3rd – 5th, 2012
•Certification: Dec. 7th – 9th, 2012
•Leading Innovation in Architecture. Stay ahead of the technology curve and
shape the future of architecture in your organization.
•Connect and share insights with the largest global network of
technology and enterprise architect practitioners.
•Attend sessions on the most current breakthroughs, case studies and
key topics in architecture - presented by a mix of practicing architects
from top performing businesses and organizations.
•Participate in pre-conference workshops and training. Maximize your time
at the summit by taking part in one of six intensive training courses designed
to provide immediate solutions to benefit your everyday practice.
•Featuring Industry Leading Keynote Speakers:
•Sheila Jeffrey •David Del Giudice •Paul Preiss
Senior Information Architect Principal Architect President, Founder
Bank of America AstraZeneca Iasa Global
•David Manning •Scott Whitmire •Cat Susch
IT Enterprise Architect Enterprise Architect Enterprise Architect
Idaho Power Company Nordstrom Microsoft
The typical state of affairs you will find in most organizations is as follows: We know we have data Some of the lineage is tracked – but probably out of date There is not a lot of clarity on ownership While the goal may be to have single sources of data – over time ad hoc data services and processes pop up Data quality is unclear or assumed but not guaranteed
The problem is that data is not static. While you may take a snapshot at any point in time it is the truth for that moment in time. Even if you have processes in place to manage the addition of data, change management of master and meta data and a set of guidelines – you can still end up with out of control data systems The root cause of this is the lack of governance, you don’t currently have governance……. See why this is tough problem to solve? The solution prevents the problem but most organizations have no clue where to start or if they do start they may either fail or complete the effort but not have a transition plan to maintain governance once it is established and over time the organization finds itself back in the same or a similar state.
There are a number of things that a Data Governance can do. It all depends on risk, priorities etc. As part of the lineage exercise and purely by formation and communication of the council’s existence – it is possible to start with a backlog of items to be addressed at the first meeting. So first and foremost – define how intake will work, how decisions will be made and how issues will be managed – the basics. Get the structure in place. Then make sure that you not only have a plan for today but that it is a flexible enough plan to be sustained over time. Because just as change is inevitable in data, the need for governance will not go away. Data governance councils will identify goals and priorities for achieving a level of proficiency across the organization which encompasses everything from policies and processes to monitoring and communications. Individuals outside of the governance council may approach the group with problems and findings which lead to investigations, studies and eventually standards for the management and handling of data. These standards will cover anything from data retention periods to best practices. The overall goal of the council is to ensure consistency in the collection, storage and delivery of data to support the business with cost effectiveness as a balancing factor.
If you walk into a room and mention governance, you can easily see that there are not a lot of people that will stick around for the conversation. Unless they have had the epiphany of how governance actually enables business and is not about locking things down and people out. There are concepts which have bad reputations – such as process and governance. These reputations are formed by bad implementations, overly zealous implementations or an inability to sustain the change over time. Worse yet, there are a lot of misconceptions about what governance actually is.
In most cases – governance has been overcomplicated. It is easier to talk about what governance isn’t vs. what governance is ‘ to govern’ is at the root – which translates to: have political authority: to be responsible officially for directing the affairs, policies, and economy of a state, country, or organization control something: to control, regulate, or direct something have influence over something: to have or exercise an influence over something This drives a lot of the perceptions people have about governance. Instead let’s think of governance as having goals such as: defining expectations, granting power, and verifying performance
The first step in the governance lifecycle is to form a team. This team may not end up being the final governing body or governance board. But as you develop the concept of governance you will want to ensure that you have equal representation of all data producing, storing and consuming groups – in other words almost every team of the organization will have representation at the table. As mentioned, this is not necessarily the final governance team. What is important at the formative stage is that you form a team of individuals with working knowledge of the data.
The first action is to catalog the data of the organization. The size of the data does not fall in line with the size of the company. In other words there can be very small companies with only a few employees which process and store petabytes of data a day. So don’t be fooled by looking at the size of the organization into thinking the data will align to that size. Data lineage is an iterative process. The size of the enterprise will determine how deep you go into the processes. Instructor: Flip to next slide to review BPMN process level definitions then return to this slide Choose a level that can be achieved in a short period of time. The goal would be to hit level 3 or 4. But in a larger enterprise you may only be able to hit level 1 or 2. If all you can accomplish in 2-3 weeks is a list of all data repositories with owners, purpose and some basic information about data sources etc. then you have enough to get started. The goal behind capturing lineage is to tie data to a purpose, typically a KPI (Key Performance Indicator). If you gather the KPIs for the company by department and then travel backwards from the end metric the goal is to find all processes and sources which lead to that data. No matter what, the lineage effort should catalogue systems and data. Instructor: Skip ahead past the next slide to the following slide
While the initial team is compiling the data lineage they should also be assessing maturity. Maturity should not be assumed to be consistent across the enterprise nor should you consider that maturity would be consistent across any one lineage for a metric.
By now it is time to form the Governance Body – you can form this body at any point in the process, but for the most part, until there is an overview of the data environment and state of maturity, the Governance Body will mostly sit back and support the discovery process. Let’s call this the Data Governance Council. The Council will be made up of representatives of each functional area of the organization. It is possible that there will be members that were part of the original working team that reside on the Council, or it could be there management.
Instructor: Ask – How do you define governance? Use this as an example of how individuals that make up the council will have their own definition of governance. As you can see – each one of you has different definitions of governance. This will also be true of the members of the council. Instructor: Ask – Why do you have the council define governance? Answers resemble the following: (you are looking for 2 major inputs) Establish a common definition Get all council members aligned to the definition As you can see, whenever you bring a group of people together of varying roles and backgrounds there is a likelihood that their definition of governance will vary. With that being said, it is important to have the council define governance to ensure that everyone has the same expectations. A shared definition of governance will only apply to this council for this organization at this time. Over time the definition may change and should be revisited each year.
The best way to revisit the definition to ensure it is still effective and applicable is to create a charter which includes the definition of governance.
Instructor: Ask – What do you think the scope of a data governance council should be? Answer: this will vary – you are looking for answers which are about the creation of rules or standards but not actually doing or building – typically. Note: If there are a lot of comments about building systems etc. (Ask – is there a risk of conflict of interest if the governance council develops systems vs. governing data?) Scope = focus. You can’t tackle everything – this is actually one of the reasons that governance councils fail – they have unreasonable goals. Each year the council should have a set of goals that are reasonable and can be achieved, followed by stretch goals. It is important to remember that everyone has a ‘day’ job and that the governance council typically gets about 10% of their attention. Image: street_sign_post_questions_400_clr presentermedia.com
Define a set of goals and expectations typically these align to the terms of the council. A reasonable set of commitments for the first year of a council would be to: Establish lineage Establish current level of maturity Identify optimal level of maturity to reach Define roadmap Execute 1 st year actions, etc. The important thing is to review progress regularly and identify when things get off track. Adjust the plan if it takes longer to achieve completion or if the outcome does not meet the expectations of the council. Don’t wait until the end and let things slowly fall apart. The failure of a governance council often comes when success is assumed and not monitored. When defining the roadmap, it is important to think of the goals as being multi-generational. Additionally you will have to break down these goals into actions, accountabilities, responsibilities, constraints and dependencies.