Enterprise Architecture and Target Operating Models

How often is an established Enterprise Architecture approach used to create a Target Operating Model? If the answer is not often, then why not? If the answer is yes all the time, then how should we go about creating one ? Are traditional consultancy approaches to target operating models good enough? What is an Operating […]

Dealing with Technical Debt Like We Mean it

What’s the biggest problem with technical debt? In my opinion, the biggest problem is that it works. Just like the electrical outlet pictured above, systems with technical debt get the job done, even when there’s a hidden surprise or two waiting to make life interesting for us at some later date. If it flat-out failed, […]

The Hidden Cost of Cheap – UX and Internal Applications

Why would anyone worry about user experience for anything that’s not customer-facing? This question was the premise of Maurice Roach’s post in the Zühlke blog, “Empathise with your users or you won’t solve their problems”: Bring up the subject of user empathy with some engineers or product owners and you’ll probably hear comments that fall […]

Solving the Polyglot Persistence Puzzle – Defining the Information Value Lifecycle

I believe an Information Architect’s primary purpose isto increase the value of the information assets belonging to anorganization. Securing and makinginformation available is no longer sufficient to grow the competitivecapabilities of an organization. Information architects must get:

  • the right information
  • to the right person
  • at the right time
  • in the right format
  • so the best decisions can be made at all levels of theorganization.

To assist Information Architects in understanding anddefining a process to increase the value of information assets, I have createdan Information Value Lifecycle map. Thisis the first step in understanding the characteristics of information on theway to building Polyglot Persistent Architectures.

Building an Information Value Lifecycle map is done in 7steps.

Step 1 – Build the Information Value Lifecycle maplayout.

Each organization has multiple levels of decisionmaking. For each level of decisionmaking, there are Information Usage patterns and the Information Structuresneeded to support the usages. Theexample below starts with the Transaction Owners, the staff that create,maintain and own the transactions required to run the business. At the highest level are the CEO and Board ofDirectors (BoD). Maps will differ toreflect each organization’s hierarchical process of decision making.

Step 2 – Define the Information Usage patterns and theInformation Structures needed to support the Information Usage pattern.

Typically different levels of decision making requiredifferent levels of aggregation and summarization of information – from simpletransaction reporting to cross line of business and industry aggregations, analytics and predictive analysis. Information architectures over the years haveevolved well know sets of information structures (most commonly 3rdNormal Form, Star, Snowflake and Cube schemas) needed to support these UsagePatterns.

Step 3 – Define the processes needed to transform andaggregate information from transactions to the highest level of the decisionmaking process.

Extract, transform and load (ETL) processes moveinformation from one level of decision making to the next based on theinformation usage patterns. Mappingthese ETL process at a high level ensures data linage is understood andinformation accuracy is guaranteed. Someapplications provide capabilities that ‘jump’ the information past some levels tothe highest levels of the decision making process. Oracle Hyperion is an example.

Step 4 – Record Master Data Management usage patterns

Understanding Master Data usage patterns gives insightsinto which types of information are most important to an organization. They also indicate the level of informationmanagement maturity – more usage of master data reflects an understanding ofthe value of master data and a willingness to invest to realize that value.

Step 5 – Identify Big Data usage patterns

Most organizations have begun the process of deployingand realizing the value of Big Data. RecordingBig Data usage patterns shows the maturity of an organization in relationshipto their ability to adopt and deploy new technologies.

Step 6 – Identify the ‘Gold Nuggets’ in Big Data

Identify where Big Data data mining and analytics hasincreased the quality and/or quantity of information inputted into the InformationValue Lifecycle. These processes arecommonly referred to as finding the ‘Gold Nuggets’ of information that were previouslynot known. It’s important to understandthe value of the ‘Gold Nuggets’ in the decision making process of anorganization to justify the level of effort and expense of deploying Big Dataarchitectures.

Step 7 – Identify new Big Data information valueopportunities

The low cost of some Big Data architectures has allowedorganization to capture new sources of data that have lead to new ways of doingbusiness. Many of these use casesinclude social media as a way of judging the success of marketing campaigns andnew product lunches. Capturing these BigData opportunities shows the agility and innovativeness of an organization.

In the next blog I will introduce the 16 Information Characteristics that make up the heart of the Information Characteristics Architecture Method.

Solving the Polyglot Persistence Puzzle – Defining the Information Value Lifecycle

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I believe an Information Architect’s primary purpose is
to increase the value of the information assets belonging to an
organization. Securing and making
information available is no longer sufficient to grow the competitive
capabilities of an organization. Information architects must get:

  • the right information
  • to the right person

  • at the right time
  • in the right format
  • so the best decisions can be made at all levels of the
    organization.

To assist Information Architects in understanding and
defining a process to increase the value of information assets, I have created
an Information Value Lifecycle map. This
is the first step in understanding the characteristics of information on the
way to building Polyglot Persistent Architectures.

Building an Information Value Lifecycle map is done in 7
steps.

Step 1 – Build the Information Value Lifecycle map
layout.Each organization has multiple levels of decision
making. For each level of decision
making, there are Information Usage patterns and the Information Structures
needed to support the usages. The
example below starts with the Transaction Owners, the staff that create,
maintain and own the transactions required to run the business. At the highest level are the CEO and Board of
Directors (BoD). Maps will differ to
reflect each organization’s hierarchical process of decision making.

Step 2 – Define the Information Usage patterns and the
Information Structures needed to support the Information Usage pattern.

Typically different levels of decision making require
different levels of aggregation and summarization of information – from simple
transaction reporting to cross line of business and industry aggregations, analytics and predictive analysis. Information architectures over the years have
evolved well know sets of information structures (most commonly 3rd
Normal Form, Star, Snowflake and Cube schemas) needed to support these Usage
Patterns.

Step 3 – Define the processes needed to transform and
aggregate information from transactions to the highest level of the decision
making process.

Extract, transform and load (ETL) processes move
information from one level of decision making to the next based on the
information usage patterns. Mapping
these ETL process at a high level ensures data linage is understood and
information accuracy is guaranteed. Some
applications provide capabilities ‘jump’ the information past some levels to
the highest levels of the decision making process. Oracle Hyperion is an example.

Step 4 – Record Master Data Management usage patterns

Understanding Master Data usage patterns gives insights
into which types of information are most important to an organization. They also indicate the level of information
management maturity – more usage of master data reflects an understanding of
the value of master data and a willingness to invest to realize that value.

Step 5 – Identify Big Data usage patterns

Most organizations have begun the process of deploying
and realizing the value of Big Data. Recording
Big Data usage patterns shows the maturity of an organization in relationship
to their ability to adopt and deploy new technologies.

Step 6 – Identify the ‘Gold Nuggets’ in Big Data

Identify where Big Data data mining and analytics has
increased the quality and/or quantity of information inputted into the Information
Value Lifecycle. These processes are
commonly referred to as finding the ‘Gold Nuggets’ of information that were previously
not known. It’s important to understand
the value of the ‘Gold Nuggets’ in the decision making process of an
organization to justify the level of effort and expense of deploying Big Data
architectures.

Step 7 – Identify new Big Data information value
opportunities

The low cost of some Big Data architectures has allowed
organization to capture new sources of data that have lead to new ways of doing
business. Many of these use cases
include social media as a way of judging the success of marketing campaigns and
new product lunches. Capturing these Big
Data opportunities shows the agility and innovativeness of an organization.

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The Seductive Myth of Greenfield Development

Greger Wikstrand‘s tweet from earlier this week packed a wealth of inspiration into one image: The second statement particularly resonated with me: “The present is built on the past.” How often do we, or those around us, long for a chance to do things “from scratch”. The idea being, without the constraints of “legacy” code, […]

Can you afford microservices?

Much has been written about the potential benefits of designing applications using microservices. A fair amount has also been written about the potential pitfalls. On this blog, there’s been a combination of both. As I noted in “Are Microservices the Next Big Thing?”: It’s not the technique itself that makes or breaks a design, it’s […]

On business capabilities, functions and application features

Working with architecture as a way of designing and cataloging the relationships between business and IT has always been a challenge. I recently attended an IASA meeting where we discussed the challenges of designing and maintaining a business architecture. At the meeting I talked about capabilities, what I think they are and how to actually go […]

Rational Rationalization – Part the First

With the upheaval of the economic downturn came a spate of mergers, acquisitions, divestitures, splits and buy-outs. The ensuing chaos of the resulting technology portfolios cannot really be overstated. Many surviving companies are just a mess. In norm…