Knowledge Integrity: Master Data Standards and Data Exchange
This topic surfaces frequently, and it relates to the use of agreed-to data set formats for data interchange whose use somehow diverges from their original intent. The changes occur subtly over time, and in potentially multiple places; therefore, until an analyst actually sits down to review the different uses, the variants would not even be noticed.
Knowledge Integrity: New Names, Old Tricks? CDI, MDM, EII
I have been seeing three business terms popping up with greater frequency recently, and it is interesting to explore these ideas within a combined context. Those terms are: customer data integration (CDI), master data management (MDM) and enterprise information integration (EII).
Data Integration Advisor: ODS Redux, Part 2
Conventional wisdom doesn’t always age like a fine wine. When it starts smelling like dirty socks, it’s time to challenge it. Sometimes the conventional wisdom published in books, written in articles and presented in seminars is accepted as gospel, even when it starts to develop a distinctive odor. Examine conventional wisdom periodically to determine if it is current and relevant. This is particularly true when it comes to an ODS. The purposes and methods used for building the ODS may have changed dramatically over the years.
This article is meant to expound upon the area of integration relating to the government sector. Listed below are brief summaries of key integration technologies.
Good summaries.
Data Integration Strategy – EAI or ETL
This million-dollar question for IT people is: which tool or technology is the right choice for their data integration needs. Two choices are enterprise application integration (EAI) or extract, transform and load (ETL). This article throws some light on these two approaches and helps decision-makers to decide on the right tool or technology.
Meta Data Management in the Enterprise
At a very high level, meta data can be classified into two categories. Shared meta data Unique meta data
Shared meta data elements need to have consistent definition and semantics across the enterprise.� For example definition of a Customer entity should be homogenous throughout the enterprise.
BI Briefs: Business Intelligence Goes Back to the Future, Part 1
Data integration is a case in point. It’s easy to convince yourself that the reason why data integration is so complicated is because people have never really understood it or had the right tools and techniques. It seems that every four years someone introduces a “new approach” to data integration. But the approaches aren’t new.
Knowledge: The Essence of Meta Data: The Meta Data Support Model, Part 2
The customer doesn’t want to feel alone and without support. Many times consultants and IT projects come into the environment and leave without a trace of letting the customer know how they can get further help. The customer support model provides three specific areas where the support team can provide help and assurance. The areas include an online environment, subject matter expert (SME) network and external resources.
Data Integration Advisor: ODS Redux, Part 1
In fact, building an ODS is like the lawless Wild West of data management because there is no standard architecture and design.
Enterprise Information Integration: A Pragmatic Approach
Unfortunately, many of the systems we’re relying on today, to provide us critical business information, were not designed with this task in mind. Many of these systems were designed for the sole purpose of increasing productivity. Thus, only the data necessary to produce the intended increase was incorporated into the system. Fortunately, the need for greater and greater productivity has forced us to change systems or build new ones to meet the demand. This process has resulted in data accumulating in rough layers that have been loosely knitted together, to provide us with many of the answers we need today to remain competitive. However, these layers have become so fragmented and isolated, that it requires Herculean efforts to make sense of it.
To drive this point home even further, the CEO of a major logistics and transportation company called his efforts to obtain a consolidated view of all business done with a particular trucking company across all business units, a “Chinese fire drill.” This quote indicates that his information systems do not support his needs, and instead, require the chaotic process of humans manually pulling data and consolidating it, in order to obtain the values this CEO needs.
Sounds like most of the organizations that I work with. Mr. Morgenthal’s book may be useful in the re-education process.