Joy Ruff - All About Data Architecture

Product Marketing Manager for ER/Studio

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Integrating Data from Multiple Sources: Inferring Source Metadata - by David Loshin, Knowledge Integrity This is the second post in this series. Read the previous post and the next post. In my last post, we began to review the data element conformance challenges associated with integrating data from a variety of original sources. The biggest issues have to do with the ability to conform data sets, or determine whether they can be blended together in a cohesive and semantically consistent way. The challenge is that in some, if not many, of the cases, there is little or no metadata, leaving you...
Integrating Data from Multiple Sources: The Challenge of Data Element Conformance - by David Loshin This is the first post in this series. Read the next post. The continued fascination with expanding an organization’s analytics capabilities often centers on the desire to identify interesting and new data sources originating outside the enterprise that can be integrated into a big data analytics application. The presumed wealth of information hidden within third-party or otherwise externally-sourced data sets has inspired many aspiring data scientists to rapidly create processes for accessing ...
Tags: data metadata
The #1 Data Modeling Issue – Being ‘Dead’ Right - By Len Silverston, Universal Data Models, LLC While many data modelers are very open minded and not righteous at all in their attitudes, over the years, I have heard the following statements (paraphrased) from data modelers numerous times: ‘There is one and only one best way to model a data modeling requirement.’ ‘My data model design is the right way to go. Those other data model constructs and solutions are just not right.’ ‘Your application project needs to implement our enterprise-wide standardized model exactly how we modeled it, wi...
Using Collaboration for Spreading Enterprise Knowledge - by David Loshin, Knowledge Integrity, Inc. This is the last in a series of six posts on metadata collaboration from David Loshin. Read the previous post in the series. In my earlier blog entries, we have looked at the need for common semantics for enterprise information concepts and the need to engage the business users as part of a larger community to steward the standardization of meta-concepts. Having a process for engagement is the first step, but without providing a means and a platform for continuous interaction and comm...
Big Data = Bigger Need for Data Models - by Rob Loranger Big Data has had a great impact on science, healthcare, government and many other industries. For instance, it is now possible for scientists to map and analyze the human genome, for healthcare organizations to provide continuous monitoring of patient health, and for financial institutions to greatly improve their ability to detect fraud. In addition, as of 2012, Big Data has been used to help win presidential elections. As described in the article Barack Obama’s Big Data won the US election, P...
Engaging the Business Users in Enterprise Semantics - by David Loshin, Knowledge Integrity, Inc. This is the fifth in a series of six posts on metadata collaboration from David Loshin. Read the previous post and the next post in the series. In my previous post, we discussed the need to review business glossary terms and data elements and their corresponding definitions to determine where there is sufficient similarity among metadata concepts to harmonize their definitions or if their definitions are distinct to take the steps to ensure their differentiation. However, from a pract...
Collaboration Principles and Universal Data Models - By Len Silverston, Universal Data Models, LLC Once upon a time, there were four expert data modelers engaged on an enterprise data modeling effort. There was also an additional expert data modeler facilitator to foster collaboration among the modelers. The modelers each had different opinions regarding how to model certain constructs, for example, how to model roles, statuses, categories, hierarchies, and so on. The facilitator looked at their suggestions and saw the merit in each of their designs and then, after numerous discussions and de...
The 3Vs may require NoSQL, but data modeling is still required - by Rob Loranger We live in an exciting time where technology is entering our lives in areas that many of us never expected. For example, at home, once unintelligent devices such as thermostats, light bulbs, and entertainment consoles are now capable of detecting when a person is within close proximity and can adjust to his or her preferences. Within the workplace, computers, peripheral systems, and machinery are constantly communicating with one another to create organizational efficiencies. And the all-pervasi...
Harmonize or Differentiate? - by David Loshin, Knowledge Integrity, Inc. This is the fourth in a series of six posts on metadata collaboration from David Loshin. Read the previous post and the next post in the series.
Data Quality and the Upsides of Data Governance Listen to Ron Huizenga of Embarcadero, David Loshin of Knowledge Integrity, Inc., and other panelists in this lively replay of Information Management’s DM Radio segment entitled “Data Quality and the Upsides of Data Governance”, moderated by The Bloor Group.

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