The Future of Information Architecture
Making your organization smarter will help build competitive advantage. However, it takes more than just the latest and greatest tools to do that. Building an organization is much like building a house: a solid foundation has to support the processes, workflows and tools that enable you to succeed. The decisions that yield competitive insights are driven by data retrieval and analysis. When seeking to maximize insight productivity, your IT infrastructure is this foundation.
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Over the course of the past several years, one can observe two key trends in information architecture:
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1. Unstructured content is gaining structure. While the traditional method of controlling uncontrolled content is not economically viable, recent years have seen significant investment in automating or semi-automating the process through the use of taxonomy management systems, tagging, wikis and metadata management.
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2. Structured content is becoming uncontrollable. Building, maintaining and managing relevant distribution pathways for one relational database is a (relatively) simple task. But today's enterprises utilize hundreds (if not thousands) of different databases. Their ensuing volume and complexity put inherent limitations on how organizations can scale the scope and depth of their distribution pathways.
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Challenges in Information Architecture
As unstructured content gains structure, organizations' demand pathways are increasingly beginning to resemble distribution pathways. Faceted search, contextualized search and federated search are all examples of how information architects are increasingly "hard-wiring" information distribution mechanisms into their demand pathways. Many enterprise search vendors are investing significant resources and developing interesting solutions for responding to this trend.
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However, as structured data becomes uncontrollable, information architects' recourses have traditionally been limited. In today's budget and time-sensitive world, engaging swarms of expensive consultants or hiring armies of systems architects and analysts is often not a viable proposition. This fact often places the greatest burden on the analytical components of available distribution pathways:
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Due to the number and diversity of structured data systems, the creation of business intelligence (BI) dashboards or reports that integrate/federate data is not scalable.
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Forced to choose between integrating business process functionality or preparing integrated analytics, most information architects will choose the former: after all, it has a greater immediate impact on revenue and profits.
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As a consequence, the analytical distribution pathways for structured data are often re-scheduled or delayed by the necessity to douse metaphorical fires elsewhere within the organization's IT infrastructure.
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Responding to the Challenges in Information Architecture
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As information architects increasingly wrestle with the challenge of building/maintaining distribution pathways for structured data in today's complex data environment, forward-thinking architects recognize the parallels to unstructured content. In order to make uncontrollable unstructured content available to information users, architects had to establish demand pathways through the use of enterprise search. As structured data becomes increasingly uncontrollable, organizations will have to build demand pathways for structured data.
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While traditional enterprise search systems can provide a viable demand pathway for uncontrollable descriptive structured data, they are unable to provide a demand pathway for uncontrollable analytical data. At best, they can provide a demand pathway for your organization's pre-existing distribution pathways. This fails to address the underlying problem discussed above: if an integrated/federated BI report has not been authored, then a user will be unable to answer their questions efficiently. However, architects seeking to make necessary analytical data available can utilize a new set of tools to accomplish this goal: numerical data search engines.
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Numerical data search technology integrates the ease-of-use of enterprise search with the data-manipulation capabilities of business intelligence platforms. The result is a search engine that can automatically access any data within your organization, find on-demand information relevant to any user within your organization, and return that data to the user in an accessible and easy-to-use format.
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By implementing this type of technology, information architects are able to:
Satisfy executive demands for insight productivity while still,
Focusing their human resources on the highest-value initiatives, and;
Encompassing the complex and varied data their organization must deal with.
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Through a judicious combination of distribution pathways and demand pathways, information architects are able to build an IT foundation capable of supporting their organization's transformation into an innovative, insight-driven competitive powerhouse.
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About ChartSearch
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This article was provided by ChartSearch Inc. ChartSearch is a newly launched enterprise technology company which helps businesses maximize insight productivity through the use of a first-of-its-kind numerical data search engine and real-time business intelligence platform. With ChartSearch, businesses can find and extract statistical research data on-demand, then automatically visualize it in a readily accessible form. For more information, please visit www.chartsearch.net.
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Related Tags: data retrieval and analysis, data search engine
R.L. Fielding is a freelance writer who has written on a wide variety of topics, with special expertise in the education, pharmaceutical and healthcare, financial service and manufacturing industries.
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