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SmartData Collective > Business Intelligence > BI and unstructured data continued…
Business Intelligence

BI and unstructured data continued…

LyndsayWise
LyndsayWise
5 Min Read
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Last week I wrote a piece for Dashboard Insight about the convergence of BI and unstructured data.  Over the years the topic of unstructured data keeps poking its head into the realm of business intelligence, but has yet to be seen on a large scale.  Some interesting vendors that I wrote about (please see below: “Enter the role of BI and unstructured data”) show that both can be used to develop a broader BI platform.  Whether or not this begins to happen on a larger scale remains to be seen.  What is interesting, however, is the way organizations are starting to use multiple types of technologies and to look at information – both the types of data available and the way in which it can be transformed into valuable information – to transition from traditional BI uses to more dynamic applications. Operational BI and the integration of external data are providing organizations with more insights into their business challenges and giving them the means to stay competitive within an unstable economy.  Hopefully, BI players will learn from their data integration counterparts…

Last week I wrote a piece for Dashboard Insight about the convergence of BI and unstructured data.  Over the years the topic of unstructured data keeps poking its head into the realm of business intelligence, but has yet to be seen on a large scale.  Some interesting vendors that I wrote about (please see below: “Enter the role of BI and unstructured data”) show that both can be used to develop a broader BI platform.  Whether or not this begins to happen on a larger scale remains to be seen.  What is interesting, however, is the way organizations are starting to use multiple types of technologies and to look at information – both the types of data available and the way in which it can be transformed into valuable information – to transition from traditional BI uses to more dynamic applications. Operational BI and the integration of external data are providing organizations with more insights into their business challenges and giving them the means to stay competitive within an unstable economy.  Hopefully, BI players will learn from their data integration counterparts that are building platforms for all of an organization’s data management needs and start to develop comprehensive suites for companies that want to look at a full BI solution that does the same.

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Enter the role of BI and unstructured data

In two recent analyst briefings, I had the opportunity to get updated on the initiative of both Bi3 Solutions and Datawatch.  Both solution providers approach the business problem of how to tackle unstructured data analysis because of the fact that much of the valuable information that businesses require to make informed decisions reside within unstructured content – whether ready-made reports, documents, contracts, emails, etc. Many organizations struggle with how to access this information, organize it, and gain insights.  Within a traditional BI model, the ability to adequately handle unstructured data and integrate it into an analytic framework is near impossible.  So how do these solution providers do it?

Bi3 Solutions uses a cloud-based infrastructure within a Software as a Service framework.  Their solution extracts relevant information from within content; thereby identifying the structured aspects organizations are looking for within their unstructured content.  For instance, pertinent contract information can be extracted and transformed into structured data to alleviate the burden of having people go through hundreds or thousands of documents, saving time and money in the process.  Afterwards, regular data analysis can occur to identify trends and the like.

With Datawatch and their Monarch BI Enterprise Server, currently created reports and other content are leveraged and transformed into relevant BI content.  Information is pulled directly from the content residing within the organization within heavy data integration requirements.  Organizations can then combine various data elements to gain valuable insights into what already exists within their business.


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