Future Trends in BI and the Integration to Support It

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Recently, the TDWI published a report on emerging technologies and trends in business intelligence and analytics. David Stodder, director of TDWI research for business intelligence, highlighted what he sees as the five most important trends in a recent article, available for free reading on the organization's site.

 

Integration is a major issue for only one of the five trends Stodder picked. Still, any IT department can tell you BI doesn't just happen, no matter how clever the technology becomes. Behind-the-scenes integration and data management are key components to any successful BI effort.

 

With that in mind, here's a look at the integration angle on each of Stodder's five emerging BI trends.

 


Trend 1: "Data discovery accelerates self-service BI and analytics."

 

What it is: Data discovery tools rely on memory to access data, which means end users can "test predictive models and perform iterative analysis without incurring the performance issues of accessing data on disk."

 

The integration angle: When end users can create their own reports on the fly, it means IT has less project work that requires specially coding a database query or ETL job. While capabilities vary by solution, some data discovery tools offer:

 

  • Search capabilities
  • Extended or hybrid SQL for different types of data, including semi-structured data
  • Masked or encapsulated ETL, metadata and other information management, so end users don't have to deal with these data complexities


Trend 2: "Unified access and analysis of types of information improves user productivity."

 

What it is: The ability to add unstructured information found in email, text documents and Web pages to BI tools for analysis.

 

The integration angle: Stodder's specifically talking about Unified Information Access (UIA) tools. These solutions bring together two capabilities in one package:

 

  1. Better search options that extend beyond most BI tools
  2. SQL-based access and analysis


Thus, users can access and explore information that's outside the parameters of the BI solution's metadata.

 

Trend 3: "Big Data Generated by Social Media Drives Innovation in Customer Analytics."

 

What it is: You know about the large amounts of data produced by social networking and social media. The idea is to do more than just track what's said on a social networking site. Companies want to use this data for customer analytics such as product development, customer service, marketing strategies and so on.

 

The integration angle: We're already seeing the beginnings of this trend, as traditional players in BI, data warehousing and analytics focus on integrating and connecting with Hadoop. " the emerging trend may be as much the integration of exotic data analysis technologies and frameworks into traditional systems as it is the growth in their implementation," writes Stodder. "How these technology trends and practices play out will have a big data' impact on customer analytics."

 

Trend 4: "Text Analytics Enables Organizations to Interpret Social Media Sentiment Trends and Commentary."

 

What it is: The ability to make sense of what's being said in unstructured data. An example: Text analytics tools will look for linguistic patterns that will show whether a comment is positive and flag.

 

The integration angle: Text analytics will help add depth to other tools. Stodder uses the example of coupling text analytics tools with "voice of the customer" tools so you can determine from a customer's tone and words how angry the customer may be. It could also be used to monitor social networks for information about drug side effects.

 

Trend 5: "Decision Management Enables Organizations to be Predictive and Proactive in Real Time."

 

What it is: Decision management will require several technologies, Stodder writes. It'll require business rules and business process management, plus complex event processing. The goal is to give organizations information to move from a reactive position to a predictive position by picking up "meaningful events."

 

The integration angle: Decision management is all about integration. Specifically, it's about bringing together analytics and data visualization tools with business rules/process management systems and event processing systems, such as RFID tags or manufacturing systems.



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