Over the past four issues of this newsletter, we have discussed the role and requirements of information workers, and examined how collaborative business intelligence (BI) can help extend the reach of business intelligence to a wider user audience. There are, however, other ways of extending business intelligence to leverage the investment organizations have made in their BI decision-making environments. This article provides an introduction to new and evolving technologies that enable companies to extend the scope as well as the reach of their BI environments. In subsequent articles, we will look at several of these technologies in more detail.

The Approaches

Figure 1 outlines the four main ways of extending business intelligence in organizations.

 

• Discover and Access Data – finding out and accessing data that is available for decision making and analytics. By improving our discovery and accessing of data, we reach a wider set of data sources.
  
  
• Integrate and Manage Information – consolidating the data into an appropriate data store (e.g., data warehouse, data mart, ODS), putting it into a business context, and converting data into information. Due to increasing sources and volumes of data, we must broaden the scope of deployment options by implementing lower cost and better price performance data management capabilities.
  
  

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• Analyze Information – creating analytics to help understand the business performance of the organization. We must broaden the scope of analytics beyond the traditional uses today and apply it to more business problems and requirements.
  
  
• Collaborate and Make Decisions – making the analytic results available to others and acting on the business insights. The goal is to use collaboration technologies to bring business intelligence to a wider and potentially less experienced audience.
  

New and evolving technologies that enable these four approaches can be grouped into the categories shown in Figure 2.

Information Technologies

Extending business intelligence to address a wider user audience involves making the information more consumable and also the technology more usable. Our recent series of newsletter articles on information workers focused on making information more consumable. These articles discussed the need to extend existing BI solutions with a business information glossary and lineage tracking, and emphasized the importance of creating actionable (rather than static) analytics using features such as performance management, alerts, and decision analysis workflows. They discussed the industry direction toward the use of collaboration and social computing in a BI environment.

Underlying technologies that enhance the usability of BI solutions include improved information visualization techniques and the move toward self-service BI applications. The use of rich web interfaces and reusable widgets, and the ability for business users to assemble (mash together) and personalize their own BI applications are important factors in improving both visualization and self-service.

For less experienced business users, the direction of BI tools toward supporting familiar workgroup interfaces and applications such as Microsoft Office are an important step forward in terms of usability. Support for mobile computing is also an important usability feature for many of these users.

Most of the features that address information and technology reach are focused on how information is consumed and used. However, the depth and range of information available to business users is also important. Given the number of data sources in an organization and the volume of data involved, it is becoming impractical, and in some cases unnecessary, to capture and consolidate all of this data into a data warehouse. Instead, the data has to be accessed in place where it resides. This can be done using data federation (also called data virtualization) techniques. The challenge is to determine when data federation should or can be used in place of data consolidation. We will look at this topic in more detail in a subsequent article.

Application Technologies

To date, most BI applications have provided data analytics for tactical and strategic decision making by executives, senior managers and business analysts. Most of these applications are reactive in nature as they provide information about business events that have occurred in the past. Predictive analytics and data/text mining, however, are now becoming more mainstream, and this trend enables organizations to move from a reactive to a more predictive approach to business decision making.

Other technologies that extend the application scope of business intelligence include operational BI solutions and analytics built using event, web and unstructured data. These technologies enable organizations to address a wider range of business needs and problems. This not only improves business decision making for existing users, but also extends BI usage to those users who have not previously been exposed to its benefits.

Deployment Technologies

As BI applications evolve toward supporting an increasing number of business users and provide access to a wider range of data sources and larger volumes of data, organizations will need lower-cost development and deployment approaches that work in concert with the existing BI environment. A range of different platforms can be used here including analytical DBMSs, appliances, open source and cloud computing. The challenge will be to determine which option to use when. A subsequent article in this series will present deployment patterns that will help in this decision-making process.

Where Next?

You can see from this discussion that there are a wide range of alternatives for extending the use of business intelligence. Many of these have been discussed in prior articles, but the area we want to focus on in this upcoming set of articles is technologies that reach out to a wider set of data sources using data federation and technologies that offer alternative approaches to managing data (analytical database systems and cloud computing). Look for these articles in the coming months.

Recent articles by Claudia Imhoff, Colin White

• Advanced Analytics and Business Intelligence: Term Abuse?
• Business Intelligence Really Can Be Fast and Effective
• Extending the Scope and Reach of Business Intelligence, Part 3
• Extending the Scope and Reach of Business Intelligence, Part 2