By using website you agree to our use of cookies as described in our cookie policy. Learn More


Introduction to Self-Service Business Intelligence

By Claudia Imhoff and Colin White

Definition of Self-Service BI

The facilities within the BI environment that enable BI users to become more self-reliant and less dependent on the IT organization. These facilities focus on four main objectives: easier access to source data for reporting and analysis, easier and improved support for data analysis features, faster deployment options such as appliances and cloud computing, and simpler, customizable, and collaborative end-user interfaces.

In today’s economic environment, organizations must use business intelligence (BI) to make smarter, faster decisions. Business users must have better access to critical information at the right time and in the right format for comprehension. The business case for BI is well established; it gives companies their competitive edge and allows them to discover new business opportunities. Corporations and their employees need to be innovative and creative if they are to compete effectively. “Those with the imagination … to invent smarter ways to do old jobs, energy-saving ways to provide new services, new ways to attract old customers, or new ways to combine existing technologies will thrive.”1 But in many organizations, countless decisions are still not based on business intelligence and analytics. Why? Certainly not from a lack of demand. Because of the changes in our economies, IT departments have been stripped down to the barest numbers, even as business users are demanding more control and faster access to BI and business data. From our survey of 587 technical and business professionals, we found that an overwhelming 78% of respondents stated that they needed a faster time to value from BI solutions.

To satisfy this demand and improve time to value, companies are looking for alternative approaches to BI. One approach is to set up an environment in which the information workers can create and access specific sets of BI reports, queries, and analytics themselves—without IT intervention. The purpose of this environment is to extend the reach and scope of BI applications to address a wider range of business needs and problems. At the same time, this extension must support the information workers’ need for a personalized and collaborative decisionmaking environment. Information workers must become more self-sufficient by having a BI environment that is more usable and more consumable. It is these two themes—usability and consumability—that play crucial roles in a fully functioning selfservice business intelligence (SS BI) environment.

Self-Service Business Intelligence and Its Objectives

This section provides a brief overview and description of four key objectives of self-service BI (see Figure 1). The technologies supporting them will be covered in detail later.

Make BI Results Easy to Consume and Enhance

This objective is probably the most important from the business community’s perspective. Users must be able to grasp what the information presented to them means. A fire hose of information makes it difficult to determine where things are going off-kilter, where exceptions occur, or even get a handle on critical situations. SS BI must be an environment in which it is easy to discover, access, and share information, reports, and analytics. Information workers want to be able to personalize their dashboards or have automated BI capabilities so that the information becomes actionable for their particular situations. It must also be in an easy-to-use format and delivered to a device and user interface of their choosing.

From a technical perspective, BI that is easy to consume and enhance requires clear business definitions that are easily accessible as well as data lineage that is tracked and documented. The organization improves its decision making by tracking interactions and decisions to discover, capture, and disseminate best practices. In addition, the information must be presented in a way that is easy for users to understand: data visualization and presentation are paramount for comprehension.

Finally, information workers increase knowledge content through interactions such as entering feedback on analytic results, models, and other BI results; adding business context on situations; and identifying related information such as external links, meteorological data, and other data that affects business activities. This allows the information workers to improve an organization’s body of knowledge content. It also enables them to be more self-sufficient and make faster decisions. This feature helps BI implementers create environments that are appealing to business users and promotes the adoption of self-service.

Make BI Tools Easy to Use

Not only do BI results need to be easy to consume and enhance, but the tools generating the results must also be easy to use. BI solution providers have focused on making these technologies easy to use for years and, for the most part, vendors have succeeded in making them straightforward and simple. This is a significant factor in the success of any SS BI environment. It may help even novice information workers select their own reports and create simple analyses. It will certainly allow technologically savvy users to get what they need when they need it.

Although reporting and simple analytics interfaces have achieved a high level of ease of use, we still need to make the more complicated analytics easy to use, create, and publish. Sophisticated analytics are often too intricate, complex, or difficult to construct for many information workers. Support for such sophisticated analyses, as well as making results easy to publish in the required format, greatly improves the productivity of a company’s information workers.

Make Data Warehouse Solutions Fast to Deploy and Easy to Manage

Self-service business intelligence may mean looking at alternative deployment mechanisms to reduce costs, improve time to value, and support increasingly extreme data processing. Agile methodology, software-as-a-service (SaaS), and cloud offerings, as well as analytic DBMSs, all contribute to these goals. Key components of this objective include ensuring that the SS BI environment provides good performance and scalability for simple to complex analytical workloads and high data volumes. In addition, SS BI must support easy administration and enhancement of the environment in a timely manner.

Opening BI to access by the business community also enables applications to be built that may not have been possible with earlier architectures and technologies. Business units can deploy their own applications, tailored to their specific requirements, and on their own timetable. User satisfaction increases dramatically when this level of creation and management of reports and analytics is available to the business community.

Make Data Sources Easy to Access

In our interviews, we heard a number of times that if you couldn’t access the data, then nothing else mattered—whether it was traditional, IT-created BI components or SS BI. However, there is one significant difference with SS BI—not all the data accessed needs to be stored in a data warehouse. Data external to the data warehouse such as operational and external but relevant data (e.g., weather information, geographic, demographic, or psychographic data) may need to be made available for access by the business community without IT assistance.

Self-service business intelligence may also require that all types of data be made accessible by the BI implementation team— not just traditional, structured data. This includes unstructured data such as comments or e-mails and even social media sources. The ability of the information workers to understand the full picture (which includes the context in addition to the content) is becoming mandatory. It may not be possible or even necessary to bring this contextual data into the data warehouse before it can be utilized by SS BI. If some of this data resides outside the warehouse, it means the BI environment must have some means or mechanism to federate data—bringing it together virtually from different sources for analysis and access.

The BI implementation team’s job is to create the infrastructure that permits the free flow of data from all these sources. They can then monitor access and utilization of the data, ensure the environment’s optimal performance, implement appropriate security and privacy procedures, and provide support to the business community where needed in the construction or publication of BI reports, analytics, and so on.

1 Tom Friedman, New York Times, October 2009.

Claudia Imhoff, Ph.D., is a popular analyst and dynamic speaker on business intelligence. She is the president of Intelligent Solutions, Inc., a data warehousing and BI consultancy. She has co-authored five books on these topics and writes articles and research papers for technical and business magazines. She is a TDWI Fellow and founded the Boulder BI Brain Trust. You can reach her at [email protected].

Colin White is the founder of BI Research. As an analyst and educator, he is well known for his in-depth knowledge of data management, information integration, and BI technologies and how they can be used for building the smart and agile business. With many years of IT experience, he has consulted for dozens of companies throughout the world and is a frequent speaker at leading IT events. You can reach him at [email protected].

This article was excerpted from the full, 36-page report, Self-Service Business Intelligence: Empowering Users to Generate Insights. You can download this and other TDWI Research free at

The report was sponsored by Birst, IBM, Infobright, Neutrino Concepts, PivotLink, Quest Software, SAP, SAS, and Tableau Software.

This article originally appeared in the issue of .

TDWI Membership

Get immediate access to training discounts, video library, research, and more.

Find the right level of Membership for you.