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.
http://www.nytimes.com/2009/10/21/opinion/21friedman.html?ref=thomaslfriedman
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 tdwi.org/bpreports.
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 .