A free guide to Business Intelligence software by Think Businessy that summarizes everything you need to know and were afraid to ask about what business intelligence software is, why it's useful and what capabilities it can offer your business. There are many makes and types of business intelligence software product available to buyers these days. Which type of product is right for your business? In this guide I provide a perspective on the capabilities you might be unknowingly looking for – just to make sure everything is ‘in the box’. Topics covered include: • What is Business Intelligence? • The Players • Capabilities • Constructs • Technology Disciplines • Future Trends • Check-list • Final Thoughts Within this guide I haven’t spent too much time profiling each of the products as this isn’t particularly helpful given that specifications and features change all of the time so it is always a good idea to conduct your own web research. I do however provide a summary of the more popular products at the end of the article.

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The Business Intelligence
Software Guide 2013
ThinkBusinessy
8th August 2013
Ian Tomlin

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Introduction
There are many makes and types of business intelligence software product
available to buyers these days. Which type of product is right for your business?
In this guide I provide a perspective on the capabilities you might be unknowingly
looking for – just to make sure everything is ‘in the box’.
Topics I cover include:
 What is Business Intelligence?
 The Players
 Capabilities
 Constructs
 Technology Disciplines
 Future Trends
 Check-list
 Final Thoughts
Within this guide I haven’t spent too much time profiling each of the products as
this isn’t particularly helpful given that specifications and features change all of
the time so it is always a good idea to conduct your own web research. I do
however provide a summary of the more popular products at the end of the
article.

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What is Business Intelligence?
While there are many definitions the role of business intelligence software is to
source insights from data. There are two main forms of data:
 Structured data – The sort of stuff you see in a database or a CSV (Comma
Separated Value) file that you’d expect to open in a desktop spreadsheet
application. These days we also have formats like XML that are essentially
structured composite files that carry data and a description of the data (so
the data file might say, “I’m an invoice” and “This first column is the Invoice
Number” which helps with data transfer between computer applications).
 Unstructured data – Data that’s held in documents and other formats that
hasn’t already been placed into nicely labelled boxes but we still might
want to mine it.
The technology tooling required to surface useful data, organize it and present it
is complex and embraces a variety of capabilities, constructs and technology
disciplines. Few Business Intelligence tools cover all of the areas - but that’s okay
because you don’t always need every attribute.
The Players
With so many vendors in the business intelligence market it would be a pretty
meaningless and unfruitful exercise as the boundaries of capabilities for each
vendor are constantly in a state of flux. Even segmenting business intelligence
tools into ‘pre-cloud’ or ‘Made of the cloud’ does not provide great signage to
buyers given that many of the old school vendors have acquired or developed
in-memory and web 2.0 self service style capabilities.
Some of the more notable names in BI with exceptional technology or big brands
include SAS, IBM, MicroStrategy, SAP BusinessObjects, Oracle Hyperion,
Informationbuilders, Microsoft, Tibco, Qliktech, Tableau, Actuate, Encanvas,
Targit, Pentaho, Yellowfin, Birst, iDashboards, Jedox, Borad International and
Jaspersoft.
In addition to these software providers there are literally hundreds if not thousands
of business intelligence consulting and IT services companies around the world
that offer expert skills in selection, deployment and outsourcing of BI services
where a ‘blended’ strategy is adopted. The best advice therefore is to define the
requirements before attempting to select the tool-ware and service provisioning.

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Capabilities
Capabilities are big categories of ‘things’ that business intelligence DOES – not be
confused by HOW it gets done. Business Intelligence has four main areas:
Enterprise Performance Management
A business intelligence platform for managing organizational performance
including governance of progress towards strategic objectives as defined in a
scorecard and the monitoring of daily activities that result in budgets and
forecasts being achieved. Business Intelligence software used for this purpose will
often adopt the very popular Balanced Scorecard model to frame and articulate
strategy as exampled in the Strategy Map illustration above.
Daily Operating Controls and Operational Reporting
Applications used to disseminate reports that show progress towards budget and
forecast targets so that managers can react to sub-optimal performance and
before it’s too late to do anything about it.

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Operational Analytics
Applications used to source actionable insights that cause managers to review
their processes and decisions in search of improvements.
Community/Social Business Intelligence
Applications used to source insights within a community to aid community
learning and cooperation; often resulting in the creation of new or enhanced
applications and processes adopted by the community.

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Constructs
I use the term construct to describe core characteristics of HOW business
intelligence software does what it does. These are:
1. Capture – In many analytical applications there is more data to be added.
Tools to author forms are important to enable keyboard data entry from PC, tablet
and mobile phone devices.
2. Discover and harvest – The ability to harvest data from multiple sources is
essential for most data analysis applications. Advanced platforms provide
opportunities for discovery of new insights held within data. For example, natural
language search tools can present data on companies that are similar to those
in the enquiry to suggest content that may be interesting to the enquirer.
3. Assimilate – Assimilation is an essential yet least understood aspect of business
intelligence and operational analytics software. Assimilation is about get data
brought into a useful form for analysis. The extent to which assimilation is required
will depend on where the data is held, what form it is in, and how it needs to be
used. This stage might include tools that normalize data, sort it, cleanse it and
mash-it into a form that’s useful.
4. Analyze and interpret – Making sense of data has always been a feature of
business intelligence tools since the humble spreadsheet came of age. Analytics
is a challenging aspect for vendors because users have such varied requirements
and expectations. Interpretation is ‘in the eye of the beholder’ which is why self-
service tools have become such a competitive battleground.
5. Present– The presentation of data could be anything from a simple table to
sophisticated charts, maps and data visualizations. Data becomes generally
more interesting when people can look at two, three or four characteristics of the
subject on the same page (examining customer data that includes spending
habits, social networking behavior, location and affluence can expose new
understanding of customer personas that would be difficult to find if each
attribute were explored separately). Presentation needs to cater for analysis of
single or multiple attributes of one entity, or single or multiple attributes of multiple
entities and should include:
 Tables with the ability to sort, group, order and compare
 Simple (easily absorbed) entity analysis views like gauges, traffic lights, slider
scales and ‘direction of trend’ arrows that bring at-a-glance understanding
 Enlightening charting and graphing tools including bar charts, pie charts,
line graphs, geo-spatial maps, spatial graphs, spider diagrams etc.

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 Scorecards – that enable formation and comparison of key performance
indicators in a dashboard to accommodate for period by period analysis,
mixed compositions of KPIs including run-rate, first-past-the-post etc.
These days it’s hard to imagine any of the above presentation modes without the
ability to drill-down into source data and download data for further analysis. Drill-
down features are so important to aid comprehension and to enable the enquirer
to gain a deep understanding of ‘the data behind charts and graphs’, and how
summary values have been aggregated.
6. Manage enquiries and socialize – It can become time consuming for users to
keep re-building the reports and report-views of data that are most useful. Expect
BI platforms to therefore provide the means for users to personalize their own suite
of queries. Establishing profile-based customized report selections means that
users don’t have to keep re-creating the same enquiries time and again. In the
noughties, users expect to be able to socialize their reports and charts; normally
by publishing them to a dedicated webpage so they can share the precise report
view they’re looking at with colleagues.
7. Predict – Business Intelligence software becomes REALLY INTERESTING to buyers
when it can not only expose insights but predict consequences on growth
opportunities, resources, operating constraints and exposure to risk or
unbudgeted costs. It takes a heady mix of clever software AND a deep
appreciation of how processes work to create the magic formula needed to
source predictive analytics.
8. Install new or adapted processes – There’s little point learning if you can’t do
anything about it. Increasingly, Business Intelligence platforms are providing the
tooling to enable business analysts to apply learning lessons. Modern BI platforms
install changes to operating processes by providing the methods and tools to
design and deploy new applications or adapting existing ones. Tools like
Encanvas and Interneer enable cross-platform, cross-discipline workflows to be
installed that run across existing administrative systems and silos of data.

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Technology Disciplines
I use the term ‘technology discipline’ to describe the big chunks of technology
found in Business Intelligence applications. The market for tools is so diverse these
days that it’s difficult for buyers to compare like-for-like capabilities. Many vendors
have particular strengths, or specialize in a specific discipline which means
creating a solution can be a choice between:
 Purchasing a ‘total platform solution’ from a software vendor where
everything is expected to be sourced by one vendor including the expertise
to deliver outcomes.
 Purchasing a ‘pick and mix’ of best of breed software vendor tools and
building your own solution.
 Inviting a third party IT Services company to take on the project overhead
of managing business intelligence sourcing across your enterprise based on
an agreed set of outcomes.
Here I describe the most prevalent technology disciplines under the headings of
the constructs I’ve outlined in the previous section. Note that I’ve not produced
a fully comprehensive list as it might stretch into pages! Neither have I
documented ‘IT hygiene’ factors such as User permissions management, security,
scaling, portal deployment, cross-browser compatibility and mobile integration
(etc.) that are ‘must-have’ business computing requirements.
(Capture)
 Key-fill forms applications - To enable keyboard-fill data entry of data that
adds-to existing business insights applications. Applications normally need
to support one-to-many and many-to-many data relationships and support
cross-browser deployment to PC, tablet and mobile devices.
(Discover and harvest)
 Natural language search engines – To spider the Internet and recover
content held in unstructured content (documents and websites articles)
based on natural language terms.
 Recommendation engines – To source recommendations of contextualized
insights (view services like Factiva and you will see that search enquiries on
a topic such as the name of a company will result in other similar companies
being ‘recommended’ to the enquirer. You will also see similar side-bar
discoverable insights from searches on popular mapping tools like
Googlemaps).
 Data source connectors – To connect to data sources and file formats.
These generally take the form of a wizard that makes it easy to connect to
a data source and configure an extraction of data or two-way dynamic

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integration. Vendors like Microsoft, Tibco, Encanvas, Xchanging, Pentaho,
and Mulesoft all offer suites of data connectors and integration tools so you
can source virtually any data from any source.
(Assimilate)
 Information upload and flow management tools – To automate triggering
and extract workflows for the purposes of loading data from its various
sources into the business intelligence environment (see products like
Information Flow Designer from Encanvas).
 Extract, Transform and Load tools – To source data and make it usable in
business intelligence applications; normally by executing transforms.
 Data mashup tools- To bring data together in news ways by picking ‘bits’ of
data from different places and creating new data structures with it (for
example, taking data from a spreadsheet and combining it with data from
Oracle and SAP in the same table-view).
(Analyze and interpret)
 Tables with Sorting, Ordering, Filtering and Grouping – To offer users the
ability to interrogate data using interactive table views.
 Comparison Views – To offer users the ability to compare entities side-by-
side in table views.
 Metering and Charting with Drill-down – To offer users the ability to view
data in the form of meters and charts used to report on aggregated data
views with the ability to drill-down to the original data; probably in an
interactive tabular view.
(Present/Self-service tooling)
 KPI Scorecarding – To enable users to create scorecards by specifying a
series of key performance indicators each with its own formative logic –
such as first-past-the-post, run-rate, period comparison etc.
 Graphing and Charting – To enable users to create charts and graphs from
the assimilated data without complexity or programming.
 Mapping and Visualizing – To enable users to geo-map or visualize data
using spatial graphing tools.
(Manage enquiries and socialize)
 Web page/dedicated-URL sharing – To enable users to share their insights
by using dedicated-URLs that can be pasted into messages etc.
 Interactive slider and choice controls – To enable users to interact with data
in real-time to understand likely impacts of decisions.
 Voting and crowdsourcing – To enable communities to contribute opinions
on the analytics being shared.

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(Predict)
 Prediction engines - To predict pinch-points in areas of resourcing capacity,
process loadings, consequences of decisions etc.
(Install new or adapted processes)
 Applications design tools – To create applications that facilitate the
iteration of business processes that are demanded when users seek to
apply the learning lessons surfaced by actionable insights.
 Business Process Management (BPM) workflow automation – To install cross-
cutting workflows that run across silos of business operation in support of the
change agenda demanded when users seek to apply the learning lessons
surfaced by actionable insights.

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Future Trends
The future trends emerging in Business Intelligence include:
1. More ‘born of the cloud’ BI products
It would be hard to imagine a business intelligence vendor surviving if they
aren’t able to provide a cloud delivered service. Companies like Encanvas
and Tableau have mature and sophisticated cloud offerings that make it
painless to configure a private-cloud environment within which company data
can be assimilated without risk of security breaches. In the architectural purity
debate, platforms that are able to deliver their insights through a browser
agnostic front-end will inevitably be favored against those that require plug-
ins or downloads. It still amazes me how incredibly poor companies like IBM
and Microsoft are at supporting the diverse range of browsers out there. It
seems these bigger players are confident enough in their brand positions to
say to customers ‘You can have IE and Safari if you’re lucky’ which a decade
ago was possibly good enough. If it was then, it isn’t anymore.
The products that will eventually grow to become the leaders in this industry
will have been ‘born’ in the cloud and of cloud technologies. Many of the
current products are built on code authored in the 1990’s and that’s a big
problem. Technologies like in-memory processing and use of AJAX tools CAN
be bolted on to legacy platforms but eventually the complexity and cost of
supporting aging technology platforms becomes a competitive Achilles’ heel.
2. Greater focus on sourcing of actionable insights than technology tools
Whilst dashboards and charts are the ‘bread and butter’ of business
intelligence solutions, what business people expect now are ACTIONABLE
insights that cause them to take action. The company that is leading the
charge to prove how effective and influential operational analytics can be to
bolster business success isn’t actually a business intelligence company at all.
It’s Google. Take a look at Google Analytics and you see a demonstration of
the art of operational analytics done well. Now imagine having Google
Analytics across every aspect of your business landscape. Wow.
Buyers are worried far less about tools than they ever used to be. They are far
more interested in outcomes. It’s the actionable insights, not the operational
analytical tools that deliver them, that’s taking center stage.
3. Increased embedding of BI tooling into business apps
Google Analytics also demonstrates the power of incorporating business
intelligence technologies into the operational platforms that business people
use. No longer is business intelligence software something separate, it is

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embedded into the applications people produce. In this sense the clever tools
of business intelligence software becomes smaller parts of a bigger system.
One could argue that platforms like IBM WebSphere and Microsoft SharePoint
have been doing this for some time. Take a look at Oracle’s fusion apps and
you will see the very best of operational analytics technology ‘ready-for-use’
and built within the core applications companies can now purchase on a
cloud. Business intelligence offerings like Tibco Spotfire and Encanvas
BusinessIntel take on the shape of applications design tool-kits that bolt into
existing applications and become as one with them. Meanwhile database
platforms like SAP Hana are symptomatic of the trend to merge operational
and business intelligence data management structures into one. This reduces
the complexity of IT architectures and increases the possibility of creating a
‘single-version-of-the-truth’.
4. More focus on predictive technologies
What tends to happen when people use business intelligence (when it works
well) is they start to see in dashboards and activities patterns of ‘things that
happen’ they can act on. Over time it becomes apparent that the task of
seeking out these insights is itself time consuming and it would be better if the
SYSTEM could itself predict these occurrences and recommend actions. The
ability to ‘predict’ resource constraints, understand events that could create
opportunity and risk – and other stuff – becomes smarter and more effective
over time. The rewards can be enormous.
5. Platforms that cover ALL of the bases
As I outlined earlier, modern business intelligence software has to cover ALL of
the capability areas including capture, discovery and harvesting, assimilation,
analytics and interpretation, presentation, socialization and enquiry,
prediction and solutions delivery. At present only a minority of vendors are
able to service all of these bases and often they achieve this only through use
of third party apps. Progressively as the market matures and it becomes more
of a brand war than a feature by feature battle, we can expect that all of the
major vendors will have to find ways to offer COMPLETE solutions; either
through development or acquisition.
6. Cloud BI going main-stream
Business intelligence software has to-date been seen as the cherry on the
cake; something businesses purchased later when they realized the system of
record they’d purchased didn’t actually source the performance analytics
and actionable insights they required. In future, business applications that
DON’T offer rich analytics and self-service tooling to source actionable insights
simply won’t be purchased. The Software-as-a-Service (SaaS) model enables

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buyers to choose their products in full view of their strengths and weaknesses.
Vendors are no longer able to hide behind the PowerPoint sales pitch or well-
fashioned demo site. The ‘capabilities’ of business intelligence software will
eventually merge into the Social Operating Systems that people use in their
work-day and as users we will see these as features of the tools we use rather
than seeing them as something different.
7. (And finally…) Price erosion
Google said almost a decade ago that buyers could one day expect to get
‘all the software they needed’ for $10 a head. I still believe this is ultimately the
way the industry will go and it becomes all the more possible when vendors
like Amazon, Apple, Encanvas, Microsoft, IBM, Oracle, SAP, Salesforce.com
and others continue to mature their Social Operating Systems platforms in the
cloud and start to provide menu-based industry and process specific solutions
that buyers can buy with ‘good practice’ built-in.
Checklist for Buying Business Intelligence Software
Requirements vary so much for business intelligence that no single vendor
offerings will always be the best-fit. Here’s a simple check-list?
1. Qualify the role that you expect business intelligence to play in your business
and the BI capabilities you will need. Some businesses (and indeed business
models) don’t change that frequently in which case a more traditional
business intelligence platform will probably work, but if you expect users to
demand intuitive self-service tools and expect your dashboards and
operational analytics to grow and grow then one of the more ‘agile’
platforms would spring to mind. Depending on your industry there may be
vendors that have ‘ready-to-deploy’ solutions to match your immediate
role needs and bring faster ‘time-to-value’.
2. Consider where the data your business intelligence platform will need to
harvest is held and in what form – it could be coming from desktop apps,
existing administrative systems, documents, web services, third party
services etc. – and check to see if the BI tools you’re considering can
access them. Check for data connectors and assimilation capabilities.
3. Audit the ‘constructs’ you will require and make sure your BI tools have the
ability to service these requirements – either from one vendor, or from
several.
4. Review the ‘hygiene’ issues like federated user permissions management,
security, scalability, cross-browser support, multi-threading capabilities and
enquiry processing potential.

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Final Thoughts
While not all BI offerings are the same but innovation in the Business Intelligence
market does seem to be reaching its peak. While some players have fallen off of
the pace, the majority are able to offer ‘complete’ solutions one way or another;
even if it involves integration with third party tools or months of development!
Competitive differentiation is strongest in areas of:
 Real-time analytics – making sense of data while it’s still moving!
 Self-serviceability tooling – giving users the tools to serve themselves with
new analytics, new applications etc.
 Discovery (exposing new insights from queries you haven’t even thought of)
 Assimilation tooling such as data mashing and normalization
 Time-to-value (often achieved by off-the-shelf process or industry specific
dashboards and reports)
 Predictive analytics that reduces manual interventions
Faced with maturing technology, we appear to be entering a new period where
BRAND will play an ever increasing role in decision making. This is good news for
companies like SAP, IBM, Oracle and Microsoft – and potentially for Apple, Nokia,
Amazon and Samsung – that already have BIG brands, particularly as business
intelligence tooling becomes integral to business applications.
We have seen in the past 20+ years a move towards ‘platforms’ in business
computing where companies sacrifice any opportunity for competitive
advantage through the tools they use for ‘good practice processes and a single
view of data brought about by the ambition of a single computing system. This
norm of behavior in buying approaches adopted by large corporations has really
helped the larger brands to dominate.
Nevertheless, it’s not all bad news for new entrants and smaller players that may
be light on brand awareness but have the more adaptive ‘born of the cloud’
tools buyers need and the opportunity to grow their brand story thanks to the new
playing field that the cloud offers. When it comes to surfacing actionable insights
and harvesting the BIG DATA that’s becoming available to business users around
the world, there’s still plenty of room for innovation.

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About the Author
Ian Tomlin is a researcher, writer and author on topics of customer science,
organization design and agility, stretch strategy and enterprise technology. He
has worked in the European Information Technology sector since 1990 holding
sales and marketing management roles covering disciplines including business
intelligence, document management, computer printing, output management,
document, content and knowledge management, search, cloud computing,
enterprise social networking, enterprise integration, ETL and data mashups.
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Books by Ian Tomlin
Agilization – The regeneration of competitiveness (2008)
Cloud Coffee House – The birth of cloud social networking and death of the old
world corporation (2009)
SOS - Social Operation Systems (2011)
Blogs and Articles by Ian Tomlin
Loyalty Beyond Reason – iantomlin.blogspot.com @ictomo
ThinkBusinessy – thinkbusinessy.blogspot.com @ThinkBusinessy
Slideshare - www.slideshare.net/ictomlin