Comprehensive Overview of BI

A Comprehensive Overview Of BI In Today’s Data Driven World
The Fundamentals of
Business Intelligence
Presented by Beyondsoft

“Businessintelligence(BI)isaconceptthattypicallyinvolvesthedeliveryand
integration of relevant and useful business information in an organization.
Data mining is nothing new, but in the last three years, companies have
come to realize that BI is much more than corporate reporting from an
information house in the IT department.
With the advancements in visualizing information, data can be accessed
and used across the organization to cut costs, streamline organizational
efficiencies, refine products and services, and launch new ones. BI
continues to be one of the fastest moving areas in the enterprise.
So, how do mid to large size companies decipher just what data the
organization should be looking at? Additionally, how do they decide what
to do with it?
In this comprehensive guide, we outline all you need to know about data,
analysis, and business intelligence.
Introduction to
— Alvin Yang, Sean Clemmons, and Robert Newman
http://www.beyondsoft.com http://blog.beyondsoft.com

1 The Fundamentals of Business Intelligence
Business intelligence (BI) is a system of tools and methods that aid in strategic planning
and informed decision-making. This process starts with extracting raw data and outputs
actionable information that when utilized properly, can provide benefits throughout the
organization. Although the breadth of a BI system differs from company to company,
possible components from end-to-end include:
What Is
Information Discovery and Management
The process of collecting data and preparing it for analysis. Data is
extracted from internal and external sources, data provenance, data
governance, data dictionaries, and ontology.
Intelligence
Running queries, DSS, intelligence systems, A/B testing, and
employing machine learning in order to analyze data to gain insights.
Visualizing data relationships for decision makers
Produce graphs and charts to represent insights derived from
comprehensive analysis through dashboards, GIS, and visual
analytics in order to distribute to decision makers and their teams.

Data is raw or unorganized information that is the essential building block of any business
intelligence system. Data is source material with the potential to provide continuous
discovery. Typically, data comes from one of four sources:
PRIVATE
Data from within the company,
such as proprietary data, that is
usually the first to be gathered.
Understanding
Data
STREAMING
Data transference from
interconnected devices that
are mined as data arrives.
SOCIAL MEDIA
Unstructured or semi-structured
information derived from online
social interactions.
PUBLICLY AVAILABLE
Information acquired from open
sources, such as data.gov or the
CIA World Factbook.
1 2
43

Data on its own –– no matter how well managed, processed, and governed –– holds
little value. Value derives from the analysis of data sets and from the insights that arise
during the analysis. Effective analysis involves finding meaningful patterns in the data and
relating those patterns to the business context. There are four general types of analysis
that organizations can employ:
Descriptive Analytics:
This most basic form of analytics involves using
historical and real-time data to find overall
tendencies and learn from past behaviors.
It is the building block for subsequent types
of analysis. General examples of descriptive
statistics include sums, averages, and
percentage changes. By using descriptive
statistics, companies can answer: What
happened and why?
Understanding
Data (continued)
Predictive Analytics:
Once descriptive statistics are in place, analysts
can combine historical data with predictive
algorithms to make predictions about future
outcomes. Predictive analytics can help with
planning and goal setting. Predictive analytics can
answer: What might happen next? Keep in mind
that the insights derived are only probabilities.
Prescriptive Analytics:
This type of advanced analytics inserts
predictive analytics into a business context to
optimize decision making. Examples include
business rules, algorithms, machine learning,
and computational modelling. Prescriptive
analytics presents projected outcomes for
potential actions, providing insights on what to
do next.
Diagnostic Analytics:
Diagnostic answers the question of how
and why of something has happened or is
happening. In order to produce insights, it
leverages techniques such as drill-down,
discovery, mining and correlations to find
patterns and trends. Diagnostic analytics
can be used to provide an understanding on
cross-functional data, thus enabling strategy
development revolving around cost, profit and
risk, and performance variations.

Help you understand customer behavior:
The use of data streamlines business
functions in many ways. According to
Datameer, 48% of companies use it to
conduct customer analytics, 21% use it for
operational analytics, 12% use it to prevent
fraud and ensure privacy compliance, and
10% use it to create new product and
service innovation.
Improve your product:
Through product data analysis, you can
identify and address quality or inconsistency
issues in your product and increase efficiency
of product development. By developing alerts
to continually monitor for anomalies, you
can identify product vulnerabilities and
remedy the situation proactively, maximizing
revenues. When new features
or enhancements are added, you can ensure
that the design of each feature is done
with an eye on the information gathered in
reporting and analysis.
What Can Business Intelligence
Do for You?
Improve company efficiency:
Data helps shed light on where efficiencies
can be improved. This can include one
or more areas like overstock, slowed
production, and low employee satisfaction.
It can also prevent short-term bottlenecks
from becoming bigger problems. By
having a centralized data system, you can
quickly identify causes of problems from
the source and tackle them immediately.
Gain competitive advantage:
By analyzing performance data against
competitors, you can determine where you
are outperforming and underperforming
other businesses in your market. With
BI mapping tools, you can visualize how
you compare in shared geographical
areas. These insights can help you decide
whether or not to expand to a new area
and where to focus marketing efforts.

Improve sales:
By leveraging sales-related data, you can
enhance your sales strategy, yielding bigger
returns and anticipating future issues.
Comparative analysis can identify gaps
in sales, capitalizing on areas that are
propelling revenue and troubleshooting in
low-performing areas. BI mapping provides
insight into customer demand, suggesting
where to funnel efforts and which new
endeavors are smart for your business.
Improve marketing:
Marketers have utilized BI for years to
achieve a variety of gains. Some of these
include: analyzing social media to determine
where to focus efforts, assessing ROI to
discover what motivates consumer behavior,
and segmenting the market to build brand.
Recent advances in audience targeting
enable markets to align their strategies with
customer sentiment and trends.
What Can Business Intelligence
Do for You? (continued)
Gain user visibility:
By having a comprehensive BI strategy
in place, you can gain visibility into every
facet of the company. This is especially
important within complex supply chains
that involve a plethora of users and
factors. This visibility leads to enhanced
reporting and informed decision making
across all levels.
Turn data into actionable information:
Through analysis, data is interpreted and
enriched. When this analysis is outputted
in reports, insights and recommendations
become visible and bring the data into
the business context. BI tools place these
reports in the hands of high and low level
decision makers, helping them see what
the best course of action is. By focusing
on KPIs, you can track progress on those
factors that are paramount to reaching
your goals. BI bridges the gap between
the data analysts and the business users.

How to Determine
If You Need BI
The Economist Intelligence Unit reports that 48% of organizations using BI feel that they
have missed opportunities to make the most of their data. To avoid missed opportunities,
look for these three major indicators that your organization needs to revamp its BI system:
Data, but no information: This means that you have a wealth of
information, but need assistance aggregating and analyzing it. You cannot
turn data into actionable insights because you are missing the intelligence
part, the operations that make this data valuable.
Relying solely on IT for reports: If you are constantly pestering the IT
department to produce reports, you are needlessly keeping them from
doing other important work. Data should be brought to those people within
the business who can utilize it. By implementing an easy to use BI tool,
those making the decisions can do the work themselves, leading to faster
decision-making and freeing up IT for other tasks.
Using spreadsheets without BI software: Spreadsheets do not present
data in real time and are often isolated. If you are only using Excel, you are
missing out on the speed and ease that BI tools provide for combining data
from many sources and sharing and updating reports.

How to Determine
What to Track
According to Alvin Yang, Senior Vice President at Beyondsoft, “Once data is prepared and
cleansed, BI professionals must determine what to measure, which changes over time depending
on current goals.” Tracking too many metrics leads to dashboard overload, which can cause
significant data to be lost in the noise. Worthwhile metrics to track are simple to understand and
use, can be replicated effortlessly, and present valuable, actionable information that impacts the
business. When determining what to track, consider these types of metrics:
Qualitative vs. Quantitative
Qualitative metrics provide intangible information, such as survey responses and customer
feedback. They provide behavioral insight and answer how and why. Quantitative metrics are
hard data and statistics that can be aggregated and evaluated to show trends. They show the
who, what, and where. These metrics are better to follow because they are more objective and
easier to analyze.
Vanity vs. Actionable
Vanity metrics make a company look good, but do not hold much meaning because they can
easily be manipulated. They are best to avoid when decision-making. However, by asking
questions like “Where are users going when they leave the page” they may lead you to
discover actionable metrics to follow. Actionable metrics are tied to tasks and are specific to
goals of the business, such as revenues or number of active users. They provide guidance
on what might be going wrong in your business. Actionable metrics do not necessarily solve
problems, but they do point you in the right direction.

How to Determine
What to Track (continued)
Reporting vs. Exploratory
Reporting metrics include typical reports that reveal what is happening in an organization, such
as how many products were sold over a given time. On their own, they may not lead to any
actionable discoveries, but they are good for measuring progress. Exploratory metrics require
searching through information to uncover a solution to a problem that may be hidden within the
data. These metrics require more user effort, but they can lead to powerful discoveries.
Correlated vs. Causal
Correlated metrics involve examining metrics that change simultaneously to make predictions.
Causal metrics involve experimenting to discover the cause of a correlation, giving you the
opportunity to influence it. Finding causality is difficult because a correlation may be influenced
by multiple outside factors and require a great deal of experimentation to determine.
Lagging vs. Leading
Correlated metrics involve examining metrics that change simultaneously to make predictions.
Causal metrics involve experimenting to discover the cause of a correlation, giving you the
opportunity to influence it. Finding causality is difficult because a correlation may be influenced
by multiple outside factors and require a great deal of experimentation to determine.

Beyondsoft Sports
(Sounders) Case Study
The Seattle Sounders entered 2015 with high
expectations following the most successful
season in the club’s history the year prior. By
the standard which they laid out for themselves,
the 2015 season must be classified as a failure.
While the team’s results can help tell the story
at the highest level, in order to properly assess
the causes of the team’s shortcomings in 2015,
a closer look at the numbers that led to those
results is needed. The key questions needing
to be answered heading into the offseason
relate to whether or not the 2015 season’s
results are likely to be repeated. Putting the
data into its proper context is vital to performing
the proper analysis.
Implications
The data behind this Power BI report has been
compiled from publicly available sources. The
majority of the information comes directly from
the official website of Major League Soccer.
Schedule and venue information comes from
official team websites. Geolocation data has
been pulled from Wikipedia. All-up statistical
information shows a player’s impact over
the course of the full season, while per-90-
minute rate statistics allow an individual’s
contribution to be projected over the course of
a full season. This is crucial in evaluating this
season in particular, as many key players were
unavailable for long stretches of the season at
a rate far exceeding what would typically be
expected.
Looking at team-wide, per-game statistics over
time also highlights the difference in performance
between the team at full-strength and the team in
a weakened state. The metrics contained within
this report help to tell a more in-depth story than
a glance at the final table. They also help answer
some key questions about the causes of this year’s
struggles. Given the variety of data points included
in the model, the available metrics can help to
adequately tell the story of past or future seasons
as well.
The following custom Power BI dashboard displays an analysis
of the Seattle Sounders 2015 season, and shows how data can
be used to create visuals that answer questions.

Beyondsoft Sports
(Sounders) Case Study
Dashboard View 1
Shows: General season results overview: the team’s progress by
month
Answers: Did they improve or get worse? At what points
in the season were they lagging?
How can this information impact decisions?:
This information can impact training decisions and determine
pacing throughout the season depending on what parts of the
season saw lower performances.
Dashboard View 2
Shows: Breakdown of high-level metrics by game location
Answers: In which locations did the team play better?
Worse performance at away games can suggest utilizing
better performing players for longer during away games. Better
performance at home games, or in certain other locations, can
suggest resting better performing players at the start of the game
and utilizing them later, if the team falls behind.
Dashboard View 3
Shows: Statistics by individual player
Answers: How important was each player to the club’s success?
This shows which players improved throughout the season and
deserve more playing time, as well as who performed better under
pressure. It also reveals which players fell in performance and
why that may have happened. For coaches, this can determine
who deserves more playing time and where on the field and when
during the game and/or season to utilize each player.

The Future of
Moving forward, understand company data is going to be paramount to success. According to
Sean Clemmons, GM of Data and Analytics at Beyondsoft:
On a larger scale, the cloud is finally settling down into a high quality tool for BI to leverage, rather
than the latest tech cure-all. Moreover, customers are asking for intelligence divisions and agency
partners to help them understand what parts of their data should move to the cloud, what should
stay on permanently, and how to bring those sets together into high quality information.
On another front, self-serve business intelligence remains a carryover theme from previous years;
ensuring the industry is getting the information in the hands of the business, not just IT. The skillset
to comprehensively leverage BI requires more business understanding than in IT and more tech
knowledge than is typically found in business. The progression of Qlik, Tableau, PowerBI, and
others have made self-serve BI less of a reach.
Today, the tools to create good BI have become less expensive, more attractive, and easier to use.
That said, the volume of data behind them has grown exponentially, which creates its own challenges.
As more companies produce positive results like these, staying afloat among competitors requires
assessing your system and replacing outdated tools and tactics.
“The overarching goal of business intelligence is to swiftly deliver pertinent information to those who can
use it to make key decisions that will generate progress towards the company’s objectives,” says Peter
Huang, Director of Data and Analytics at Beyondsoft. “To see positive return on your BI investment,
these objectives must be clearly defined beforehand and kept in mind throughout the process – from
strategizing, to choosing tools, to determining KPIs to track,” he adds.
To ensure your efforts are comprehensive, reach beyond diagnostics and aim to predict future
outcomes and prescribe potential solutions, maximizing insights that can positively impact present
and future business.
Do you want to learn more?
Visit blog.beyondsoft.com or contact us at Beyonddata@us.beyondsoft.com, to see how Beyondsoft
can make your data work better for your organization.

Who is
Beyondsoft
Beyondsoft is a global IT Consulting, Solutions and
Services provider. Founded in 1995 and headquartered
in Seattle, Washington, Beyondsoft has over 30 global
offices, R&D bases and delivery centers, as well as
facilities in United States, Japan, China, India, Canada
and Singapore. Relying on its strong R&D heritage
and ability to innovate, we are now focusing on using
emerging, disruptive technologies, such as cloud, mobility,
big data and analytics, to provide powerful solutions
and products for clients in a wide range of industries
including: high-tech, e-Commerce, finance, automobile,
retail, logistics, energy, manufacturing, healthcare,
telecommunications, media & entertainment, and travel.
Our comprehensive worldwide delivery and service
network is built on years of deep industry experience
and business process excellence. It’s supported by an
international team of experts with the practical abilities,
dedication and innovative spirit to help global clients
achieve and maintain the highest levels of operational
excellence and profitability, and to continuously create
value for their stakeholders. The management team
is headed by Alvin Yang, Senior Vice President at
Beyondsoft.
Learn more about Business
Intelligence, Beyondsoft and
industry trends by following
us on social media:
Twitter:
twitter.com/beyondsoftUS
Facebook:
facebook.com/beyondsoftUS
LinkedIn:
linkedin.com/company/beyondsoft
YouTube:
youtube.com/channel/UC6f-
WNxipK3R9EschRo5RExA
Instagram:
instagram.com/beyondsoftUS

References
Halper, Fern. Four Reasons to Analyze Customer Behavior. TDWI Research. August 25, 2015.
Kondo, Naka. The Business of Data. The Economist Intelligence Unit. January 12, 2016.
McKenna, Brian. Amadeus Aims to Add More Business Intelligence to Travel Industry. Computer Weekly. July 7, 2015.
Popky, Linda J. Identifying the Marketing Metrics That Actually Matter. Harvard Business Review. July 14, 2015.
Steinberg, Leigh. Changing the Game: The Rise of Sports Analytics. Forbes. August 18, 2015.
2015 State of the Industry. Datameer. 2015.
2015 Supply Chain Report. Raconteur. 2015.

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