Module 3 - Improving Current Business with External Data- Online

D: DRIVE
How to become Data Driven?
This programme has been funded with
support from the European Commission
Module 3: Improving current
business with external data

Smart Data Smart Region | www.smartdata.how
This programme has been funded with support from the European Commission. The author is
solely responsible for this publication (communication) and the Commission accepts no
responsibility for any use that may be made of the information contained therein.
The objective of this module is to gain an overview how
you can use the data available outside of your company
to improve your business.
Upon completion of this module you will:
- Learn the basics of external data and where to find it
- Be able to recognize there is a lot of Open Data
already out there for you to use
- See the benefits of using the external data in order to
improve your business
Duration of the module: approximately 2 – 3 hours
Module 3: Improving
current business
with external data

1 External data
2
This programme has been funded with support from the European Commission. The author is
solely responsible for this publication (communication) and the Commission accepts no
responsibility for any use that may be made of the information contained therein.
– The benefits using external data
– The challenges associated with using the
external data
– Why external data is the fuel of your
business
The Bussines Aspect of External Data
– Primary Data
• Sources of Primary Data
– Secondary Data
• Sources of Secondary Data
– Open Data
• Defining Open Data
• Big Data vs Open Data
• Benefits
– Factors of Data Quality

EXTERNAL DATA
1. Primary Data
1. Sources of Primary Data
2. Secondary Data
1. Sources of Secondary Data
3. Open Data
1. Defining Open Data
2. Big Data vs Open Data
3. Benefits
4. Factors of Data Quality

Data is everywhere. That fact is not necessarily
new or interesting—great minds of past
generations have long harnessed and utilized data
in order to inform their decisions, create and test
hypotheses, and attempt change the world.
But “data is everywhere” doesn’t have the same
meaning for our generation as it did for past
generations. For us, it’s a nod to the fact that we
are more connected to each other, to the
businesses we buy from, and to the world than
ever before. Today, thanks to the widespread
adoption and use of the Internet, we have instant
and real-time access to an incomprehensibly large
amount of data.

When most people think about Big Data and
Business Intelligence they think about internal
data (module 2). But the problem with internal
data is that it only paints part of the picture.
So what’s missing?
The answer, as you may have guessed, is external
data.

External data can be divided into two categories:
1. Primary data
• It refers to the information collected by the researcher from original sources. It is not
a published data; it has to be gathered by the researcher himself by tapping various
resources. Primary data is usually collected for specific purposes.
• It is a very slow process of collecting data and involves huge costs. But results
obtained from this data are original and tend to be more accurate and reliable.
2. Secondary data
• Secondary data is already existing which has been collected and published by some
individuals or institutions. This data is available at a very low cost and it requires lesser
time to collect it.
• Open data!
EXTERNAL DATA
External data refers to data
generated from outside an
organization. It can come
from a variety of places
and serve nearly every
industry in the business
world.

PRIMARY DATA
Primary data is unique, original, reliable and accurate in nature, since it has not been changed or altered by human beings, therefore its validity is greater than
secondary data. It is also specially collected for a research project.
Interview Questionnaire Focus group
Community
forums and
public hearings
Observation
Case study
Key informants
interview
Online
research
methods
There are several methods of collecting primary data:

A questionnaire is a research instrument consisting of a series of questions (or other types of prompts) for
the purpose of gathering information from respondents. A distinction can be made between questionnaires
with questions that measure separate variables, and questionnaires with questions that are aggregated into
either a scale or index. Questionnaires with questions that measure separate variables, could for instance
include questions on:
• preferences (e.g. political party)
• behaviors (e.g. food consumption)
• facts (e.g. gender)
Questionnaires with questions that are aggregated into either a scale or index, include for instance questions
that measure:
• latent traits
• attitudes (e.g. towards immigration)
• an index (e.g. Social Economic Status)
Questionnaire
PRO‘s
•Inexpensive
•It can be widely used
•Quick
•Easy to analyze
CON‘s
•Very low return rates
•Because of the specific questions the
information gained can be minimal
•They can contain quite large measurement
errors
•There is a long delay in receiving filled in
questionnaires

An interview in qualitative research is a conversation where questions are asked to elicit information.
The interviewer is usually a professional or paid researcher, sometimes trained, who poses questions to
the interviewee, in an alternating series of usually brief questions and answers.
When choosing to interview as a method for conducting qualitative research, it is important to be tactful and
sensitive in your approach. While an interviewer generally enters each interview with a predetermined,
standardized set of questions, it is important that they also ask follow-up questions throughout the process.
Such questions might encourage a participant to elaborate upon something poignant that they’ve shared
and are important in acquiring a more comprehensive understanding of the subject matter. Additionally, it is
important that an interviewer ask clarifying questions when they are confused. If the narrative, details, or
chronology of a participant’s responses become unclear, it is often appropriate for the interviewer to ask
them to re-explain these aspects of their story so as to keep their transcriptions accurate.
Interview
PRO‘s
•Simple and convenient
•Saves time, money and labor
•Useful in investigation of a large area
•Adequate information can be gained
CON‘s
•Information can‘t be relied as absence of
direct contact
•Intewview with an improper man will spoil
the results
•To get real data, a sufficient number of
people are to be interviewed
•Careless attitude of informant affects the
degree of accuracy

The essence of survey method can be explained as “questioning individuals on a topic or topics and then
describing their responses”. In business studies survey method of primary data collection is used in order to
test concepts, reflect attitude of people, establish the level of customer satisfaction, conduct segmentation
research and a set of other purposes.
Survey method pursues two main purposes:
• Describing certain aspects or characteristics of population and/or
• Testing hypotheses about nature of relationships within a population.
Survey method can be broadly divided into three categories:
• mail survey – a written survey that is self-administered
• telephone survey – a survey conducted by telephone in which the questions are read to the respondents
• personal interview - a face-to-face interview of the respondent
Survey
PRO‘s
• Highly accurate, reliable and valid
• Allows for comparisons with
other/larger populations when items
come from existing instruments
• Easily generates quantitative data
CON‘s
• Relatively high costs
• Slow to design, implement and analyze
• Accuracy depends on who and how
many people sampled
• May have low response rates
• Little opportunity to explore issues in
depth

A case study is a research method involving an up-close, in-depth, and detailed examination of a subject of
study (the case), as well as its related contextual conditions. In doing case study research, the "case" being
studied may be an individual, organization, event, or action, existing in a specific time and place. For
instance, clinical science has produced both well-known case studies of individuals and also case studies of
clinical practices.] However, when "case" is used in an abstract sense, as in a claim, a proposition, or an
argument, such a case can be the subject of many research methods, not just case study research.
Case study research can mean single and multiple case studies, can include quantitative evidence, relies on
multiple sources of evidence, and benefits from the prior development of theoretical propositions.
Case study
PRO‘s
• Direct behavioral study
• Real and personal experience record
• Make possible the study of social
change
• Increase analysis ability and skills
CON‘s
• Each case is different from another
case
• Personal bias
• It can be used only in a limited sphere
• It demands more time
• Money consuming

A focus group is a small, but demographically diverse group of people and whose reactions are studied
especially in market research or political analysis in guided or open discussions about a new product or
something else to determine the reactions that can be expected from a larger population.
It is a form of qualitative research consisting of interviews in which a group of people are asked about their
perceptions, opinions, beliefs, and attitudes towards a product, service, concept, advertisement, idea, or
packaging. Questions are asked in an interactive group setting where participants are free to talk with other
group members. During this process, the researcher either takes notes or records the vital points he or she is
getting from the group. Researchers should select members of the focus group carefully for effective and
authoritative responses.
Focus group
PRO‘s
•Low costs
•Rapid data collection
•Participants define what is important
•Some opportunity to explore issues in
depth
•Opportunity to clarify responses through
probes
CON‘s
•Can be time consuming to assemble groups
•Produces limited quantitative data
•Requires trained facilitators
•Less control over process than key
informant interviews
•Difficult to collect sensitive information
•May be difficult to analyze and summarize
findings

Observation, as the name implies, is a way of collecting data through observing. Observation data collection
method is classified as a participatory study, because the researcher has to immerse herself in the setting
where her respondents are, while taking notes and/or recording.
Observation as a data collection method can be structured or unstructured. In structured or systematic
observation, data collection is conducted using specific variables and according to a pre-defined schedule.
Unstructured observation, on the other hand, is conducted in an open and free manner in a sense that there
would be no pre-determined variables or objectives.
Observation
PRO‘s
•Setting is natural, flexible and unstructured
•Evaluator may make his/her identity known
or remain anonymous
•Evaluator may actively participate or
observe passively
•Can be combined with a variety of other
data collection methods
•Generates relevant, quantifiable data
•Most useful for studying smaller units
CON‘s
•Requires a skilled observer
•The evaluator has less control over the
situation in a natural enviroment
•Hawthorne effect – if group is aware that
they are being observed, resulting
behaviour may be affected
•Can not be generalized to entire population
unless a plan for representativness is
developed

Key informant interviews are qualitative, in-depth interviews of 15 to 35 people selected for their first-hand
knowledge about a topic of interest. The interviews are loosely structured, relying on a list of issues to be
discussed. Key informant interviews resemble a conversation among acquaintances, allowing a free flow of
ideas and information. Interviewers frame questions spontaneously, probe for information and takes notes,
which are elaborated on later.
The following are two common techniques used to conduct key informant interviews:
• Telephone Interviews
• Face-to-Face Interviews
Key informant
interview
PRO‘s
• Low costs
• Respondents define what is important
• Rapid data collection
• Possible to explore issues in depth
• Opportunity to clarify responses
through probes
• Sources of leads to other data sources
and other key informants
CON‘s
• Can be time consuming to set up
interviews with busy informants
• Requires skilled and/or trained
interviewers
• Accuacy is limited and difficult to secify
• Produces limited quantitative data
• May be difficult to analyze and
summarize findings

A series of public meetings to involve the community in defining and discussing needs. These methods are
data-gathering techniques from the political arena. Community forums are less formal and open to the
public, while hearings consist of testimony from selected witnesses and often the issuance of a summary
report.
Community
forums and
public
hearings
PRO‘s
•They can raise the credibility of the needs
assessment process by enhancing openness
and inclusion
•These activities are inexpensive and
relatively easy-to-arrange
•Community members who were not
selected for planning group membership
can participate
•Forums and hearings can raise the level of
awareness and understanding about your
issue and the community planning initiative
•These methods can be a way to build
community ownership of and investment in
your issue and the planning process
•The meetings may reveal issues that
warrant further investigation
CON‘s
•Community members who choose to
participate may not be completely
representative of the community;
remember, some people with good ideas or
a clear understanding of the issues do not
like to speak at such events
•Just because the needs may be stated
eloquently and with many listeners, does
not mean that other data collection
methods should be discounted
•Do not allow representation to become too
narrow; the needs identified depend on the
characteristics and backgrounds of those
who participate
•Do not use hearings/forums as your
primary data collection method

Online research methods are the digital tools and processes used to gather information on a topic from an
internet search. The information gathered may include both factual information and the opinions of experts.
They help people find the information they need quickly. Online tools provide information instantly. This
information would take much longer to locate using offline research methods (such as searching for books in
a library).
Some specific types of method include:
• Cyber-ethnography
• Online content analysis
• Online focus groups
• Online interviews
• Online qualitative research
• Online questionnaires
• Social network analysis
• Web-based experiments
• Online clinical trials
Online
research
methods
PRO‘s
•Automated data collection
•Minimal cost
•Easier targeting of respondents across
numerous segmentation variables
•Rapid turnaround
CON‘s
•Limited to internet population
•Respondent fraud and bias
•Researcher bias

SECONDARY DATA
Secondary data is research data that has previously been
gathered and can be accessed by researchers. The term
contrasts with primary data, which is data collected directly
from its source.
Secondary data is used to increase the sampling size of
research studies and is also chosen for the efficiency and
speed that comes with using an already existing resource.
Secondary data facilitates large research projects, in which
many research groups working in tandem collect secondary
data. The main researcher is then allowed to focus on
primary research or particular areas of interest. This
division of labor helps researchers learn more in less time.

Sources of Secondary data:
PUBLISHED PRINTED SOURCES
Books
Books are available
today on any topic
that you want to
research. The uses of
books start before
even you have
selected the topic.
After selection of
topics books provide
insight on how much
work has already
been done on the
same topic and you
can prepare your
literature review.
Journals
Journals and
periodicals are
becoming more
important as far as
data collection is
concerned. The
reason is that
journals provide up-
to-date information
which at times books
cannot and secondly,
journals can give
information on the
very specific topic on
which you are
researching rather
talking about more
general topics.
Magazines/
Newspapers
Magazines are also
effective but not
very reliable.
Newspaper on the
other hand is
morereliable and in
some cases the
information can only
be obtained from
newspapers as in
thecase of some
political studies.
Commercial
services
Published market
research reports and
other publications
are available from a
wide range of
organisations which
charge for their
information.
Typically, marketing
people are
interested in media
statistics and
consumer
information which
has been obtained
from large scale
consumer or farmer
panels.
General Websites
Generally websites
do not contain very
reliable information
so their content
should be checked
for the reliability
before quoting from
them.
Blogs
Weblogs are also
becoming common.
They are actually
diaries written by
differentpeople.
These diaries are as
reliable to use as
personal written
diaries.
UNPUBLISHED SOURCES
National and
international
institutions
Bank economic
reviews, university
research reports,
journals and articles
are all useful sources
to contact.
International
agencies such as
World Bank, IMF,
IFAD, UNDP, ITC,
FAO and ILO produce
a plethora of
secondary data
which can prove
extremely useful to
the marketing
researcher.
Trade Associations
Trade associations
differ widely in the
extent of their data
collection and
information
dissemination
activities. However,
it is worth checking
with them to
determine what they
do publish. At the
very least one would
normally expect that
they would produce
a trade directory
and, perhaps, a
yearbook.
Government
Records
Government records
are very important
for marketing,
management,
humanities and
social science
research.
These may include
all or some of the
following:
· Population
censuses
· Social surveys,
family expenditure
surveys
· Import/export
statistics
· Production
statistics
· Agricultural
statistics.

DIFFERENCE BETWEEN PRIMARY
AND SECONDARY DATA
Primary data
• Real time data
• Sure about sources of data
• Help to give results/findings
• Costly and time consuming
process
• Possible bias results
• More flexible
Secondary data
• Past data
• Not sure about the sources of
data
• Refining the problem
• Cheap and doesn‘t take too
much time
• Can not now if data is bias or
not
• Less flexible

Data is the raw
material of the new
industrial revolution.
Francis Maude MP

DEFINING OPEN DATA
Data enrichment refers to
processes used to enhance, refine
or otherwise improve raw data.
This idea and other similar
concepts contribute to making
data a valuable asset for almost
any modern business or
enterprise.
Data, that is made available
by organizations,
businesses and individuals
for anyone to access, use
and share.
Open data has to have a license that says it is open data. Without a license, the data
can’t be reused. The license might also say:
– that people who use the data must credit whoever is publishing it (this is called
attribution)
– that people who mix the data with other data have to also release the results as
open data (this is called share-alike)

1
2
3
• Large datasets from
scientific research,
social media or
othe non-
government
sources
• Large government
datasets (weather,
GPS, healthcare,...)
• Public data from
state, local, federal
government
(budget data,...)
BIG DATA
• Non-public
data for
marketing,
business
analysis,
national
security
OPEN DATA
• Business reporting and
other business data
(consumer complaints,...)
OPEN
GOVERNMENT
• Citizen
engagement
programs not
based on data
(petitions,
websites,...)
BIG DATA
VS
OPEN DATA
Intersection of the three concepts
defines the six subtypes of data
shown on the diagram. There’s no
separate category for the
intersection of Big Data and Open
Government – anything in that
category is also Open Data.

1. Big Data that’s not Open Data. A lot of Big Data falls in this category, including some Big Data that has great commercial value. All of the data that large retailers
hold on customers’ buying habits, that hospitals hold about their patients, or that banks hold about their credit-card holders, falls here. It’s information that the
data-holders own and can use for commercial advantage. National security data, like the data collected by the NSA, is also in this category.
2. Open Government work that’s not Open Data. This is the part of Open Government that focuses purely on citizen engagement. For instance, the White House
has started a petition website, called We the People, to open itself to citizen input. While the site makes its data available, publishing Open Data – beyond
numbers of signatures – is not its main purpose.
3. Big, Open, Non-Governmental Data. Here we find scientific data-sharing and citizen science projects. Big data from astronomical observations, from large
biomedical projects like the Human Genome Project, or from other sources realizes its greatest value through an open, shared approach. While some of this
research may be government-funded, it’s not “government data” because it’s not generally held, maintained, or analyzed by government agencies. This category
also includes a very different kind of Open Data: the data that can be analyzed from Twitter and other forms of social media.
4. Open Government Data that’s not Big Data. Government data doesn’t have to be Big Data to be valuable. Modest amounts of data from states, cities, and the
federal government can have a major impact when it’s released. This kind of data fuels the participatory budgeting movement, where cities around the world
invite their residents to look at the city budget and help decide how to spend it. It’s also the fuel for apps that help people use city services like public buses or
health clinics.
5. Open Data – not Big, not from Government. This includes the private-sector data that companies choose to share for their own purposes – for example, to
satisfy their potential investors or to enhance their reputations. Environmental, social, and governance (ESG) metrics fall here. In addition, reputational data,
such as data from consumer complaints, is highly relevant to business and falls in this category.
6. Big, Open, Government Data (the trifecta). These datasets may have the most impact of any category. Government agencies have the capacity and funds to
gather very large amounts of data, and making those datasets open can have major economic benefits. National weather data and GPS data are the most often-
cited examples. U.S. Census data, and data collected by the Securities and Exchange Commission and the Department of Health and Human Services, are others.
With the new Open Data Policy, this category will likely become larger, more robust, and even more significant.
The diagram explained:

Open Government Data is a
wealth of untapped
potential. As with any
initiative within the public
domain, it also involves
expenditures and the effort
of internal resources. Better
understanding the benefits
of Open Data can help
accelerate the commitment
around your Open Data
initiative. The following
overview provides more
evidence of these benefits
to support your initiative.
BENEFITS • It provides citizens with a reliable knowledge base regarding government and public sector bodies’ activities.
• It enables them to take part in public sector bodies’ activities and therefore participate actively to the public
choices (eDemocracy).
• It represents the initial material for public or private stakeholders to develop new added-value services and
supply them to citizens.
• It is one of the crucial tasks to fulfil the aim of the Digital Agenda for Europe to “deliver sustainable economic
and social benefits from a digital single market based on fast and ultra-fast internet and interoperable
applications” (Kolodziejski, 2013)
• Opening up data can optimise your process internally. When data is open, none of your colleagues will have to
go through an internal process to receive particular data. Many organisations have encountered the benefit of
having their data open, simply because it takes less time to find data. Remember, your organisation will most
probably be the most active re-user of your data.
• Not only your organisation, but also citizens will benefit from an improved – and perhaps faster – internal
information structure. Processes will take less time, services can be digitalized, and citizens will benefit from
more efficiency and transparency. A simple example might be to apply a single data provision to your services,
thereby ensuring that users – citizens and / or businesses – will not have to keep on providing data you already
have.
• If your organisation’s data infrastructure may be outdated, your Open Data initiative might be a wonderful
chance to achieve an internal change. Many organisations have taken the opportunity to redesign their internal
data infrastructure and incorporated the publication of data as a main activity in working instructions. Talk with
the managers within your organisation what the plans are concerning IT infrastructure on data level.
• By means of user feedback, you can improve the quality of your datasets. The power of the crowd, known as
crowd sourcing, is a very efficient way of pooling resources to reach a given, sometimes surprising, result.

Benefits when Open Government Data is re-used

A trained, professional eye in today's business world
studies data analytics in data collection as a means of
extracting the most significant issues related to each
particular type of business. It is difficult to imagine those
in the restaurant industry, for example, neglecting to
gather data on competitors for their market share. Data
analytics plays a large role in financial, manufacturing,
medical, healthcare, marketing and government. Within
these industries, thousands of businesses perform data
analysis on a variety of business operations.
FACTORS OF DATA
QUALITY
Timeliness
Consistency
Validity
Accuracy
Entirety
1
2
3
4
5
To obtain optimal quality data, there are factors that should be considered. These
include:

1. The benefits using external data
2. The challenges associated with using the
external data
3. Why external data is the fuel of your
business
THE BUSINESS
ASPECT OF EXTERNAL
DATA

Organisations that use external data effectively have the
potential to place themselves ahead of the game in
terms of strategic planning and competitiveness within
the sector.
Benefits include:
THE BENEFITS OF
USING EXTERNAL
DATA
External data providers make available high quality information and data for reuse by organisations to
support strategic planning
The quality of data held is assured
Large quantities of data are freely available to organisations from providers’ websites
Bespoke services are provided when more detailed data is required
Regular publications are provided in hard copy form by some providers
High level data on peer organisations enables comparisons to be made
Time series and historical data enables comparisons over time
Training in the use of data is offered by some providers
Ongoing discussion between providers aims to provide a rounded service
Data providers are working proactively to enhance the usability of their data
Allows an organisation to benchmark specific aspects of its own performance against that of peer and/or rival
organisations.

There are still challenges in delivering and using
external data for optimum results, both for
organisations and data providers.
These challenges include:
THE CHALLENGES
ASSOCIATED
WITH USING
EXTERNAL DATA
Working with statistics is still seen as a burden rather than a benefit by some managers
Some managers still see working with statistics as a function just for the IT department
Without experience it can be difficult to frame the right question to ask external providers
It can be expensive to acquire data from external data providers
It can be difficult to translate statistics into meaningful information accurately
Providers need to supply more guidance and case studies on reuse to the sector
A lack of data join up (about the same data) between external providers can lead to inefficiency and
inaccurate outcomes
It can be difficult to join up externally with internally held data to draw accurate conclusions
It is difficult to obtain data at a sufficient level of detail for making useful comparisons with
competitors

There are a number of reasons why more
and more businesses and data professionals
are incorporating external data analytics
into their decision making processes. Here
are just a few worth mentioning that really
highlight why now is the perfect time to go
all in on external data.
WHY EXTERNAL
DATA IS THE FUEL
OF YOUR BUSINESS

External data can provide you with a
bigger picture.
As a business owner or data professional, you
need to be collecting, evaluating, and acting on
internal data. But as mentioned, that really only
gives you part of the picture. In order to get the
full view, you have to look to external data (user-
generated data, public data, competitor data,
partner data, etc).
1

Accessing external data is not costly.
Thanks to initiatives by governments and businesses
around the world, accessing external data doesn’t cost a
lot of money. In fact, a lot of databases can be accessed
for free. Where the cost does come into play, however,
is organizing, evaluating, and applying external after
the external data to specific business needs (that’s
where experienced data scientists and analysts come
into the picture!).
2

Technology and tools have made accessing
external data easier and more convenient
than ever.
It’s never been easier or more convenient to access
external data. As the world continues to become more
and more connected, and as technology continues to
advance, it’s becoming a lot easier to find, collect, and
interpret external data. You don’t need a computer
science degree or a Masters in Data Science in order to
benefit from external data. You definitely want someone
who does have those degrees on your team in order to
dive deeper into the internal and external data you
ultimately collect, but you don’t necessarily need them
in order to access or collect the data itself. A lot of the
external tools that are available today are incredibly easy
to use.
3

External data can give you real-time,
minute-by-minute updates on industry,
consumer, and product trends.
This is the biggest value for business and it’s why
external data is so important. External data analytics
can have a major impact when it comes to making
decisions about the future of a business, learning
more about the health of an industry, determining
which new products to release and where to release
them, and many, many other areas. In a lot of cases,
the tools and sites that collect and present external
data are updating information in real-time—which is
invaluable during times when an informed decision
needs to be made fast.
4

External data can give you a leg up on
competition.
The other major benefit of external data is that it
creates an opportunity to get a leg up on
competition. There are a lot of tools out there
that make it easier than ever to keep an eye on
your competition in order to stay ahead of the
game. With competition for the attention of
online consumers at an all time high, the ability to
quickly, easily, and regularly check up on
competition in invaluable and can mean the
difference between growing your business or
closing your doors for good.
5

More and more data is being uploaded
to the web everyday.
Consider the following statement from Rose
Business Technologies: “IDC estimates the volume
of digital data will grow 40% to 50% per year. By
2020, IDC predicts the number will have
reached 40,000 EB, or 40 Zettabytes (ZB). The
world’s information is doubling every two years.
By 2020 the world will generate 50 times the
amount of information and 75 times the number
of “information containers” while IT staff to
manage it will grow less than 1.5 times.”
6

Data will talk, if you‘re
willing to listen.
Jim Bergeson

www.smartdata.howwww.facebook.com/smartdatasr

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