Smart Data Module 2 d drive_own data

D: DRIVE
How to become Data Driven?
This programme has been funded with
support from the European Commission
Module 2: Improving current
business with own 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 you already have available to
improve your business.
Upon completion of this module you will:
- Learn the tips of how take advantage of the existing
data you already have
- Be able to locate where internal data already lies
within your company
- Recognize the importance of implementing data
enrichment into your big data projects
- See how data can help you to build your brand
Duration of the module: approximately 1 – 2 hours
Module 2: Improving
current business
with own data

1 Advantages of Smart Data
2
Data Enrichment3
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.
– Sources of Data
– Sources of Internal Data
Data Collection
– Why Data Enrichment is a must
– How does it work?
– The Steps of Integration
– The Principles of Data Enrichment
– Why is Smart Data smart?
– How to turn your Data into
Competitve Advantage?
Using Data to build your Brand4
– How can Data help you build your
Business
– The Benefits of using Internal Data in
Marketing

ADVANTAGES OF
SMART DATA
1. Why is Smart Data smart?
2. How to turn your Data into Competitve
Advantage?

It's not important how much data you have,
it's about how well you use it. Big Data could
potentially be just a big a problem. Smart
Data is a solution that changes the game of
marketing, and how we deliver better
solutions for customers from this point
forward.

• Smart in what data to collect, validate and transform
• Smart in how data is stored, managed, operated and used
• Smart in taking actions based on results of data analysis including
organisation structures, roles, devolution and delegation of decision-
making, processes and automation
• Smart in being realistic, pragmatic and even sceptical about what can be
achieved and knowing what value can be derived and how to maximise
value obtained
• Smart in defining achievable, benefits-lead strategy integrated with the
needs business and in its implementation
• Smart in selecting the channels and interactions to include smart data
use cases
More focussed investment in achieving better
business and organisation results
Greater confidence by the business and organisation
in justifying and approving investment and resource
allocation
Quick delivery of results
WHY IS SMART DATA SMART?
SMART DATA MEANS BEING...

The real challenge of Big Data is
not technological: it is "business".
It will necessarily involve human
expertise to enrich the data and
get it to "speak". When turning big
into smart, be aware of next tips!
HOW TO TURN
YOUR DATA
INTO COMPETITIVE
ADVANTAGE
Big Data is a project, not a tool!
Ask the right questions
Start with internal data
Enrich and cross-reference existing data
Enrich the models with external data
Involve business experts
Do not presume what the outcome will be
Remain agnostic
1
2
3
4
5
6
7
8

1. Sources of Data
– Internal
• Sources of Internal Data
– External
DATA COLLECTION

Big Data is not
neccessarily big. The
most „magical“ aspect
of big data is what I
call „Smart Data“.
Philip Brittan

The data collection component of research is common to all fields of study including
physical and social sciences, humanities, business, etc. The goal for all data collection is to
capture quality evidence so as to translate into rich data analysis.
DATA COLLECTION
Data collection is the process
of gathering and measuring
information on variables of
interest, in an established
systematic fashion that
enables one to answer stated
research questions and
evaluate outcomes.
Need of Data Collection
• To get information for analysis
• To get idea about real time situation
• To compate between two situations
Factors to be considered before collection of Data
• Scope of the enquiry
• Sources of information
• Quantitive expression
• Techniques of data collection
• Unit of collection

SOURCES OF DATA
DATA
INTERNAL SOURCES EXTERNAL SOURCES
PRIMARY SOURCES
SECONDARY
SOURCES

Sources of Internal Data
Before decision-makers and data scientists look for external sources, it’s critical to ensure that all of a business’s internal data sources are mined,
analyzed and leveraged for the good of the company. While external data can offer a range of benefits, internal data sources are typically easier to
collect and can be more relevant for the company’s own purposes and insights.
There are a number of impactful, internal places that companies can look to mine data. These include:
TRANSACTIONAL
DATA AND POS
INFORMATION
CUSTOMER
RELATIONSHIP
MANAGEMENET
SYSTEM
INTERNAL
DOCUMENTS
ARCHIVES
OTHER BUSINESS
APPLICATIONS
DEVICE SENSORS
Find out how Amazon gathers its own
internal data and how it uses it in Exercise
1 of Learners workbook #2

Overall, internal sources of big data can offer
numerous advantages for today’s
businesses. Not only are these sources
incredibly telling and relevant, but they’re
free of cost to the company, as this is
information that the organization already
owns. In this way, enterprises can launch an
array of big data initiatives without ever
looking beyond their own walls.

DATA ENRICHMENT
1. Why Data Enrichment is a must
2. How does it work?
3. The Steps of Integration
4. The Principles of Data Enrichment

The data integration process is traditionally thought of in three steps:
1. Extract
2. Transform
3. Load
DATA ENRICHMENT
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.
WHY DATA ENRICHMENTS IS A NECESSARY 4th STEP
25%
74%
88%
36%
0
10
20
30
40
50
60
70
80
90
100
of the average
B2B marketer's
database contains
critical data errors
of companies do
not have a
sophisticated
approach to data
quality
of records
analyzed lack
firmographic data
of marketers say
that data quality is
the biggest
obstacle to
marketing
automation
success

HOW DOES IT WORK?
Data integrators traditionally bring data from source
to target unchanged. It's as if ETL developers were
movers who prided themselves on putting your
furniture in the new place unbroken. Businesses
today are asking the movers to repair and improve
the furniture before landing it in the new house.
The types of information that can be added, or
"augmented„ to a demographics database:
GEOGRAPHIC
BEHAVIORAL
DEMOGRAPHIC
PSYCHOGRAPHIC
CENSUS
Complete Exercise 2 of Learners workbook
#2, to test your knowledge on best
practices of collecting Big Data

First Last Income
John Smith 32,000 $
Henry White 88,000 $
Andy Brown 120,000 $
Steve Brook 54,000 $
Income L Income U Target
20000 39999 A
40000 59999 B
60000 79999 C
80000 99999 D
100000 119999 E
120000 139999 F
First Last Income Target
John Smith 32,000 $ A
Henry White 88,000 $ D
Andy Brown 120,000 $ F
Steve Brook 54,000 $ B
Example

Enrichment isn't limited
only to demographics. Data
quality tools allow
definition of rules that
integrate into the ETL
stream for any data source.
MATCHING CORRECTING INTERPOLATING
THE STEPS OF INTEGRATION
1 2 3

THE PRINCIPLES OF DATA ENRICHMENT
Operations that automatically match, correct, or interpolate data values operate with some "confidence" level, meaning that sometimes they are wrong. That means
that hundreds of thousands of matches may have been incorrect - not necessarily an issue for the particular application involved, but something for those implementing
enrichment to consider.
The business should drive and manage enrichment definition
Enriched data must be identifiable and audit-able in the target database
Data replaced by enrichment must be available alongside the enriched data
1
3
2

USING DATA TO
BUILD YOUR BRAND
1. How can Data help you build your
Business
2. The Benefits of using Internal Data in
Marketing

HOW CAN DATA HELP
YOU BUILD YOUR
BUSINESS

Identifying trends
2
Checking out the competition3
Improving operations4
Recruiting and managing talent5
Understanding what makes your customers tick1
Tweaking your business model6

THE BENEFITS OF
USING INTERNAL DATA
IN MARKETING

ORIGINALITY
CONSUMER
VALUE
OPERATIONAL
TRANSPARENCY
CONSUMER
TRUST
BRAND
RECOGNITION
COMPANY
WORTH
Integrate Big Data into your own company
in Exercise 3 of Learners workbook #2

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Smart Data Module 2 d drive_own data

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