As pressure for digital transformation increases, companies must harness big data more effectively. But the well-known V’s of data—volume, variety, velocity—represent both opportunities and challenges. Data enrichment enables organizations to take full advantage of the benefits while addressing these typical problems. In this session, we look at what an enrichment workflow might look like and how it enhances data’s value across different use cases.

1. Unlocking Big Data
to Power Digital
Transformation
How data enrichment gets you to smart data.

2. 2
Today’s Agenda
1. Why is big data on the rise?
2. How is big data connected to the business mandate of
digital transformation?
3. What big data challenges need to be overcome to
achieve measurable value
4. Where does a smart data process fit into digital
transformation?

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Why is big data on the rise?
Data itself isn’t new.
The Ishango Bone
- Tally Stick from 18,0000 BC
Egyptian Hieroglyphics
- Early data visualizations

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Why is big data on the rise?
Data empowers insight
• Meets consumers’ data
needs
• Monetizes data for ad
relevance
• Data exhaust reveals
important information
Google’s ‘Aha’ moment offers a clue.

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What is data exhaust?
The breadcrumbs of internet searches speak volumes.
Every click counts
• Patterns of search terms
• Query phrasing
• Spelling & punctuation
• Location
• Dwell times
• Click patterns

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How does Google use data exhaust?
Improving search relevancy with location data is just one benefit.
Find Stroopwafels near me

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Growing value of data
Data is intrinsic to digital transformation. Digital transformation creates more data.
$1 Trillion invested in
digital transformation
in 2018
Poor data quality
costs businesses
Millions every year

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Data leaders unlock data’s value
Those who don’t will be left behind.
Google may have led the way,
but these days:
80%of the most innovative companies use
data to drive advantages in their business

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The Internet of Things (IoT) also multiplies the data available
Making use of IoT data has powerful potential.
Connected sneakers, wearables
and apps help Nike understand
runners’ behaviors.

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The Internet of Things (IoT) also multiplies the data available
Making use of IoT data has powerful potential.
Propeller Health’s use of user
sensor data led to a 50%
reduction in asthma attacks.

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The Internet of Things (IoT) also multiplies the data available
Making use of IoT data has powerful potential.
On-car sensors help teams
adjust race strategies in real
time to bring home the win.

12. 12LexisNexis Confidential
“Companies are either:
• Already data companies
• Will become data companies
• Or will cease to exist.”
~ Stephen Brobst, CTO of Teradata
Are we there yet?
Driving toward digital transformation is a must.

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0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Not Important
Somewhat Important
Important
Very Imortant
Critical
Examples of Digital Transformation
Where is digital transformation already well-established?

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Digital innovation and data are transforming industries
Consumers want personalized, go-everywhere experiences.

15. 15LexisNexis Confidential
Digital innovation and data are transforming industries
Digitization is a powerful ally of the empowered employee.

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Digital innovation and data are transforming industries
No industry is immune.

17. Of knowledge workers'
work-days are spent trying
to find and manage data
17
2.5 Quintillion Bytes
of data is created every day
5 Billion Inquiries
are processed by search engines daily
90% Of All Data
has been generated in the past 2 years
Source: http://bit.ly/3154f13
Of companies are
dissatisfied with their ability
to filter irrelevant data
60%
43%
Source: http://bit.ly/2LPV01t
The Challenges: Volume
The volume of data has increased exponentially.

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The Challenges: Variety
The variety of data types and sources has also exploded.
Can you use more
data types?
• News
• Audio & video
• Social

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The Challenges: Veracity
Validating the trustworthiness of data poses problems.
Can you trust the data?
• Media bias
• Typos
• Colloquialisms

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The Challenges: Velocity
Keeping up with the constant data barrage.
Can you take advantage
of real-time data?
• Clicks and calls
• 24/7/365 news

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The Challenges: Vulnerability
With great power comes great responsibility.
Can you protect your
data?
• Privacy concerns
of consumers
• Security expectations
of regulators

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5 key components for a data strategy
Identify. Store. Provision. Process. Govern
GovernProcessProvisionStoreIdentify

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Component 1: Identify
Identify data and understand its meaning regardless of structure, origin or location.
Search for the right data

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Component 2: Store
Ensure the data you gather is easy to access and process.
Determine how to store the
growing volume of data

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Component 3: Provision
Set rules and access guidelines for data.
Pack up the data so it can
be reused and shared

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Component 4: Process
Establish how different types of data will be processed for maximum value.
Gather data and
process it for a unified,
consistent view

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Component 5: Govern
Create policies for using and protecting data.
Use data responsibly

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Moving from big data to smart data
Get maximum Value from data to support digital transformation.
better results.
Smarter data
helps deliver

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Revealing the true value of big data
What makes data smart?
• Aggregation
• Normalization
• Enrichment

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INTERNAL
Datasets
CURATED
Datasets
PUBLICLY
AVAILABLE
Datasets
Integrated
with Data
Analysis Tools
Data aggregation: Layered data yields better insights
Build variety by going beyond the confines of internal datasets.

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Data normalization: Creating clean, semi-structured data
Make data more searchable and user-friendly.
Structured versus Unstructured

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Data enrichment: Enhancing the quality of data with tags
Metadata describes other data, making it easier to search.
Structured versus Unstructured

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Our Smart Data Process
Licensing of news & social
commentary, company &
industry information,
legal & patents data, people
data & public records
Aggregation, normalization & archival
of data using cloud technologies
Enrichments to enhance data value while reducing data volume
Cloud-based
applications and
Data as a Service
options to meet a
wide range of use
cases
2
1
3
4

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Entity
Extraction &
Resolution
Improves ability
to narrow a
search to a
specific entity.

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Classification
Enables search
refinements to
narrow results
to the most
relevant data

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Sentiment
Understand
and anticipate
trends, analyze
value of media
coverage and
more.

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Identifier
Metadata
Further refine
data searches
to reduce
volume while
increasing
relevance

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Smart data puts digital transformation on a fast track
“Businesses that successfully apply artificial intelligence (AI) could increase profitability by an
average of 38 percent by 2035.” — Accenture Research
Descriptive Analytics
What has happened?
• Using data aggregation
and data curation to
provide insight into the
past
• Analyzing historical data
to report on financials,
inventory, customers

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Smart data puts digital transformation on a fast track
“Businesses that successfully apply artificial intelligence (AI) could increase profitability by an
average of 38 percent by 2035.” — Accenture Research
Predictive Analytics
What could happen?
• Using statistical models
and forecasts techniques
to understand the future
• Analyzing purchases and
sentiment to predict the
next big consumer trend

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Smart data puts digital transformation on a fast track
“Businesses that successfully apply artificial intelligence (AI) could increase profitability by an
average of 38 percent by 2035.” — Accenture Research
Prescriptive Analytics
What should we do?
• Using optimization and
simulation algorithms to
advise on possible
outcomes
• Automated stock trades
based on quant models

41. Here’s to a Smart Data strategy
& one last ‘V’: Victory!
Thank You