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BIG DATA ANALYTICSTO THE NEXT LEVEL

A peek into Bisnode’s recent acquisition of Swan Insights and its integration within KI3.

FOR

INTERNAL

USE ONLY!

Swan’s and KI3 teams merge and will act as a group-wide R&D competence centre for Big Data Analytics.

LIFT UP BIG DATA ANALYTICSTO THE NEXT LEVEL

A few weeks ago, the Bisnode

Group finalized the acquisition

of Swan Insights. This operation

strengthens the group’s Big Data

Analytics capabilities, and will

ensure its leadership in the field,

thanks to Swan’s deep expertise

in machine learning, network

science, data engineering, and to

its R&D culture.

During the last three years, this

creative squad has been de-

veloping a Big Data framework

industrializing Business Informa-

tion and Consumer Marketing

tasks: massive data acquisition,

matching, enrichment, disam-

biguation, natural language

processing, predictive analysis

- and delivery interfaces.

Two months later, the two teams

have become one. Management

and staff are now working hand

in hand to digest the already

intense flood of opportunities

detected in many markets, and

to disseminate the Big Data &

Analytics capabilities throughout

the whole Bisnode group. Here’s

a quick peek on what’s in it for

all of us.

Based in the heart of Europe, Swan is a Big Data & Analytics team, filled with data scientists and business engineers evolving in an innovation-infused culture.

2 BISNODE - SWAN 2017

Cost OptimisationIdentify and realize cost optimization potentials in the context of data

enrichment / enhancement by applying machine and deep learning

capabilities.

Product DifferentiationDistil insights into our products and differentiate them with distinctive

Big Data Analytics features.

Business DevelopmentReinforce Bisnode’s position within selected large accounts with Big

Data Analytics capabilities.

R&DHelp reposition Bisnode as an innovative data & analytics company in

the market with big data capabilities and explore new business oppor-

tunities.

KI3 KEY OBJECTIVES 2017

Brussels is at the heart of Europe

Swan is located in Brussels. The

KI3’s Innovation lab was established

in Berlin. The process to merge the

two teams in the capital of Europe

in order to foster creative power and

innovation has started. The inspiring

office space there shelters a high-tal-

ented team of complementary sci-

entists and engineers. Not less than

4 PhD-level researchers, surrounded

by mathematicians, computational

linguists, statisticians, software de-

velopers and business engineers put

their boiling minds at work and push

the big data frontiers further.


That’s it - let’s combine the three (new data sources, advanced algorithms and

technology) to create a new-generation Big Data frame-

work. We call this approach « Context Mining ».

Contextual Intelligence is indeed at the core of KI3’s

ambition. Context is what turns an information into

an insight. By combining sources and applying the

right analysis, a context emerges and the information

suddenly becomes relevant, timely - and actionable. As

such, Context Mining is not only about capturing the

data, but also about making the machine understand it,

filter it, disambiguate it, combine it with other datasets

- and turning it into insights that truly matter for the

business end user.

CONTEXT MINING

First, the exponential growth of machine- and human-generated,

unstructured data is a huge yet untapped potential for organizations.

The business world still has difficulties to grasp the value out of those

data floods - social data, news feeds, web search engines - open data

in general. Capturing this value is however becoming critical in an

increasingly complex, competitive and global trade world.

Second, the recent advances in fundamental research on data science

and applied mathematics provide the tools and methods to turn those

data into valuable insights, and to explore, disrupt and transform exist-

ing business models.

Third, recent technologies open a wide opportunity window to scale

operations and leverage our European footprint.

12

3

What are they up to? The starting point of KI3’s roadmap was born from a three-fold observation.


DATA SOURCES (*)

Data acquisition is at the epicentre of Bisnode’s identity – therefore also at Swan@KI3, focusing on four specific categories:

Worldwide NewsBusiness activity lies in the news, and

we monitor millions of articles a day

from hundreds of thousands of news

feeds. The challenge here is to make

the machine understand the meaning

of everything, detect and match enti-

ties and business events, in real time,

and in any European language.

Social Data We capture social profiles, bios,

posts and connections from

mainstream social networks like

Twitter, but also from profession-

al ones (Linkedin, Xing, Viadeo)

and vertical ones (i.e. Github and

Stackoverflow for IT develop-

ment professionals). This cate-

gory not only provide information

on companies and individuals,

but is also the raw material of ad-

vanced network science projects

which use the graph of connec-

tions for clustering, characteriza-

tion and behavioural prediction.

Open Data This is huge. Since we know where to

look, we can find anything. Business

registers, statistics, job listings, ten-

ders, patents, risk- and marketing-re-

lated data - the potential is infinite.

(*) Data acquisition, storage, processing and use are operated following the latest data protection require-ments.


Technology Now imagine what we can achieve together when those data sources

are combined with Bisnode and D&B data. Thibault Dory is Head of

Tech at Swan. Together with Goran Loncar, Data Analytics and Tech-

nology Lead, they confirm that the technology framework is being built

upon core principles like open architecture and hyper-scalability, and

would easily fit in the group’s set-up. This team runs a Big Data & Ana-

lytics’ R&D environment with which innovative solutions are prototyped,

productized by our team, supported by our offshore partner and indus-

trialized in all Bisnode markets through the group’s standard production

environment and the forthcoming Bisnode common platform.

Data Science Swan’s Data team is working in a collaborative open space. Next to

Thibault sits Pierre Deville, PhD, co-founder of Swan, former Chief Sci-

entist and now Head of Data Analytics leading the data scientists and

the R&D activities. He summarizes Swan’s capabilities in those terms:

« We can organize our skills range in three main areas: machine learn-

ing, network science and data engineering. With this expertise, we are

able to cover most of Business Information and Consumer Marketing

needs. » Let’s detail.

GORAN LONCAR

DATA ANALYTICS &

TECHNOLOGY LEAD

THIBAULT DORY

HEAD OF TECHNOLOGY

PIERRE DEVILLE, PHD

HEAD OF DATA ANALYTICS


Machine learning and natural language processingThe computer is now more intelligent than ever, and

we try to take the most out of it to automate tasks and

let the machine do the job. When it comes to Business

Information and Consumer Marketing, we developed a

deep machine learning expertise in a couple of areas.

Network scienceNodes and links in complex networks like social media

are an amazing source of insights - think about the

graph of connected individuals on Linkedin and the

knowledge we can draw from its analysis. Swan has

the network science expertise at its core, especially

when it comes to data exploration, link inference and

clustering.

Data engineeringMachine learning and Network science will not be

possible without the raw material: the data itself. Swan

has developed an integrated framework embed-

ding the four pillars of Data engineering: Acquisition,

Cleaning, Storage and Processing - following the fun-

damental objectives of Real time and Scalability.

Text Mining: entity detection (we identify

organizations, people, locations, dates,

etc), sentiment analysis, business event

detection (used in monitoring and risk

management) and pattern matching (we

detect any structured format like phone

numbers, contact data, number of em-

ployees, etc).

Similarity Matching: we disambiguate

topics like websites or social profiles

against a verified list.

Predictive Modelling: we try to see the

future with churn prediction, lead genera-

tion, behavioural outlook, etc.


DATA PRODUCTSCollect the right data, apply the right science on it, and make it fit a busi-ness need, and you’ll get a marketable Data Product at Bisnode. Swan is building a growing list of packaged features resulting from the com-bination of data, capability and scalability. Xavier Rouby, PhD, was also a co-founder of Swan and former CTO, now in charge of Productisation in KI3. He says: « During the last three years, Swan has assembled data and science to create super-efficient modules that can be combined to follow a specific business goal. With Bisnode, this capacity will scale at a high pace thanks to the group’s business reach. ».

The existing Data product portfolio is organised around 3

main Business Information functions. We have modules

that Enrich the data, as a fixed asset. We have others

that detects triggers and Signals in a real-time feed. And

we have a few ones that Explore new areas, create new

information, find hidden insights. Have a look - prod-

uct names speak for themselves.

Those modules can be combined together and organized

in Platforms addressing specific business areas. Swan’s

Big Data Analytics setup allows both productisation and

scaling through the master platform Swan.business. It

provides views on business activity and events. Different

add-ons have already been built on it, like Swan.jobs de-

scribing organizations through the talent, human glass,

and Swan.estate taking the environment and location

perspective. Which will be the next one? Well, we’ll devel-

op it with Bisnode, right?

KI3@Swan current offering is illustrated on page 9.

SIGNALDATA PRODUCTS

Business Events

Workforce Monitoring

Sentiment Analyzer

ENRICHDATA PRODUCTS

Website Finder

Contact Finder

People Matcher

Company Matcher

EXPLOREDATA PRODUCTS

Skills Graph

Company Talent View

Community Detector

XAVIER ROUBY, PHD

HEAD OF PRODUCTISATION


OK. So, now let’s put all this at work for concrete outcomes. A long list of use cases can demonstrate the real value and benefits, both for Bisnode projects and for direct customers. Jean-Philippe Schepens, co-founder of Swan and former CCO, now working with Bernard Knapik in Sales En-gagement, has a clear statement on this: « Our ambition is to bring mea-surable results to our customers, and to support their path to a better business. We were a customer-driven company, every choice we made went in that direction. We would like to keep it like this and never derail. »Let’s take a few examples of use cases that Swan@KI3 has rolled out since the integration.

• Real-time monitoring and quarter-

ly reporting of event-triggered risk

indicators.

• Identification and collection of

business contact information of

retail chains to increase market

coverage.

• In several markets, support

customers in AML compliance by

providing a risk platform covering

transactions in digital currencies.

Enrich telecom GPS data with

customer data in order to get

insights on who customers are, how

to segment them, where they are

and their movement patterns.

• Determine if a company is still

active or not from a dataset of com-

panies, using data from websites,

social networks, open data and

news.

• In several countries, identify the

phone number, fax, e-mail address,

social pointers, bitcoin address and

contact person of 2 million com-

panies, using data from websites,

social networks, search engines

and open data.

TARGET GROUP MASS MARKET

GO-TO-MARKET OWNER: GPM

TARGET GROUP KEY ACCOUNTS

GO-TO-MARKET OWNER: SWAN

EMBEDDED PRODUCT

FEATURE

USE CASES

BERNARD KNAPIK

COMMERCIAL LEAD

JEAN-PHILIPPE SCHEPENS

HEAD OF SALES & PROJECTS

TAILORED LIGHTHOUSE

SOLUTIONBIG DATA LABPACKAGE STANDARD

STANDALONE PRODUCT


KI3 ORGANISATION CHARTMARCUS HARTMANNGROUP DIRECTOR BIG DATA ANALYTICS

WHAT’S NEXT?Different new projects have just or are about to be started within

Bisnode, such as: Deliver real-time business events and signals about

companies for risk management and global account management.

Use Text mining to automate the plain text feedback from Voice of the

Customer users.

Enrich a national consumer population from social media clustering.

Automate the collection of vehicle data from websites, social media

and communities.

Enrich and segment customer databases from websites and social

media.

… and a lot more! The Swan team is available to present in-depth cases

and discuss any opportunity or need.

GORAN LONCARDATA ANALYTICS & TECHNOLOGY LEAD

LOUIS DE VIRON

DIMITRI PFEIFFER

GAUTHIER DOCQUIRE, PhD

RAPHAEL HUBAIN, PhD Cand.

CAROLINE VAN MOLPROGRAM MANAGEMENT OFFICE

PIERRE-LOUIS PEETERS

SOFYAN BOKORNA

LAURENT KINETBUSINESS DEVELOPMENT LEAD

XAVIER ROUBY, PhDHEAD OF PRODUCTISATION

PIERRE DEVILLE, PhDHEAD OF DATA & ANALYTICS

BERNARD KNAPIKCOMMERCIAL LEAD

JEAN-PHILIPPE SCHEPENSHEAD OF SALES & PROJECTS

RENAUD DE HEMPTINNE

THIBAULT DORYHEAD OF TECHNOLOGY

LAURENT KINET

BUSINESS DEVELOPMENT LEAD

[email protected]

MOB. +32 476 528 173


With Swan, KI3 is on the right path to support the group with the stra-

tegic transformation towards a leading Big Data & Analytics company.

KI3 will soon release an Extranet gathering use cases, inspirational

content and marketing & sales material that will help to communicate

this new potential. It will indeed not fly alone. The magic will come from

the smart collaboration between this team and the different markets,

KIs and Group functions. Together, we will be able to deliver new-gen-

eration products, solutions and support to our customers everywhere.

Swan@KI3 wants to support innovation, R&D, prototyping and produc-

tisation, always with the business in mind and, while looking ahead in a

forward-looking approach, never loose the grip with the ground - as one

says, it’s not about strategy, it’s about making it happen.

SO LET’S MAKE IT HAPPEN!

MARCUS HARTMANN

KI3 LEAD

[email protected]

MOB +49 170 218 2100


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