ce document présente les orientations du marché en terme de business intelligence.

1. Department solution : B2B
BI : actuel context and
market offersDATE 22/08/2013

2. Sommaire
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BI framework
Traditionnel BI view
Review of BI customer needs
Customer needs vs Market offers
Market innovation areas
BI trends
Benchmarking

3. BI framework
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Business Intelligence is playing a key role in modern business and is
considered central to identifying new opportunities within an organization

4. Traditionnel BI
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focused on
collecting data
Simple on
presenting data
complex for
business users
Required Trained
users
Data analysis
• No appropriate tools for
business users
Limited resources
• wait several days to
receive data insights
into corporate
performance

5. Review of BI Customer needs
Date
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traditional customer
needs
Improved quality of information available
to the companies.
Access to relevant information in easy-
to-use reporting interfaces for ad hoc
reporting.
Assistance with interpreting and drawing
conclusions from the information.
Access to relevant information in
standard reports.
An overview of which data is available
for analysis.
A formal/Quick assessment of the
companies information needs.
Business needs
Power to the business user :Easy to use
and understand
Data is dynamic and evolving : enables
users to absorb data on the fly
Anytime, anywhere
Make it relevant –make it personal :
getting the right information and insight
to the specific user
The power of being social : collaborate
using social tools
cost effective BI

6. Customer needs vs market offers
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Improved quality
of information
available to the
companies.
Data is dynamic
and evolving
Data intégration
and Quality,
Data
Governance,
Master Data
Management
In-memory
storage
Big Data
storage,
Integration

7. Customer needs vs market offers
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Access to
relevant
information in
easy-to-use
reporting
interfaces for
ad-hoc
reporting.
Power to the
business user.
Make it relevant-
make it
personal.
Data visualisation
and dashbording
Advanced
visualisation
Self service BI
(create report)
Mass reporting
Collaborative BI/
BI portal
Customer-Facing Business
Intelligence

8. Customer needs vs market offers
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Access to
relevant
information in
standard
reports.
Anytime,
anywhere
Targeted
solutions
Embedded BI,
mobile
Real time BI
Active Report

9. Customer needs vs market offers
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Assistance with
interpreting and
drawing
conclusions
from the
information.
the power of
being social
Analyst tools :
statistic, predective
Big data analysis
Performance
Management
Data discovery, BI
search
Sentiment analysis

10. Customer needs vs market offers
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A formal/Quick
assessment of
the companies
information
needs.
cost effective BI
Agile BI
Cloud
BI as service
Open source BI

11. Market innovation areas
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Big Data Integration, Management and
analysis
Data Quality, Governance, and Master
Data Management
Customer-Facing Business Intelligence
and mobile BI
Performance Management
Advanced Analytics
•Price Simulation
•Predictive Analytic
Business Process Automation

12. Market innovation areas
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Data Quality, Governance, and Master
Data Management
In-memory
capabilities
Benefits :
• Less persistence
• reduces time to creation of component
• improves flexibility and,
• Reducing the need for physical data marts means
less data movement reformatting and extracting, and
much less data redundancy
• eliminates the need for specific technical tuning of the
data mart
• gain more agility in design and development activities
Disadvantages :
• The CPU may have to wait for the data to be loaded
from memory to cache. If that becomes a bottleneck
due to high data volumes, it may be best to load only
the data needed for the analytic process

13. Market innovation areas
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Data Quality, Governance, and Master
Data Management
Virtualization
Benefits
• like in-memory
technologies (Less design
effort, less data
movement, easier
maintenance, less data
redundancy, lower costs,
and better agility in
designs and development)
• no synchronization issues,
• the ability to combine
different data sets together
(e.g., operational data with
analytic results)
MasterData
Management
To effectively sell to
existing and potential
customers,
companies must
obtain a fully unified
view of all their
activities
(MDM) tools, ensures
that information about
clients and prospects
is correct, complete,
and consistent across
all enterprise systems
and sources

14. Market innovation areas
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Big Data Integration, Management and
analysis
Bigdata Needs :
• companies seeking to optimize revenue need to effectively tap into the wealth of
information that exists in their internal systems, as well as the data that is available
via social media channels and third-parties.
• Selon IBM : 3V:volume, variety, and velocity
• Définition : Big data technologies describe a new generation of technologies and
architectures, designed to economically extract value from very large volumes of a
wide variety of data, by enabling high- velocity capture, discovery, and/or analysis
• Related to NoSQL :Groups non relational approaches under a single term
Benefits
• include “sandboxes” or experimental areas in addition to the enterprise data
warehouse
• ability to analyze ALL the data not just subsets , historical and real-time,
structured and unstructured
• NoSQL, Hadoop, columnar databases, in-database analytics, and in-memory
caching all improve performance and storage requirements
deadvantages
• it may prove to be prudent to separate the traditional data warehouse ETL/Data
Quality processing from the big data ETL one. It generally means you must use
micro-batches to achieve required near real-time capabilities
• Need for new connectors to big data sources

15. Market innovation areas
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Customer-Facing Business IntelligenceLowlatencyor
real-timeanalytics
requirements
Need :
• Operational intelligence requires fresher, more
current data .
• Business users must be able to analyze data
as soon as it is made available or within a few
minutes of its creation
Benefits :
• high availability, disaster recovery,
• the ability to embed BI in operational
workflows,
• faster response times

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Market innovation areas Customer-Facing Business Intelligence
Data
visualisation
• Web 2.0 gives BI a
face-lift
• BI goes mobile
• Microsoft office BI
integration
becomes standard

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Market innovation areas Advanced Analytics
Advanced Analytics
• Such as predictive analysis, statistical analysis, …
• It easier for organizations to uncover where risk may exist, and under what conditions it
could do the most damage
Use case
• Banks and credit cards companies, for instance, analyze withdrawal and spending
patterns to prevent fraud or identity theft.
• Ecommerce companies examine Web site traffic or navigation patterns to determine
which customers are more or less likely to buy a product or service based upon prior
purchases or viewing trends.
Data analytics vs datamining
• Data analytics is distinguished from data mining by the scope, purpose and focus of the
analysis. Data miners sort through huge data sets using sophisticated software to
identify undiscovered patterns and establish hidden relationships

18. Agile BI : accelerating the time to deliver value
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Agile BI
In-
memory
Real-
time
Search
Self-
service
Open
source
SAAS

19. New or emerging trends
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BI goes green
Analytic applications
make a comeback :
specific to business
areas
Composite
applications and
embedded BI
empower operational
workers(BI gadgets)
Advanced
visualization
becomes part of
core BI
event-driven analytic
platforms
System and usage
monitoring mature
Mission-critical
infrastructure :
clustering, failover,
turbocharge,
microbatches, …

20. Tools Benchmarking
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Data intégration
ETL tool
databases sources
fichiers plats
Bigdata sources
social network data
salesforce data
master data management
audit erreurs et gestion des
rejets
Data visualisation
et dashbording
TdB standars
Tdb personnalisés
Tdb interactifs
Self-service BI
Advanced visualization
intégration des valeurs
objectifs/cibles
collaboratif/portail décisionnel
reporting de masse
mobile device support
temps réel
Bigdata
Active Report. (offline)
Data discovery
comptabilité analytique
Statistical Analysis
predictive analytics
analyse multidimensionnelle
microsoft office integration
Requette ad hoc
text mining
BI search
Sentiment analysis (social
media)
Performance
management
performance management
tools(balanced scorecard)
performance planning
business activity monitoring
business process management

21. Tools Benchmarking(suite)
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Data storage
SGBDR
OLAP
spécifique : CRM, SCM,…
datawarehouse/datamarts
Bigdata/document
warehouses
in-memory storage
Administration
gestion des métadonnées
gestion de la sécurité
gestion de reprise après
incident
System and usage monitoring
mature
Alerts
management
dans les tableaux de bord
au sein du portail décisionnel
envoi des alertes par mail
envoi des alertes par sms
déploiement
Cloud
SAAS
opensource
propriétaire
packaged analytic
applications
Composite applications and
embedded BI: gadget
for Operational/ ERP Systems