Presentatie van Roland Haeve (Atos): 'Using the Cloud for Big Data Analytics' tijdens het Big Data Analytics seminar 14 juni van Almere DataCapital in Almere.

1. Using the Cloud for
Big Data Analytics
Roland Haeve, Thought Leader
14 juni 2012

2. Big Data in the Cloud
Email Blogs
Big Data
Instant
messaging
Twitter
Open
Surveys
Social
networking
Web

3. Atos Big Data Services
Big Data
OFFERINGS

4. Cloudservices
Canopy in partnership with EMC and VMware, to form an open cloud
computing strategic alliance.
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5. Big Data Architecture & Technology Roadmap
- Architecture components: Analytic platform
Big Data Analytics demand
BI tools &
Visualization ▶ Support for (No) SQL based queries, data mining, statistical
analysis, fact clustering, data visualization, natural
language processing, AI etc.
Analytic platform
▶ High performance analysis to rapidly uncover new and
Distribution changing patterns in data
System
▶ Real-time analytics & scalability
Integration ▶ Need to support in-database analytics, CEP, predictive
analysis etc
Storage ▶ Support for structured, unstructured, graphical, geo-spatial
data etc

6. Big Data Architecture & Technology Roadmap
- Architecture components: Analytic platform
BI tools & ▶ Based on open source Hadoop
BI tools & Visualization
Visualization ▶ Designed to improve manageability of
Cloudera
Hadoop deployment
▶ Supports scalability and flexibility across
Analytic platform
Analytic platform wide range of data types
▶ Shared nothing massively parallel
processing architecture
EMC
Distribution System
Distribution System ▶ High performance parallel dataflow
Greenplum engine
Integration
Integration ▶ IBM Infosphere Big Insights based on
Hadoop
IBM/Oracle ▶ Features text analytics, spreadsheet style
data discovery & exploration tool
Storage
Storage ▶ Oracle; Exalythics

7. Key factors for Analytic Platform roadmap

8. Some examples of Big Data Visualizations
Chromogram: Text Visualization
Word Tree Thermail
Connection Analysis
from LinkedIn
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9. Eisen Big Data Analytics
▶ Vaardigheden: Slechts 14 procent van de Nederlandse respondenten zegt
genoeg analytische vaardigheden in huis te hebben.
▶ Kennis: Zorgen over de moeilijkheden bij de implementatie van geavanceerde
analytics-mogelijkheden bovenop de bestaande technologie. Ook is het moeilijk
om werknemers in korte tijd bij te brengen wat de mogelijkheden van de
analytics-software zijn.
▶ Afdekking: Web 2.0 analytics, risk en Fraude analytics, Financiële analytics,
customer analytics en enterprise business analytics strategy.
▶ Investering: Grote investeringen staan op stapel: markt voor Big Data-tools zal
groeien van 9 miljard vorig jaar naar 86 miljard in 2020. Dan zullen uitgaven
aan Big Data-tools goed zijn voor ongeveer 11 procent van alle bedrijfsuitgaven
(in relatie tot IT uitgaven).
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10. Case: Big Data - Atos WorldGrid
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11. Case: Big Data – Travel Web Site
Business Issue
▶ Limited understanding of the dynamics of marketing
response and external influences on web traffic and sales
▶ “Static” customer information
Use Cases
▶ How can RSH derive the best possible value from its
marketing strategies, eg:
– Does a positive spike in social media sentiment
translate into an increase in web sales?
– Does a local radio advertising campaign translate into
redspottedhanky.com increased web traffic and sales?
sells discounted train – What impact does weather have on web traffic?
tickets on-line. Customers
gather loyalty points for Solution
each ticket purchased ▶ Cloud based Big Data platform integrating, storing and
which can be used to buy analysing unstructured and structured data
additional train tickets. ▶ Hadoop based solution integrating weather, twitter feeds,
ticketing sales, CRM and web traffic data into single
repository for trend identification and analysis

12. Meer informatie?
Voor de Open Source Solution Big Data Whitepaper, ga naar:
http://atos.net/en-us/about_us/insights-and-innovation/thought-leadership/bin/wp-open-source
» Naam: Roland Haeve
» Rol: Thought Leader
» Mail: Roland.Haeve@atos.net
» Tel: 06-22465013
» @RHaeve