sones GraphDB is a graph-based database for cloud computing that models associations between complex data types, similar to how the human brain works. It allows for flexible data modeling and can efficiently store, manage, and query connected data. Unlike traditional relational databases with structured tables, sones GraphDB uses an object network approach to maintain the original data structure and enable linking of various data types, like text, images, videos, and more.
Hadoop, Big Data, and the Future of the Enterprise Data Warehousetervela
Under the umbrella of big data, the nature of data warehousing inside enterprises is undergoing a massive transformation. Originally designed as a clearinghouse for organizing data to discover and analyze historical trends, business units are now putting extreme pressure on their data groups to enhance their services. Their goals: provide better customer service, real-time marketing, and more efficient business operations.
In this webcast, Big Data expert Barry Thompson will discuss how will enterprise data warehouses are evolving to meet these challenges. Some of the topics we will cover include:
- How Hadoop and other big data technologies are coexisting with traditional data warehouses
- Dealing with multiple big data sources – and multiple versions of the truth
- Techniques like warehouse replication and parallel data loading that enable platforms with different levels of service for different types of applications
Hadoop World 2011: Changing Company Culture with Hadoop - Amy O'Connor, NokiaCloudera, Inc.
We are living in a time of tremendous convergence, convergence of mobile, cloud and social…This convergence is forcing companies to change. At Nokia, we are changing the way we make decisions, from a manufacturing model to a data driven one. Yet making cultural changes is one of the hardest things to accomplish. In this talk, Amy O’Connor will highlight the journey Nokia is taking to evolve its culture - from building a platform for cultural evolution on top of Hadoop, to the administration of Nokia’s data, to how the company conducts the analysis that is enabling Nokia to compete with data.
Want to get involved in our big data/big content efforts? Direct Tweet me at jmancini77 -- I also did a blog post on this topic -- http://www.digitallandfill.org/2012/03/big-data-and-big-content-just-hype-or-a-real-opportunity.html
Hadoop, Big Data, and the Future of the Enterprise Data Warehousetervela
Under the umbrella of big data, the nature of data warehousing inside enterprises is undergoing a massive transformation. Originally designed as a clearinghouse for organizing data to discover and analyze historical trends, business units are now putting extreme pressure on their data groups to enhance their services. Their goals: provide better customer service, real-time marketing, and more efficient business operations.
In this webcast, Big Data expert Barry Thompson will discuss how will enterprise data warehouses are evolving to meet these challenges. Some of the topics we will cover include:
- How Hadoop and other big data technologies are coexisting with traditional data warehouses
- Dealing with multiple big data sources – and multiple versions of the truth
- Techniques like warehouse replication and parallel data loading that enable platforms with different levels of service for different types of applications
Hadoop World 2011: Changing Company Culture with Hadoop - Amy O'Connor, NokiaCloudera, Inc.
We are living in a time of tremendous convergence, convergence of mobile, cloud and social…This convergence is forcing companies to change. At Nokia, we are changing the way we make decisions, from a manufacturing model to a data driven one. Yet making cultural changes is one of the hardest things to accomplish. In this talk, Amy O’Connor will highlight the journey Nokia is taking to evolve its culture - from building a platform for cultural evolution on top of Hadoop, to the administration of Nokia’s data, to how the company conducts the analysis that is enabling Nokia to compete with data.
Want to get involved in our big data/big content efforts? Direct Tweet me at jmancini77 -- I also did a blog post on this topic -- http://www.digitallandfill.org/2012/03/big-data-and-big-content-just-hype-or-a-real-opportunity.html
Semantic Web & Web 3.0 – Eine Einführungbasis06 AG
Einführung in das Thema ohne Buzzwords und Technospeak aber mit nachvollziehbaren Beispielen und konkreten Tipps anlässlich der Eventreihe Reise ins Web
A Short Introduction to Semantic Web-based E-Commerce: The GoodRelations Voca...Martin Hepp
In this slidecast, I will give a brief overview of how the next generation of Web technology, known as the "Web of Data" or the Semantic Web will improve our e-commerce shopping experience. In particular, I will explain how the Web of Data - will allow for more precise search for suppliers for our particular needs and - how manufacturers can support retailers in presenting their products including all distinct features.
For more information, see http://purl.org/goodrelations
Wondering how advertisers can target specific ads to audiences of 1? Then you need to understand terms like SSP, DSP, DMP, and RTB - all of which are made possible by cookie synching.
Cutting Big Data Down to Size with AMD and DellAMD
Matt Kimball, AMD Server Solutions Marketing presentation on "Cutting Big Data Down to Size with AMD and Dell" from Dell World.
Learn how “Hadoop” solutions are helping companies overcome growing pressures on IT budgets with an innovative approach to Big Data.
Collaboration & Social Media New Challenges For Records ManagementMaurene Caplan Grey
Presentation was delivered as the keynote of the 27 Feb 2009, ARMA Northern VA chapter conference (http://www.armamar.org/nova/programs/ARMA%20NOVA%202009%20Seminar%20Brochure-c.pdf).
Semantic Web & Web 3.0 – Eine Einführungbasis06 AG
Einführung in das Thema ohne Buzzwords und Technospeak aber mit nachvollziehbaren Beispielen und konkreten Tipps anlässlich der Eventreihe Reise ins Web
A Short Introduction to Semantic Web-based E-Commerce: The GoodRelations Voca...Martin Hepp
In this slidecast, I will give a brief overview of how the next generation of Web technology, known as the "Web of Data" or the Semantic Web will improve our e-commerce shopping experience. In particular, I will explain how the Web of Data - will allow for more precise search for suppliers for our particular needs and - how manufacturers can support retailers in presenting their products including all distinct features.
For more information, see http://purl.org/goodrelations
Wondering how advertisers can target specific ads to audiences of 1? Then you need to understand terms like SSP, DSP, DMP, and RTB - all of which are made possible by cookie synching.
Cutting Big Data Down to Size with AMD and DellAMD
Matt Kimball, AMD Server Solutions Marketing presentation on "Cutting Big Data Down to Size with AMD and Dell" from Dell World.
Learn how “Hadoop” solutions are helping companies overcome growing pressures on IT budgets with an innovative approach to Big Data.
Collaboration & Social Media New Challenges For Records ManagementMaurene Caplan Grey
Presentation was delivered as the keynote of the 27 Feb 2009, ARMA Northern VA chapter conference (http://www.armamar.org/nova/programs/ARMA%20NOVA%202009%20Seminar%20Brochure-c.pdf).
SAP HANA and Apache Hadoop for Big Data Management (SF Scalable Systems Meetup)Will Gardella
In this presentation I argue that the future of data management may see a split between (1) real-time in-memory systems such as SAP HANA for most enterprise workloads (2) disk-based free and open-source Apache Hadoop for certain specialized big data uses.
The presentation starts with a definition of what is intended by the term big data, then talks about SAP HANA and Apache Hadoop from the perspective of suitability for enterprise use with a special concentration on Hadoop. (The basics of SAP HANA were covered in the immediately preceding session). This is followed by a description of currently available SAP support for Apache Hadoop in SAP BI 4.0 and SAP Data Services / EIM. Due to time constraints I did not discuss Apache Hadoop support built into Sybase IQ.
SnapLogic provides a Data Integration platform that takes integration to another level, by combining the power of dynamic programming languages with standard Web interfaces to solve today's most pressing problems in application integration. SnapLogic has an intuitive visual designer that runs in your browser and connects to highly scalable web based Integration server that you can run on premise or in the cloud.
BDT101 Big Data with Amazon Elastic MapReduce - AWS re: Invent 2012Amazon Web Services
Big data technologies let you work with any velocity, volume, or variety of data in a highly productive environment. This session seeks to answer questions such as "what is big data," "how can I use unstructured data," and "how can I integrate data collections from different sources" using Hadoop with Amazon Elastic MapReduce. Join general manager of EMR, Peter Sirota, on a journey through real-world use cases of data-driven discovery.
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
2. About sones
sones GraphDB
is the first database for
cloud computing that
makes associations
between complex data just
like the human brain.
(*)e.g.:
Seman-c
Web
data,
workflows,
pictures,
personal
documents,
loca-on,
sensor
data,
eCommerce
items,
Facebook,
TwiAer,
blogs,
mobile
apps,
configura-on
data,
your
email
inbox,
CRM
data
3. Company history
Series A financing
GraphDB as an round with TGFS
GraphDB 1.0 open source
version Talend data
T-Venture Initial proof of à OSE 1.1 – integration
sones GmbH
founded invests concept 5,000 downloads
Customer saves during the first Enterprise Edition
First on 100 servers month license for telcos,
The basic
concept of the customer: T- with version 1.0 web, data analysis
DB structure is Online GraphDB Cloud
developed (prototypes) Start of OEM and Edition on Azure New CEO and
partner sales expanded
strategy management
Financing with
seed capital
3 employees
4. Information - the capital of today and tomorrow
§ How people access information today:
• using the Web (no boundaries, unstructured) or
• using databases (structured, boundaries)
§ How people will access information in the
future:
Sones GraphDB
• using the Semantic Web, ontologies
(no boundaries, structured, automated)
5. The current market
90% of data traffic
today is
unstructured
(worldwide)
In 2011, this digital
universe will be 10
Videos, photos, times bigger than it
articles, user profiles, was in 2006 (IDC
news, groups, prediction)
events...
§ Cloud
compu-ng
data
management’s
unsolved
issues
(Cloud
Compu-ng,
Hype
Cycle,
Gartner):
§ Data
security,
data
portability,
user
controls,
reliability,
concurrency
and
dynamic
connec4ons
between
data
records
(#)
(data
has
to
be
shi:ed
from
one
data
center
to
another
to
process
the
informa4on)
6. Database Evolution
Graph-based concepts - latest innovation
Olap - and other
concepts for
real time analytics
Graph based
Content /
Application /
Analytics / Search
Object. Joe
Person Lives in Palo Alto IBM
IBM.com
Web Site
City Company
Relational Database
Database
Publisher of
Subscriber to Fan of Lives in
Employee of Sue
Niche-products,
Jane Person
Dave.com
ERP, CRM, …
RSS Feed Coldplay
Band
Fan of
Design
Person
Friend of
Dominating the Developers
Source of
Dave.com
Team
Group Member
of
Married to
Bob
Depiction of
123.JPG
Photo
Weblog Person
market Author of
Dave
Member of
Person
Stanford
AlumnaeMember of
Depiction of
Group
Member of
Hierarch. Database
Nearly “died out”
Key value based
concepts for
search and Web
60s 70s 80s 90s Since 2000 Today
Search, Cloud Computing
7. The database world
The innovation:
IBM.com
Joe Website
Person Lives in Palo Alto IBM
City Company
Publisher of
Fan of
Subscriber to Lives in
Employee of
Sue
Jane Person
Dave.com Fan of
Coldplay Person
RSS feed Friend of
Band Member
of
Design Depiction of
Married to
Source of Team
Member
Group 123.JPG
of
Dave.com Bob Photo
Web log Person
Depiction of
Member of
Stanford Member of
Dave
Author of Alumnae
Person
Group
Member of
8. What is sones GraphDB?
sones GraphDB:
§ A new type of object-oriented, graph-based database management
system
§ Enables efficient storage, management and evaluation of complex,
highly connected data records
§ Combines the advantages of file storage with the possibilities of a
database management system
§ Unstructured data and information (e.g., video files), semi-structured
data (metadata, e.g., log files) and structured data (similar to SQL) can
be linked to each other, which makes it possible for users to manage
this data themselves and evaluate when necessary
9. What makes us different?
Persistence: Flexible data
Storage on a modeling
non-volatile while the
storage system is
medium running
10. We do it differently
§ Information and data are saved in object networks instead of
tables.
§ The original data structure is maintained.
§ New paradigm:
§ Linking logic and data. Improved efficiency-real-time.
§ New functions for large numbers of queries on highly complex,
distributed, dynamic data.
•Fewer processing steps required.
•Cost advantages, competitive advantages
11. Universal data access
Personalized recommendations Social CRM
New database applications
Scaling at the push of a button Targeting
GraphDB SOAP
Web Universal data access REST
DAV
Automatically generates metadata from Consolidation and links to other Links to your
images, videos, music and documents information corporate data
Metadata Image data Public profile data
… Type Compression Can be linked with
Dimensions Camera corporate data on
Width Photographer Facebook
Relational Height Price Increased
data silos Resolution
Bit depth
… information density
Universal access Your data remains Develop your own
no matter where your data consistent even when solutions using a
is stored modeled while the flexible
system running data structure
12. Easy to manage
Easy-to-learn GQL query
language
MySQL query
SELECT w.word AS wort, k.sig AS sig FROM co_s k,
words w WHERE k.w1_id=(SELECT w_id
FROM words w WHERE word = “Laptop”) AND
k.w2_id=w.w_id ORDER BY k.sig DESC LIMIT
10;
Index-based storage, simplifies GQL query
storage and search processes
FROM Word SELECT Cooccurrences.TOP(10)
WHERE Content = ‘Laptop’;
Index
Can be scaled as
No. Subject you like – our
… … BeAer
solution easily grows
… …
… …
Performance
with your demands
… … =
… … Cost
savings
Rela-onal
Database
SEARCH Increasing
amount
of
connected
data
13. Real-time analytics
Recognizing and evaluating
multidimensional relationships
Universal analytics
Analysis and
prioritization
Relevant
information
14. Low TCO
Highly scalable
Complex queries as in-depth as
desired on the GraphDB call for less
processing power due to their graph
structure
Optimized processing power, up to
No double data
300% greater performance when
storage for data
handling
processing and
semi-structured data
evaluation
JPEG …
$ €
15. Solution approaches
Cross-system
duplicate recognition
Point of sale
Real-time recommendations
Analyses of customer
behavior
e.g.: churn detection
15
18. Web
§ Image portal - Increases sales of images since the
right image can be found much more quickly or is
automatically recommended
§ AB testing - Fast and easy evaluation of marketing
campaigns Real-time analysis also possible during
implementation
§ Click-path analysis - e.g., via which paths do
customers access the portal
18
19. Web / content
§ Link building – Automatically links relevant pages/
content, checks completeness of references, makes
automatic recommendations of links to appropriate
pages (according to topic or other criteria).
§ SEO – Optimized search results (e.g., with Google).
The system does not directly link pages but generates
“link chains” that provide the desired depth (e.g., 4
plus x).
§ Content management - Providing the right content to
the right user in the right context at the right time
19
20. Universal data access
§ Enterprise Search/Enterprise Storage - Access to all
data present internally regardless of their data silo.
With the option of saving changes in that same
location. Supplements internal data with external
information from the Web (e.g. blogs/web portals/
social networks).
§ Central metadata repository - Universal data
access layer, centrally manage corporate data. Link
data from diverse editorial sources (images, articles,
etc.)
20
21. Social graph
§ Analysis of user behavior - How do visitors/customers
behave on the corporate website?
§ Customer/user group evaluation
§ SRM (social CRM) – Supplementing existing customer
data with customer data from sources such as social
networks, e.g., Facebook. Intention: to develop a
holistic picture of the customer. When customer X
calls, sales agents/customer agents can access both
the internal customer status as well as information on
the customer that they have posted on blogs, social
networks, etc.
21
22. Social net
§ Campaign management - Addressing campaigns to
the right customers at the right time.
§ Automatic categorization (e.g., job profiles for job
portals) - Semantic categorization in order to increase
the quality of job ads, etc., on the portal.
§ Social networks - Real-time friend-of-a-friend
calculation. Who do I know through WHOM?
Customizable path query with desired depth possible
ad-hoc.
22
23. eCommerce
§ eCommerce - Recommendations regarding the
right products made to the right customers at the
right time (customer-specific advertising), regional
targeting. Goal: To increase the number of items
sold.
§ eCommerce - Optimizing costs by reducing the
number of items returned – Automatic recognition
of “safe” returns, conducting pre-defined
processes, e.g., recommending suitable products,
increasing costs for shipping, etc.
23
24. Social commerce
§ Adding social commerce, i.e., recommendations
from/to friends in the friendship graph (i.e., also multi-
hop!) or
§ product graphs (shared shopping possible)
§ for members of a group or similar shopping behaviors
§ e.g., same brand regarding individual products
§ e.g., same interests/groups/rated products
24
25. Visualization
§ Affiliation management – Who is affiliated with which
companies? Direct storage of related information such
as minutes of meetings, company agreements, etc.
§ Visualization – Simple, interactive depiction of
relationship networks/connections/relationships.
Intuitive use (e.g.,. via Silverlight)
§ Geomapping - Linking the data mentioned above with
geoinformation Where are customers/subscribers
located? (and why?)
25
26. Miscellaneous
§ Recalls, e.g., for cars: Ad-hoc report of all the people
who purchased a car in which the defective part is
installed.
§ Parts tracking – Who installed which part when?
Which supplier can deliver a specific product at a
certain time for the lowest price?
§ Semantic Web – social tagging, processing user
generated content, crowd sourcing, social media
monitoring
26
27. CMDB
§ Configuration management database
• Definition according to Wikipedia In the IT Infrastructure Library (ITIL)
context, a CMDB is a database that is used to access and manage
configuration items. All IT resources are classified as configuration items
(CI) in the context of IT management. […] In this context, this refers to the
existing pool and the interdependencies of the objects being managed.
• Specification: federation (metadata management) / reconciliation (target/
current state comparisons) / mapping visualization / synchronization
sones graphDB can be described as the only real
CMDB
27
28. Disclaimer
General Disclaimer
This document is not to be construed as a promise by any participating company to develop, deliver,
or market a product. It is not a commitment to deliver any material, code, or functionality, and should
not be relied upon in making purchasing decisions. sones GmbH makes no representations or
warranties with respect to the contents of this document, and specifically disclaims any express or
implied warranties of merchantability or fitness for any particular purpose. The development, release,
and timing of features or functionality described for sones products remains at the sole discretion of
sones. Further, sones GmbH reserves the right to revise this document and to make changes to its
content, at any time, without obligation to notify any person or entity of such revisions or changes. All
sones marks referenced in this presentation are trademarks or registered trademarks of sones GmbH
and other countries. All third-party trademarks are the property of their respective owners.
28