In this talk from the Neo4j Government Graphday in DC, Philip Rathle discusses how government agencies are leveraging graph technology to power their applications.
Data Science Innovations is a guest lecture for the Advanced Data Analytics (an Introduction) course at the Advanced Analytics Institute at University of Technology Sydney
With the explosion of the maker movement, schools are beginning to embrace creativity. However, what does this mean for assessment? Should we assess the creative process? Should we assess the finished product? Does assessing creativity actually make kids more risk-averse? In this workshop we explore what it means to assess both the creative process and the creative product without leading to risk aversion.
In the world of big data, legacy modernization, siloed organizations, empowered customers, and mobile devices, making informed choices about your enterprise infrastructure has become more important than ever. The alternatives are abundant, and the successful Enterprise Architect must constantly discern which new technology is just a shiny object and which will add true business value.
A Related Matter: Optimizing your webapp by using django-debug-toolbar, selec...Christopher Adams
This talk explains how to perform SQL query analysis and how to rewrite your views to reduce the number of queries Django uses in evaluating your model objects and their attributes. Special emphasis will be given to the powerful methods "select_related" and "prefetch_related." I will highlight the problem with a naive use of the ORM, how to target code for optimization, and the beneficial result.
Like any abstraction layer, the Django ORM hides the messy details about its underlying implementation. This is both the benefit and the risk. If used naively, any tool can cause unexpected or problematic outcomes. Likewise, the ORM can cause your application to interact with the database in an ugly and inefficient way, creating special challenges regarding scaling a quickly-prototyped webapp.
Many design patterns and best practices have been developed as a result to nudge developers to use the ORM more efficiently. The good news is, one of the easiest and most powerful patterns has been wrapped into Django itself, in the dual pairs of methods in the Django ORM's Queryset API, "select_related" and "prefetch_related." These methods instruct the Queryset, when evaluated, to perform two kinds of useful optimizations for you that can reduce the number of queries by orders of magnitude resulting from iterating over model objects and many-to-many relations.
This talk summarizes the problem these methods of the Queryset API try to solve, how to effectively use them, and the beneficial result. Mastering how to use Queryset methods efficiently and powerfully is a major step in moving from a beginner to intermediate Django developer.
Delivered at DjangoCon 2014.
Data Science Innovations is a guest lecture for the Advanced Data Analytics (an Introduction) course at the Advanced Analytics Institute at University of Technology Sydney
With the explosion of the maker movement, schools are beginning to embrace creativity. However, what does this mean for assessment? Should we assess the creative process? Should we assess the finished product? Does assessing creativity actually make kids more risk-averse? In this workshop we explore what it means to assess both the creative process and the creative product without leading to risk aversion.
In the world of big data, legacy modernization, siloed organizations, empowered customers, and mobile devices, making informed choices about your enterprise infrastructure has become more important than ever. The alternatives are abundant, and the successful Enterprise Architect must constantly discern which new technology is just a shiny object and which will add true business value.
A Related Matter: Optimizing your webapp by using django-debug-toolbar, selec...Christopher Adams
This talk explains how to perform SQL query analysis and how to rewrite your views to reduce the number of queries Django uses in evaluating your model objects and their attributes. Special emphasis will be given to the powerful methods "select_related" and "prefetch_related." I will highlight the problem with a naive use of the ORM, how to target code for optimization, and the beneficial result.
Like any abstraction layer, the Django ORM hides the messy details about its underlying implementation. This is both the benefit and the risk. If used naively, any tool can cause unexpected or problematic outcomes. Likewise, the ORM can cause your application to interact with the database in an ugly and inefficient way, creating special challenges regarding scaling a quickly-prototyped webapp.
Many design patterns and best practices have been developed as a result to nudge developers to use the ORM more efficiently. The good news is, one of the easiest and most powerful patterns has been wrapped into Django itself, in the dual pairs of methods in the Django ORM's Queryset API, "select_related" and "prefetch_related." These methods instruct the Queryset, when evaluated, to perform two kinds of useful optimizations for you that can reduce the number of queries by orders of magnitude resulting from iterating over model objects and many-to-many relations.
This talk summarizes the problem these methods of the Queryset API try to solve, how to effectively use them, and the beneficial result. Mastering how to use Queryset methods efficiently and powerfully is a major step in moving from a beginner to intermediate Django developer.
Delivered at DjangoCon 2014.
While the Rio 2016 Olympics are winding down and the final medals are being handed out, we thought we would share a bit of work that was done recently by Rik Van Bruggen to explore a really interesting dataset in Neo4j.
Based on an original public dataset by the UK newspaper The Guardian, Rik completed the medallist dataset to contain over 30,000 Olympians between 1896 and 2012. He created a graph model, loaded the data, and wrote a bunch of example queries that yielded some very interesting results. Join us for this 30 minute webinar where we’ll take you through this great Olympian graph and take the data for a spin yourself afterwards.
Presentation on Large Scale Data ManagementChris Bunch
These are the slides for a presentation I recently gave at a seminar on Large Scale Data Management. The first half talks about the current state of affairs in the debate between MapReduce and parallel databases, while the second half focuses on two recent papers on virtual machine migration.
Are you trying to change your company IT Department's persistence paradigm from OOP => RDBMS to OOP => NoSQLDb? Want to benefit of DDD+CQRS+EVS in your enterprise-class distributed application but don't know where to start?
Look at this...
How to establish a sustainable solution for data lineageLeigh Hill
The implementation of data lineage is complex but necessary, driven by regulation such as BCBS 239 and internal needs to gain a better understanding of risk, reduce systems complexity and eliminate duplicate data and processes. The webinar will discuss the essential elements of data lineage, how they can be implemented, and the beneficial outcomes of a successful and sustainable data lineage programme.
Join the webinar to find out about:
Requirements for data lineage
Data and management issues
Metadata in data lineage
Supporting technology
Business benefits
How to Search, Explore and Visualize Neo4j with Linkurious - Jean Villedieu @...Neo4j
Graph visualizations are cool! Learn how everyone can use Linkurious to solve common problems like correcting errors, identifying patterns, or finding and communicating insights.
Km4City: how to make smart and resilient your city, beginner documentPaolo Nesi
Open Source and inter-operable tools to
• keep city under control via personalized dashboards
• monitoring services’ status of city operators
• monitoring and understanding the city users behaviour
• collecting moods, contributions and data from the city users
• monitoring social media for city services and events, event predictions
• improve city resilience, reducing risks and decision support by:
• assessing city resilience level
• improving city resilience, providing objective hints
• improving city users awareness with personal city assistants and participatory tools
• transform data in value for the city:
• enabling commercial and business applications
• aggregating multi-domain data and services for SMEs and city operators
• enabling integrated city services into third party web portal for all
• providing suggestion on demand services for SMEs and city operators
• accelerating and simplifying the implementation of business and service oriented Apps
Follow the Km4City City Smartener Process
Graphically understand and interactively explore your Data LineageMohammad Ahmed
Graphically understand and interactively explore your Data Lineage:
Data Lineage for ER/Studio gives data management professionals and business users essential insight to the extracts, transformations, and loads of complex enterprise data. Data governance and organizational compliance is supported with detailed metadata management for risk reduction and data discrepancy isolation.
In this presentation we look at the key reasons for using ER/Studio Data Lineage and what it provides you with.To learn more about ER/Studio Data Lineage please look here: http://www.embarcadero.com/products/er-studio-data-lineage or request a demo here: http://forms.embarcadero.com/forms/ERStudioProductInterest
Palestra de Design Patterns sob o ponto de vista arquitetônico, apresentando diferentes tipos de paradigmas e princípios, como o GoF, ISO, GRASP, SOLID, MVC e Aspect.
Decompose that WAR? A pattern language for microservices (@QCON @QCONSP)Chris Richardson
When architecting an enterprise Java application, you need to choose between the traditional monolithic architecture consisting of a single large WAR file, or the more fashionable microservices architecture consisting of many smaller services. But rather than blindly picking the familiar or the fashionable, it's important to remember what Fred Books said almost 30 years ago: there are no silver bullets in software. Every architectural decision has both benefits and drawbacks. Whether the benefits of one approach outweigh the drawbacks greatly depends upon the context of your particular project. Moreover, even if you adopt the microservices architecture, you must still make numerous other design decisions, each with their own trade-offs.
A software pattern is an ideal way of describing a solution to a problem in a given context along with its tradeoffs. In this presentation, we describe a pattern language for microservices. You will learn about patterns that will help you decide when and how to use microservices vs. a monolithic architecture. We will also describe patterns that solve various problems in a microservice architecture including inter-service communication, service registration and service discovery.
Samza at LinkedIn: Taking Stream Processing to the Next LevelMartin Kleppmann
Slides from my talk at Berlin Buzzwords, 27 May 2014. Unfortunately Slideshare has screwed up the fonts. See https://speakerdeck.com/ept/samza-at-linkedin-taking-stream-processing-to-the-next-level for a version of the deck with correct fonts.
Stream processing is an essential part of real-time data systems, such as news feeds, live search indexes, real-time analytics, metrics and monitoring. But writing stream processes is still hard, especially when you're dealing with so much data that you have to distribute it across multiple machines. How can you keep the system running smoothly, even when machines fail and bugs occur?
Apache Samza is a new framework for writing scalable stream processing jobs. Like Hadoop and MapReduce for batch processing, it takes care of the hard parts of running your message-processing code on a distributed infrastructure, so that you can concentrate on writing your application using simple APIs. It is in production use at LinkedIn.
This talk will introduce Samza, and show how to use it to solve a range of different problems. Samza has some unique features that make it especially interesting for large deployments, and in this talk we will dig into how they work under the hood. In particular:
• Samza is built to support many different jobs written by different teams. Isolation between jobs ensures that a single badly behaved job doesn't affect other jobs. It is robust by design.
• Samza can handle jobs that require large amounts of state, for example joining multiple streams, augmenting a stream with data from a database, or aggregating data over long time windows. This makes it a very powerful tool for applications.
Km4city Smart City Ecosystem Urban PlatformPaolo Nesi
keep city under control via personalized dashboards
improve city resilience, reducing risks and decision support
transform data in value for the city
monitoring services’ status of city operators
Smart City Dashboards, http://dashboard.km4city.org Dashboard Builder
monitoring and understanding the city users behaviour
Recommender and User Behavior Analyzer, http://recommender.km4city.org
WiFi monitor, http://wifimap.km4city.org
Origin Destination matrix tools http://www.disit.org/6694
collecting moods, contributions and data from the city users
Collecting contributions: images, stars, comments and Social Media
monitoring social media for city services and events, event predictions
Twitter Vigilance, http://www.disit.org/tv , http://tvsolr.disit.org
assessing city resilience level
Resilience Decision Support, http://resilienceds.km4city.org
Smart decision support system, http://smartds.km4city.org
improving city resilience, providing objective hints
Resilience Decision Support implementing European Resilience Management Guidelines (ERMG) http://www.resolute-eu.org
improving city users awareness with personal city assistants and participatory tools
Dashboard: http://dashboard.km4city.org
Km4City Web App http://www.km4city.org
Km4City Mobile App: http://www.km4city.org/app
enabling commercial and business applications
decision support access
aggregating multi-domain data and services for SMEs and city operators
Data /Service Aggregator: open, flexible and suitable access
data aggregation and access Smart City API
integrated data and services, accessible as on demand basis
providing services for third party portals and Apps: geo-localized data and services, info, suggestions
suggestion on demand service for SMEs and city operators
Suggestion On Demand see above
Personal Assistance: information, engagement, soundage
development tool for fast and low cost implementation of business and service oriented Apps
Smart City API
This presentation covers several aspects of modeling data and domains with a graph database like Neo4j. The graph data model allows high fidelity modeling. Using the first class relationships of the graph model allow to use much higher forms of normalization than you would use in a relational database.
Video here: https://vimeo.com/67371996
"Searching for Meaning: The Hidden Structure in Unstructured Data". Presentation by Trey Grainger at the Southern Data Science Conference (SDSC) 2018. Covers linguistic theory, application in search and information retrieval, and knowledge graph and ontology learning methods for automatically deriving contextualized meaning from unstructured (free text) content.
While the Rio 2016 Olympics are winding down and the final medals are being handed out, we thought we would share a bit of work that was done recently by Rik Van Bruggen to explore a really interesting dataset in Neo4j.
Based on an original public dataset by the UK newspaper The Guardian, Rik completed the medallist dataset to contain over 30,000 Olympians between 1896 and 2012. He created a graph model, loaded the data, and wrote a bunch of example queries that yielded some very interesting results. Join us for this 30 minute webinar where we’ll take you through this great Olympian graph and take the data for a spin yourself afterwards.
Presentation on Large Scale Data ManagementChris Bunch
These are the slides for a presentation I recently gave at a seminar on Large Scale Data Management. The first half talks about the current state of affairs in the debate between MapReduce and parallel databases, while the second half focuses on two recent papers on virtual machine migration.
Are you trying to change your company IT Department's persistence paradigm from OOP => RDBMS to OOP => NoSQLDb? Want to benefit of DDD+CQRS+EVS in your enterprise-class distributed application but don't know where to start?
Look at this...
How to establish a sustainable solution for data lineageLeigh Hill
The implementation of data lineage is complex but necessary, driven by regulation such as BCBS 239 and internal needs to gain a better understanding of risk, reduce systems complexity and eliminate duplicate data and processes. The webinar will discuss the essential elements of data lineage, how they can be implemented, and the beneficial outcomes of a successful and sustainable data lineage programme.
Join the webinar to find out about:
Requirements for data lineage
Data and management issues
Metadata in data lineage
Supporting technology
Business benefits
How to Search, Explore and Visualize Neo4j with Linkurious - Jean Villedieu @...Neo4j
Graph visualizations are cool! Learn how everyone can use Linkurious to solve common problems like correcting errors, identifying patterns, or finding and communicating insights.
Km4City: how to make smart and resilient your city, beginner documentPaolo Nesi
Open Source and inter-operable tools to
• keep city under control via personalized dashboards
• monitoring services’ status of city operators
• monitoring and understanding the city users behaviour
• collecting moods, contributions and data from the city users
• monitoring social media for city services and events, event predictions
• improve city resilience, reducing risks and decision support by:
• assessing city resilience level
• improving city resilience, providing objective hints
• improving city users awareness with personal city assistants and participatory tools
• transform data in value for the city:
• enabling commercial and business applications
• aggregating multi-domain data and services for SMEs and city operators
• enabling integrated city services into third party web portal for all
• providing suggestion on demand services for SMEs and city operators
• accelerating and simplifying the implementation of business and service oriented Apps
Follow the Km4City City Smartener Process
Graphically understand and interactively explore your Data LineageMohammad Ahmed
Graphically understand and interactively explore your Data Lineage:
Data Lineage for ER/Studio gives data management professionals and business users essential insight to the extracts, transformations, and loads of complex enterprise data. Data governance and organizational compliance is supported with detailed metadata management for risk reduction and data discrepancy isolation.
In this presentation we look at the key reasons for using ER/Studio Data Lineage and what it provides you with.To learn more about ER/Studio Data Lineage please look here: http://www.embarcadero.com/products/er-studio-data-lineage or request a demo here: http://forms.embarcadero.com/forms/ERStudioProductInterest
Palestra de Design Patterns sob o ponto de vista arquitetônico, apresentando diferentes tipos de paradigmas e princípios, como o GoF, ISO, GRASP, SOLID, MVC e Aspect.
Decompose that WAR? A pattern language for microservices (@QCON @QCONSP)Chris Richardson
When architecting an enterprise Java application, you need to choose between the traditional monolithic architecture consisting of a single large WAR file, or the more fashionable microservices architecture consisting of many smaller services. But rather than blindly picking the familiar or the fashionable, it's important to remember what Fred Books said almost 30 years ago: there are no silver bullets in software. Every architectural decision has both benefits and drawbacks. Whether the benefits of one approach outweigh the drawbacks greatly depends upon the context of your particular project. Moreover, even if you adopt the microservices architecture, you must still make numerous other design decisions, each with their own trade-offs.
A software pattern is an ideal way of describing a solution to a problem in a given context along with its tradeoffs. In this presentation, we describe a pattern language for microservices. You will learn about patterns that will help you decide when and how to use microservices vs. a monolithic architecture. We will also describe patterns that solve various problems in a microservice architecture including inter-service communication, service registration and service discovery.
Samza at LinkedIn: Taking Stream Processing to the Next LevelMartin Kleppmann
Slides from my talk at Berlin Buzzwords, 27 May 2014. Unfortunately Slideshare has screwed up the fonts. See https://speakerdeck.com/ept/samza-at-linkedin-taking-stream-processing-to-the-next-level for a version of the deck with correct fonts.
Stream processing is an essential part of real-time data systems, such as news feeds, live search indexes, real-time analytics, metrics and monitoring. But writing stream processes is still hard, especially when you're dealing with so much data that you have to distribute it across multiple machines. How can you keep the system running smoothly, even when machines fail and bugs occur?
Apache Samza is a new framework for writing scalable stream processing jobs. Like Hadoop and MapReduce for batch processing, it takes care of the hard parts of running your message-processing code on a distributed infrastructure, so that you can concentrate on writing your application using simple APIs. It is in production use at LinkedIn.
This talk will introduce Samza, and show how to use it to solve a range of different problems. Samza has some unique features that make it especially interesting for large deployments, and in this talk we will dig into how they work under the hood. In particular:
• Samza is built to support many different jobs written by different teams. Isolation between jobs ensures that a single badly behaved job doesn't affect other jobs. It is robust by design.
• Samza can handle jobs that require large amounts of state, for example joining multiple streams, augmenting a stream with data from a database, or aggregating data over long time windows. This makes it a very powerful tool for applications.
Km4city Smart City Ecosystem Urban PlatformPaolo Nesi
keep city under control via personalized dashboards
improve city resilience, reducing risks and decision support
transform data in value for the city
monitoring services’ status of city operators
Smart City Dashboards, http://dashboard.km4city.org Dashboard Builder
monitoring and understanding the city users behaviour
Recommender and User Behavior Analyzer, http://recommender.km4city.org
WiFi monitor, http://wifimap.km4city.org
Origin Destination matrix tools http://www.disit.org/6694
collecting moods, contributions and data from the city users
Collecting contributions: images, stars, comments and Social Media
monitoring social media for city services and events, event predictions
Twitter Vigilance, http://www.disit.org/tv , http://tvsolr.disit.org
assessing city resilience level
Resilience Decision Support, http://resilienceds.km4city.org
Smart decision support system, http://smartds.km4city.org
improving city resilience, providing objective hints
Resilience Decision Support implementing European Resilience Management Guidelines (ERMG) http://www.resolute-eu.org
improving city users awareness with personal city assistants and participatory tools
Dashboard: http://dashboard.km4city.org
Km4City Web App http://www.km4city.org
Km4City Mobile App: http://www.km4city.org/app
enabling commercial and business applications
decision support access
aggregating multi-domain data and services for SMEs and city operators
Data /Service Aggregator: open, flexible and suitable access
data aggregation and access Smart City API
integrated data and services, accessible as on demand basis
providing services for third party portals and Apps: geo-localized data and services, info, suggestions
suggestion on demand service for SMEs and city operators
Suggestion On Demand see above
Personal Assistance: information, engagement, soundage
development tool for fast and low cost implementation of business and service oriented Apps
Smart City API
This presentation covers several aspects of modeling data and domains with a graph database like Neo4j. The graph data model allows high fidelity modeling. Using the first class relationships of the graph model allow to use much higher forms of normalization than you would use in a relational database.
Video here: https://vimeo.com/67371996
"Searching for Meaning: The Hidden Structure in Unstructured Data". Presentation by Trey Grainger at the Southern Data Science Conference (SDSC) 2018. Covers linguistic theory, application in search and information retrieval, and knowledge graph and ontology learning methods for automatically deriving contextualized meaning from unstructured (free text) content.
JIMS IT Flash , a monthly newsletter-An Initiative by the students of IT Department, shares the knowledge to its readers about the latest IT Innovations, Technologies and News.Your suggestions, thoughts and comments about latest in IT are always welcome at itflash@jimsindia.org.
Visit Website : http://jimsindia.org/
Relational databases were conceived to digitize paper forms and automate well-structured business processes, and still have their uses. But, oftentimes with RDBMS, performance degrades with the increasing number and levels of data relationships and data size.
A graph database like Neo4j naturally stores, manages, analyzes, and uses data within the context of connections meaning Neo4j provides faster query performance and vastly improved flexibility in handling complex hierarchies than SQL.
This webinar explains why companies are shifting away from RDBMS towards graphs to unlock the business value in their data relationships.
You've heard the news, Data Science is the cool new career opportunity sweeping the world. Come learn from Thinkful Mentors all about this new and exciting industry.
SWOT of Bigdata Security Using Machine Learning Techniquesijistjournal
This paper gives complete guidelines on BigData, Different Views of BigData, etc.How the BigData is useful to us and what are the factors affecting BigData all the things are covered under this paper. The paper also contains the BigData Machine learning techniques and how the Hadoop comes into the picture. It also contains the what is importance of BigData security. The paper mostly covers all the main point that affect Big Data and Machine Learning.
The Art of Storytelling Using Data ScienceGramener
Gramener's VP - Sales, APAC Region, Vijayam Sirikonda interacted with the students of IIM Raipur and talked about the importance of data storytelling for business users.
"Big Data" is term heard more and more in industry – but what does it really mean? There is a vagueness to the term reminiscent of that experienced in the early days of cloud computing. This has led to a number of implications for various industries and enterprises. These range from identifying the actual skills needed to recruit talent to articulating the requirements of a "big data" project. Secondary implications include difficulties in finding solutions that are appropriate to the problems at hand – versus solutions looking for problems. This presentation will take a look at Big Data and offer the audience with some considerations they may use immediately to assess the use of analytics in solving their problems.
The talk begins with an idea of how big "Big Data" can be. This leads to an appreciation of how important "Management Questions" are to assessing analytic needs. The fields of data and analysis have become extremely important and impact nearly all facets of life and business. During the talk we will look at the two pillars of Big Data – Data Warehousing and Predictive Analytics. Then we will explore the open source tools and datasets available to NATO action officers to work in this domain. Use cases relevant to NATO will be explored with the purpose of show where analytics lies hidden within many of the day-to-day problems of enterprises. The presentation will close with a look at the future. Advances in the area of semantic technologies continue. The much acclaimed consultants at Gartner listed Big Data and Semantic Technologies as the first- and third-ranked top technology trends to modernize information management in the coming decade. They note there is an incredible value "locked inside all this ungoverned and underused information." HQ SACT can leverage this powerful analytic approach to capture requirement trends when establishing acquisition strategies, monitor Priority Shortfall Areas, prepare solicitations, and retrieve meaningful data from archives.
In this talk, I reflect on the tasks commonly involved in crafting visualizations and show examples of different applications of information/data visualization. Along this ride I will share my workflow, point out the common pitfalls and provide recommendations.
These slides were from my guest lecture in InfoVis class at UC Berkeley iSchool on Apr 11, 2016. Thank you Prof. Marti Hearst for inviting.
Data Science Innovations : Democratisation of Data and Data Science suresh sood
Data Science Innovations : Democratisation of Data and Data Science covers the opportunity of citizen data science lying at the convergence of natural language generation and discoveries in data made by the professions, not data scientists.
How to Feed a Data Hungry Organization – by Traveloka Data TeamTraveloka
In Traveloka's Inaugural Data Meetup held in April 2017, Ainun Najib (Head of Data), Dr. Philip Thomas (Lead Data Scientist), and Rendy B. Junior (Lead Data Engineer) shared about the journey that Traveloka's Data Team have taken so far so that the audience can learn from the struggles and triumphs in managing Traveloka's burgeoning data.
You will learn more about:
1) Data culture in Traveloka
2) Data engineering in Traveloka
3) Data science in Traveloka
To follow our LinkedIn page, visit bit.ly/TravelokaLinkedInPage
Safe Harbor Statement
Our discussion may include predictions, estimates or other information that might be considered conclusive. While these conclusive statements represent our current judgment on the best practices, they are subject to risks and uncertainties that could cause actual results to differ materially. You are cautioned not to place undue reliance on our statements, which reflect our opinions only as of the date of this presentation. Please keep in mind that we are not obligating ourselves to revise or publicly release the results of any revision to these presentation materials in light of new information or future events.
Graph Database is the new paradigm of Big Data.
New insights are discovered in the connected data.
Fabricating Big Data into connected data is the cutting edge technology.
Graph database is the driver for sustainable growth in the Era of Big Data.
Graph Data is already prevailing among the global leading companies.
Graph Database will pass the dawn of standards.
The most widely adopted method will be the Hybrid Database.
Each company needs to prepare for the wave of change.
AgenGraph will support your business with superior capabilities.
For more information, please visit www.bitnine.net
Similar to The Five Graphs of Government: How Federal Agencies can Utilize Graph Technology (20)
Russian anarchist and anti-war movement in the third year of full-scale warAntti Rautiainen
Anarchist group ANA Regensburg hosted my online-presentation on 16th of May 2024, in which I discussed tactics of anti-war activism in Russia, and reasons why the anti-war movement has not been able to make an impact to change the course of events yet. Cases of anarchists repressed for anti-war activities are presented, as well as strategies of support for political prisoners, and modest successes in supporting their struggles.
Thumbnail picture is by MediaZona, you may read their report on anti-war arson attacks in Russia here: https://en.zona.media/article/2022/10/13/burn-map
Links:
Autonomous Action
http://Avtonom.org
Anarchist Black Cross Moscow
http://Avtonom.org/abc
Solidarity Zone
https://t.me/solidarity_zone
Memorial
https://memopzk.org/, https://t.me/pzk_memorial
OVD-Info
https://en.ovdinfo.org/antiwar-ovd-info-guide
RosUznik
https://rosuznik.org/
Uznik Online
http://uznikonline.tilda.ws/
Russian Reader
https://therussianreader.com/
ABC Irkutsk
https://abc38.noblogs.org/
Send mail to prisoners from abroad:
http://Prisonmail.online
YouTube: https://youtu.be/c5nSOdU48O8
Spotify: https://podcasters.spotify.com/pod/show/libertarianlifecoach/episodes/Russian-anarchist-and-anti-war-movement-in-the-third-year-of-full-scale-war-e2k8ai4
Many ways to support street children.pptxSERUDS INDIA
By raising awareness, providing support, advocating for change, and offering assistance to children in need, individuals can play a crucial role in improving the lives of street children and helping them realize their full potential
Donate Us
https://serudsindia.org/how-individuals-can-support-street-children-in-india/
#donatefororphan, #donateforhomelesschildren, #childeducation, #ngochildeducation, #donateforeducation, #donationforchildeducation, #sponsorforpoorchild, #sponsororphanage #sponsororphanchild, #donation, #education, #charity, #educationforchild, #seruds, #kurnool, #joyhome
Up the Ratios Bylaws - a Comprehensive Process of Our Organizationuptheratios
Up the Ratios is a non-profit organization dedicated to bridging the gap in STEM education for underprivileged students by providing free, high-quality learning opportunities in robotics and other STEM fields. Our mission is to empower the next generation of innovators, thinkers, and problem-solvers by offering a range of educational programs that foster curiosity, creativity, and critical thinking.
At Up the Ratios, we believe that every student, regardless of their socio-economic background, should have access to the tools and knowledge needed to succeed in today's technology-driven world. To achieve this, we host a variety of free classes, workshops, summer camps, and live lectures tailored to students from underserved communities. Our programs are designed to be engaging and hands-on, allowing students to explore the exciting world of robotics and STEM through practical, real-world applications.
Our free classes cover fundamental concepts in robotics, coding, and engineering, providing students with a strong foundation in these critical areas. Through our interactive workshops, students can dive deeper into specific topics, working on projects that challenge them to apply what they've learned and think creatively. Our summer camps offer an immersive experience where students can collaborate on larger projects, develop their teamwork skills, and gain confidence in their abilities.
In addition to our local programs, Up the Ratios is committed to making a global impact. We take donations of new and gently used robotics parts, which we then distribute to students and educational institutions in other countries. These donations help ensure that young learners worldwide have the resources they need to explore and excel in STEM fields. By supporting education in this way, we aim to nurture a global community of future leaders and innovators.
Our live lectures feature guest speakers from various STEM disciplines, including engineers, scientists, and industry professionals who share their knowledge and experiences with our students. These lectures provide valuable insights into potential career paths and inspire students to pursue their passions in STEM.
Up the Ratios relies on the generosity of donors and volunteers to continue our work. Contributions of time, expertise, and financial support are crucial to sustaining our programs and expanding our reach. Whether you're an individual passionate about education, a professional in the STEM field, or a company looking to give back to the community, there are many ways to get involved and make a difference.
We are proud of the positive impact we've had on the lives of countless students, many of whom have gone on to pursue higher education and careers in STEM. By providing these young minds with the tools and opportunities they need to succeed, we are not only changing their futures but also contributing to the advancement of technology and innovation on a broader scale.
This session provides a comprehensive overview of the latest updates to the Uniform Administrative Requirements, Cost Principles, and Audit Requirements for Federal Awards (commonly known as the Uniform Guidance) outlined in the 2 CFR 200.
With a focus on the 2024 revisions issued by the Office of Management and Budget (OMB), participants will gain insight into the key changes affecting federal grant recipients. The session will delve into critical regulatory updates, providing attendees with the knowledge and tools necessary to navigate and comply with the evolving landscape of federal grant management.
Learning Objectives:
- Understand the rationale behind the 2024 updates to the Uniform Guidance outlined in 2 CFR 200, and their implications for federal grant recipients.
- Identify the key changes and revisions introduced by the Office of Management and Budget (OMB) in the 2024 edition of 2 CFR 200.
- Gain proficiency in applying the updated regulations to ensure compliance with federal grant requirements and avoid potential audit findings.
- Develop strategies for effectively implementing the new guidelines within the grant management processes of their respective organizations, fostering efficiency and accountability in federal grant administration.
Jennifer Schaus and Associates hosts a complimentary webinar series on The FAR in 2024. Join the webinars on Wednesdays and Fridays at noon, eastern.
Recordings are on YouTube and the company website.
https://www.youtube.com/@jenniferschaus/videos
Jennifer Schaus and Associates hosts a complimentary webinar series on The FAR in 2024. Join the webinars on Wednesdays and Fridays at noon, eastern.
Recordings are on YouTube and the company website.
https://www.youtube.com/@jenniferschaus/videos
A process server is a authorized person for delivering legal documents, such as summons, complaints, subpoenas, and other court papers, to peoples involved in legal proceedings.
Understanding the Challenges of Street ChildrenSERUDS INDIA
By raising awareness, providing support, advocating for change, and offering assistance to children in need, individuals can play a crucial role in improving the lives of street children and helping them realize their full potential
Donate Us
https://serudsindia.org/how-individuals-can-support-street-children-in-india/
#donatefororphan, #donateforhomelesschildren, #childeducation, #ngochildeducation, #donateforeducation, #donationforchildeducation, #sponsorforpoorchild, #sponsororphanage #sponsororphanchild, #donation, #education, #charity, #educationforchild, #seruds, #kurnool, #joyhome
3. Fred Kagan David Mesa
Chief Knowledge
Architect for
NASA
Kimberly Kagan
Director
Critical Threats Project
American Enterprise Institute
President
Institute for the
Study of War
Today’s Guest Speakers
4. “Life can only be understood backwards;
but it must be lived forwards.”
-Søren Kierkegaard
5.
6. Yellowstone National Park Ecosystem
Known Influences Entered One-at-a-Time
(Willow)-[:HABITAT_FOR]->(Lincoln’s Sparrow)
(Aspen)-[:FOOD_FOR]->(Beaver)
(Beaver Ponds)-[:HABITAT_FOR]->(Beaver)
(Deer)-[:BROWSE_ON]->(Cottonwood)
(Berry Shrubs)-[:FOOD_FOR]->(Bears)
…
8. MATCH path = (:Animal {Entity:"Wolves"})-[*]->(:Landscape {Entity:"Rivers"})
WITH extract(node IN nodes(path) | node.Yellowstone) AS factor, rand() AS number
RETURN factor AS How_Wolves_Affect_RiverStability
ORDER BY number
LIMIT 5
Yellowstone National Park Ecosystem
Query for Trophic Cascades
Conclusion:
9. 1. Where do graph databases fit into the overall data landscape?
2. What is a graph database & when is it useful?
3. Be inspired to find your next graph in government
Takeaways from this Session:
11. Discrete Data
Minimally
connected data
All You Really Need to Know
(at least for today)
Other NoSQL Relational DBMS Neo4j Graph DB
Connected Data
Focused on
Data Relationships
12. e of Graphs has created some of the most successful companies in the wo
13. “Graph analysis is possibly the single most effective competitive
differentiator for organizations pursuing data-driven operations
and decisions after the design of data capture.”
By the end of 2018, 70% of leading organizations will have one or
more pilot or proof-of-concept efforts underway utilizing graph
databases.
Analyst Perspective
“Forrester estimates that over 25% of enterprises will be using
graph databases by 2017”
IT Market Clock for Database Management Systems, 2014
https://www.gartner.com/doc/2852717/it-market-clock-database-management
TechRadar™: Enterprise DBMS, Q1 2014
http://www.forrester.com/TechRadar+Enterprise+DBMS+Q1+2014/fulltext/-/E-RES106801
Making Big Data Normal with Graph Analysis for the Masses, 2015
http://www.gartner.com/document/3100219
22. Relational
Database
Good for:
• Well-understood data structures
that don’t change too frequently
A way of representing data
• Known problems involving
discrete parts of the data, or
minimal connectivity
DATA
23. Graph
Database
Relational
Database
A way of representing data
Good for:
• Dynamic systems: where the data
topology is difficult to predict
• Dynamic requirements:
the evolve with the business
• Problems where the relationships
in data contribute meaning & value
Good for:
• Well-understood data structures
that don’t change too frequently
• Known problems involving
discrete parts of the data, or
minimal connectivity
24. 27
A unified view for
ultimate agility
• Easily understood
• Easily evolved
• Easy collaboration
between business
and IT
#1 Benefit: Project Agility
The Whiteboard Model Is the Physical Model
25. Connectedness and Size of Data Set
ResponseTime
Relational and
Other NoSQL
Databases
0 to 2 hops
0 to 3 degrees
Thousands of connections
1000x
Advantage
Tens to hundreds of hops
Thousands of degrees
Billions of connections
Neo4j
“Minutes to
milliseconds”
#2 Benefit:
“Minutes to Milliseconds” Real-Time Query Performance
26. “We found Neo4j to be literally thousands of times faster
than our prior MySQL solution, with queries that require
10-100 times less code. Today, Neo4j provides eBay with
functionality that was previously impossible.”
- Volker Pacher, Senior Developer
“Minutes to milliseconds” performance
Queries up to 1000x faster than RDBMS or other NoSQL
#3 Benefit:
“Minutes to Milliseconds” Real-Time Query Performance
28. At Write Time:
data is connected
as it is stored
At Read Time:
Lightning-fast retrieval of data and
relationships via pointer chasing
Index free adjacency
Magic Ingredient #1 of 3:
Graph Optimized Memory & Storage
29. MATCH (:Person { name:“Dan”} ) -[:MARRIED_TO]-> (spouse)
MARRIED_TO
Dan Ann
NODE RELATIONSHIP TYPE
LABEL PROPERTY VARIABLE
Magic Ingredient #2 of 3:
A Productive and Powerful Graph Query Language
30. 3
3
Example HR Query in SQL The Same Query using Cypher
MATCH (boss)-[:MANAGES*0..3]->(sub),
(sub)-[:MANAGES*1..3]->(report)
WHERE boss.name = “John Doe”
RETURN sub.name AS Subordinate,
count(report) AS Total
Project Impact
Less time writing queries
• More time understanding the answers
• Leaving time to ask the next question
Less time debugging queries:
• More time writing the next piece of code
• Improved quality of overall code base
Code that’s easier to read:
• Faster ramp-up for new project members
• Improved maintainability & troubleshooting
Magic Ingredient #2 of 3:
A Productive and Powerful Graph Query Language
31. Graph Transactions Over
ACID Consistency
Graph Transactions Over
Non-ACID DBMSs
34
Maintains Integrity Over Time Becomes Corrupt Over Time
Magic Ingredient #3 of 3:
ACID Graph Writes
36. Law
Enforcement
Use Case:
Information and Data
Synchronization in
Law Enforcement
Law Enforcement Agencies use
Neo4j to model the information
into graphs to improve efficiency
and make direct and implicit
patterns readily apparent in real
time.
A suspect often appears in several
different databases
Financial recordsConvictions
Adresses
Vehicles
Traffic cameras
Arrests
Police Reports
Agency Records Public Records Traffic Records
SUSPECT
The Graphs In Government
37. The Graphs In Government 01
Bystander investigated
due to deep connection found
Use Case:
Modeling Graphs
in Investigations
Neo4j is used by LE to track all
parts of criminal investigations,
including witnesses, suspects,
forensic evidence, and
locations. All related directly and
indirectly.
Law
Enforcement
39. Revolving Debt
Number of Accounts
Normal behavior
Fraudulent pattern
Fraud Detection With Connected Analysis
40. The Graphs In Government 01
ACCOUNT
HOLDER 2
ACCOUNT
HOLDER 1
ACCOUNT
HOLDER 3
CREDIT
CARD
BANK
ACCOUNT
BANK
ACCOUNT
BANK
ACCOUNT
ADDRESS
PHONE
NUMBER
PHONE
NUMBER
SSN 2
UNSECURED
LOAN
SSN 2
UNSECURED
LOAN
Law
Enforcement
Use Case:
Modeling Fraud
Rings as Graphs
Organizing a fraud ring in the real
world is relatively simple. A group of
people share their personal
information to create synthetic
identities. For example with just 2
individuals sharing names and
social security numbers can create
4 different identities. This can be
discovered with connected analysis.
48. The Graphs In Government 01
Withdraw
Use Case:
Combating Money
Laundering With
Graphs
Neo4j is used to combat
advanced money laundering
schemes. Money laundering is all
about how funds travel across a
network of parties. Without graph
analysis capabilities, some of
these patterns can be impossible
to detect.
Washed in complex series of transfers
Anti-Money
Laundering
Deposit
49. The Graphs In Government 01
The Cali
Cartel Money
Laundering
Scheme
Money
Laundering
50. Source: http://neo4j.com/blog/analyzing-panama-papers-neo4j/
Case Study:
“The Panama
Papers”
• The International Consortium of
Investigative Journalists (ICIJ) exposed
highly connected networks of offshore tax
structures used by the world’s richest elites.
• With 11,5 million documents, it’s the largest
financial leak of all times.
• The unfolded connections in “The Panama
Papers” was a major news story 2016.
The Graphs In Government 01
Money
Laundering
If there’s one thing to remember for today, it’s this journey
Frederick Kagan, Director, Critical Threats Project at American Enterprise Institute, and Kimberly Kagan, President at Institute for the Study of War
I’d like to start the day with a koan…
What Kierkegaard is talking about is Causality. Oftentimes we don’t understand what the effects will be because they’re so complex. --- Let me show you one of my favorite examples of complex causality in nature.
Here is what one gets if one does precisely that. Finding the paper, reading it, and expressing the links as a graph, was given to one of our summer interns, who was able to build this graph in an afternoon.
Source: http://gist.neo4j.org/?0ac320c799ce55089377
Here is what one gets if one does precisely that. Finding the paper, reading it, and expressing the links as a graph, was given to one of our summer interns, who was able to build this graph in an afternoon.
Source: http://gist.neo4j.org/?0ac320c799ce55089377
The beauty of the graph however is in the questions it enables us to answer. For example, here we ask: what are all of the paths between “Wolves” and “Rivers”. It turns out there are quite a few, but that all four of the paths leading immediately into “Rivers” have the effect of promoting the rivers. We can easily conclude therefore that wolves can be expected to have an overall salutary effect upon the rivers… which was, after 15 years of experimental science, found to be true.
And deriving value from data-relationships is exactly what some of the most successful companies in the world have done.
Google created perhaps the most valuable advertising system of all time on top of their search-enginge, which is based on relationships between webpages.
Linkedin created perhaps the most valuable HR-tool ever based on relationships amongst professional
And this is also what pay-pal did, creating a peer-to-peer transaction service, based on relationships.
How many of you feel you have a handle on the Big Data Landscape?
So apparently according to this article in Dataconomy, it’s simply a matter of memorizing this.
The “fruit salad” slide earlier outlined technologies that were mostly focused on dealing with data in discrete chunks.
What’s interesting about the right side is that some of the largest & most successful tech companies in the last decade were possible thanks to their use of graphs.
And deriving value from data-relationships is exactly what some of the most successful companies in the world did.
Google created perhaps the most valuable advertising system of all time on top of their search-enginge, which is based on relationships between webpages.
Linkedin created perhaps the most valuable HR-tool ever based on relationships amongst professional
And this is also what pay-pal did, creating a peer-to-peer transaction service, based on relationships.
Continuing on – We have receive very solid validation from these industry watchers that the market we are pursuing represents a huge opportunity and being anointed as the leader in this market that is likely to grow at this rate is very exciting.
“Neo4j is the most popular graph database on the planet, so we have a privileged view on the massive adoption of graph databases. As an example, Neo4j is today used in verticals as diverse as <click> Software, <click>, Financial Services, <click> Retail, etc… by some of the biggest companies on the planet, across a wide range of use cases.”
First, not everyone in the room would know what a graph is.
What this means for your data structure
Kick off with discussing major trends happening in enterprises.
The query asks: “Find all direct reports and how many people they manage, up to three levels down”
Keeping Your Graph Intact is Essential for Graph Operations
This is great… Now let’s talk about reads. Some applications are ok with somewhat stale data. Some are not. Causal consistency gives you the choice.
Titan example:
Ghost Vertices: If a vertex gets deleted while it is concurrently being modified, the vertex might re-appear as a ghost.
Stale Index entries: Index entries might point to nonexistent vertices in case of partial mutation persistence.
Half-Edges: Only one direction of an edge gets persisted or deleted which might lead to the edge not being or incorrectly being retrieved.
Uni-directed Ghost Edges: A uni-directed edge points to a deleted vertex.
First, not everyone in the room would know what a graph is.
Its obvious that traditional technologies which were aimed at individuals and their behavior are inadequate to detect and prevent sophisticated fraud rings. So why is that?
So let’s take a look on how Data Synchronization in Law Enforcement could work modeled in a graph.
For example: We have a suspect that might have prior convictions, arrests, and figures in police reports, and this could be stored in agency records..
A suspect might appear in many different databases. However these systems are not designed to relate to each other and here Neo4j and a graph database approach would be a very effective tool to augment existing systems.
Having graph search capabilities across this data opens up for both targeted searches and advanced connected analysis.
Neo4j is used by LE to track all parts of criminal investigations, including witnesses, suspects, forensic evidence, and locations.
All of this is related directly and indirectly. Therefor connected analysis can give Law Enforcement agents an important insight of who and what to investigate… even implicit connections could unravel patterns that weren’t available before.
[In this simple fraud detection approach to detect credit card fraud, it is relatively easy to spot outliers. But what if the fraudster commits fraud while still exhibiting normal behavior. Well - this is exactly how fraud rings operate]
[A fraud ring rarely strays outside the normal behavior band. Instead they operate within normal limits and commit widespread fraud. This is very hard to detect by systems that are looking for outliers or activities outside the normal band.]
Another important area for Law Enforcement is Fraud.
Organizing a fraud ring in the real world is relatively simple. A group of people share their personal information to create synthetic identities. For example with just 2 individuals sharing names and social security numbers can create 4 different identities. This is something that can be discovered with connected analysis and the use of graphs.
Today, agencies need to augment their discrete analysis capability with connected analysis. Whether you’re dealing with a fraud ring or stolen and synthetic identities, it’s extremely powerful to use a graph database
Normally, your operational data is loaded into your fraud detection application which then conducts a wide range of discrete analysis to help your internal team to detect fraud.
Neo4j helps extend this capability with connected analysis. You can load some of the same information inside Neo4j. Neo4j’s native graph model stores both the data and its relationships which can help your team detect known fraud patterns as well as discover new ones.
Top Queries:
1. Trace dependencies up from servers all the way to applications and users
2. Trace dependencies across virtual and physical layers of infrastructure
3. Identify routes & alternate paths between various points in the network
4. Find the best, shortest, or least busy path, the best location in the network to introduce a new service
Because money laundering is all about how funds travel across a network of parties. Without graph analysis capabilities, some of these patterns can be impossible to detect.
What we see here a simple sketch of how this could be modelled. It’s deposits from different people and money that gets washed in a complex series of transfers.
This is a real example of such complexities, done by the Department of Treasury’s Office of Foreign Assets Control… unfolding the Money Laundering Scheme of the Cali Cartel.
And what we see here is a highly connected network of accounts, assets and people, which is perfect for graph analysis.
One case study that we are very proud of is enabling The International Consortium of Investigative Journalists (ICIJ) to expose highly connected networks of offshore tax structures, through what they call the Panama Papers.
Mars Curiosity Rover
In the retail-example… this would probably look something like this. You will have systems in place to perform different functions, all of them probably crucial and doing the job btw, The problem is that these systems are designed to perform a very specific task.
So in order to put the data from all these systems to good use effectively, in the recommendations-example we just showed you, in real-time you need to add the graph database-layer.
Because building a system based on a foundation that doesn't handle connections naturally, is extremely difficult, and it would require so much time and money, that it is virtually impossible to justify.
That WWI can be predicted without domain knowledge by iterating a graph and applying local structural constraints is nothing short of astonishing to me.
Note how the network slides into a balanced labeling — and into World War I.
You can pull in other dimensions easily here: geopolitics, weapons technology, genealogy (because the royals were not exactly blameless in this),
Graphs rock. Sometimes humans not so much.