The importance of data

•

2 j'aime•2,665 vues

APNIC

Presentation by Jay Daley at APRICOT 2017 on Tuesday, 28 February 2017.

Internet

Importance of data
Jay Daley, APNIC Vietnam 2017

• Small registry - Big data pioneer
22 server Hadoop cluster installed in 2012
Full packet capture of DNS servers
• Data science oriented research team
18% of total staff
• World class registrar data portal
Main business priority for new development
• Actively building data products
Recent success with broadbandmap.nz
• Open data portal for .nz data
Why is .nz presenting?
APNIC Vietnam 2017 2

• Evidence based policy
• Organisational development
• Detecting badness
• Business - more, new, better
• Public trust
Why data matters
APNIC Vietnam 2017 3

Evidence based policy
APNIC Vietnam 2017 4

• Data is not public and so …
No reproducibility
Agenda set by those who pay the analysts
Very low throughput of research
• Some people have their own data
Gives them real power in the debate
• Open Data means Open Debate
Use of data in policy
APNIC Vietnam 2017 5

Case study – hoarding?
APNIC Vietnam 2017 6
1
10
100
1000
10000
100000
1000000
1
2
3
4
5
6
7
8
9
10
11-20
21-30
31-40
41-50
51-60
61-70
71-80
81-90
91-100
101-200
201-300
301-400
401-500
501-600
601-700
801-900
901-1000
1001-2000
2001-3000
Numberofregistrants
Portfolio size
Number of registrants by portfolio size

• Highly developed use of data
Multiple research teams, cooperative forums and
service providers
Multiple data resources, extensive data sharing
• Data collection – source evidence
Passive monitoring (e.g. DNSDB, PassiveTotal)
Hand produced by threat researchers
• Strong sharing culture – via data feeds
40+ feeds available (both NFP and commercial)
Track domains, IPs, credentials, URLs, etc
Very active area
APNIC Vietnam 2017 8

Business – more, new, better
APNIC Vietnam 2017 9

11
Search by
address
Search by
dropping a pin
Switch to
aerial view
Browse
APNIC Vietnam 2017

• Over 20 providers
• Some very sensitive about their data
• Awkward formats
• High cost for them to provide
• Our approach
• Ask nicely – no payment
• Demonstrate security – gain trust
• Sell the vision
• Be patient
• Help with tools
• Built a tool to generate wireless coverage
• Adopted another tool to convert files to right
format
The data
15APNIC Vietnam 2017

• Only be used for this purpose:
• Provide info to owner/occupier or
prospective owner/occupier on availability
• Missing providers
• Missing technologies
• No satellite (coming soon)
• No cellular
Limitations on the data
16APNIC Vietnam 2017

“Sunlight is the best
disinfectant”
• Open data can prove:
Effectiveness of markets and regulators
Social benefit
Where problems remain
Open data and public trust
APNIC Vietnam 2017 19

Case study – Web Index
APNIC Vietnam 2017 20

Data enabled community &
industry
• Data openly shared by all market
participants
• Data is easy to find and use and can be
trusted
• Strong community use of data
• Authoritative publications
A goal to consider
APNIC Vietnam 2017 21

• Begin cultural change
Broaden the principle of openness to include data
Set the vision of the benefits
• Engage community – “social license”
Community expectations of openness vs privacy
• Put legal framework in place
Adjust contracts, policies and processes to
support open data
Determine privacy protection rules
Steps to make it happen
APNIC Vietnam 2017 22

• National Broadband Map
• broadbandmap.nz
• Internet Data Portal
• idp.nz
• IP topology map
• ip.topology.net.nz
• BGP topology map
• bgp.topology.net.nz
Finding our services
23APNIC Vietnam 2017

Contact:
www.nzrs.net.nz
jay@nzrs.net.nz
Thanks
Any questions?

Contenu connexe

Tendances

Data management

RahulJoshi975765

Data Quality Presentation

Stephen McCarthy

Data visualization

Jan Willem Tulp

Data Quality

Michael Collins

Introduction to Data Visualization

Stephen Tracy

Data Governance

SambaSoup

Data analysis

Carthikvinay1

Data Analytics in Healthcare

Mark Gall

Tackling Data Quality problems requires more than a series of tactical, one-off improvement projects. By their nature, many Data Quality problems extend across and often beyond an organization. Addressing these issues requires a holistic architectural approach combining people, process, and technology. Join Nigel Turner and Donna Burbank as they provide practical ways to control Data Quality issues in your organization.

DAS Slides: Data Quality Best Practices

DATAVERSITY

Introduction to data analytics

SSaudia

Data Analytics for R Course: https://www.edureka.co/r-for-analytics This Edureka Tutorial on Data Analytics for Beginners will help you learn the various parameters you need to consider while performing data analysis. The following are the topics covered in this session: Introduction To Data Analytics Statistics Data Cleaning and Manipulation Data Visualization Machine Learning Roles, Responsibilities and Salary of Data Analyst Need of R Hands-On Statistics for Data Science: https://youtu.be/oT87O0VQRi8 Follow us to never miss an update in the future. Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka

Data Analytics For Beginners | Introduction To Data Analytics | Data Analytic...

Edureka!

Business Intelligence Trends 2020

Wiiisdom

1. Data Analytics-introduction

Unit 2

Data analytics

What is "data"?

Data Exploration.pptx

PerumalPitchandi

Data analytics vs. Data analysis

Dr. C.V. Suresh Babu

Master Data Management (MDM) can provide significant value to the organization in creating consistent key data assets such as Customer, Product, Supplier, Patient, and the list goes on. But getting MDM “right” requires a strategic mix of Data Architecture, business process, and Data Governance. Join this webinar to learn how to find the “sweet spot” between technology, design, process, and people for your MDM initiative.

Master Data Management - Aligning Data, Process, and Governance

DATAVERSITY

Metadata ppt

Shashikant Kumar

Tendances (20)

Data management

Data Quality Presentation

Data visualization

Data Quality

Introduction to Data Visualization

Data Governance

Data analysis

Data Analytics in Healthcare

DAS Slides: Data Quality Best Practices

Introduction to data analytics

Data Analytics For Beginners | Introduction To Data Analytics | Data Analytic...

Business Intelligence Trends 2020

1. Data Analytics-introduction

Unit 2

Data analytics

What is "data"?

Data Exploration.pptx

Data analytics vs. Data analysis

Master Data Management - Aligning Data, Process, and Governance

Metadata ppt

En vedette

3 Big Data Trends for 2017

Judd Bagley

5 facts everyone should know about big data presentation

Infobrandz

Digital marketing Trends 2017 in vietnam

Time Universal

Digital report in Vietnam 2016

VMarketing (Powered by VIVAS, A member of VNPT)

B2C Content Marketing 2017 - Benchmarks, Budgets & Trends - North America

Content Marketing Institute

Vietnam IPv6 Measurement

APNIC

What is Big Data?

Bernard Marr

We Are Social's comprehensive new Digital in 2016 report presents internet, social media, and mobile usage statistics and trends from all over the world. It contains more than 500 infographics, including global data snapshots, regional overviews, and in-depth profiles of the digital landscapes in 30 of the world's key economies. For a more insightful analysis of the numbers contained in this report, please visit http://bit.ly/DSM2016ES.

Digital in 2016

We Are Social Singapore

Cimigo customer service in vietnam today

Cat Van Khoi

PDU 214 Methods of Observation & Interviewing: Observation - Methods & Record...

Agatha N. Ardhiati

Mapping presentation THAG big data from space

Bartosz Szkudlarek

Benefícios e desafios que Big Data & Analytics traz para as empresas na jorna...

Flávio Secchieri Mariotti

Author: Stefan Papp, Data Architect at “The unbelievable Machine Company“. An overview of Big Data Processing engines with a focus on Apache Spark and Apache Flink, given at a Vienna Data Science Group meeting on 26 January 2017. Following questions are addressed: • What are big data processing paradigms and how do Spark 1.x/Spark 2.x and Apache Flink solve them? • When to use batch and when stream processing? • What is a Lambda-Architecture and a Kappa Architecture? • What are the best practices for your project?

20170126 big data processing

Vienna Data Science Group

TV market in Vietnam

DI Marketing

Data Mining, Predictive Analytics and Big Data - Course information Spring 2017

Andrés Fortino, PhD

Uji perbedaan ayda tri_valen_virdya

Ayda Fitriani

Bsc vietnam outlook 2017 eng red

Long Tran

Vietnam TV Market Overview

Financial Business News Channel

The study of research methodology gives the student the necessary training in gathering material and arranging or card-indexing them, participation in the field work when required, and also training in techniques for the collection of data appropriate to particular problems, in the use of statistics, questionnaires and controlled experimentation and in recording evidence, sorting it out and interpreting it.

Importance of knowing how research is done - Research Methodology - Manu Melw...

manumelwin

Statistik deskriptif(1)

Cloudys04

En vedette (20)

3 Big Data Trends for 2017

5 facts everyone should know about big data presentation

Digital marketing Trends 2017 in vietnam

Digital report in Vietnam 2016

B2C Content Marketing 2017 - Benchmarks, Budgets & Trends - North America

Vietnam IPv6 Measurement

What is Big Data?

Digital in 2016

Cimigo customer service in vietnam today

PDU 214 Methods of Observation & Interviewing: Observation - Methods & Record...

Mapping presentation THAG big data from space

Benefícios e desafios que Big Data & Analytics traz para as empresas na jorna...

20170126 big data processing

TV market in Vietnam

Data Mining, Predictive Analytics and Big Data - Course information Spring 2017

Uji perbedaan ayda tri_valen_virdya

Bsc vietnam outlook 2017 eng red

Vietnam TV Market Overview

Importance of knowing how research is done - Research Methodology - Manu Melw...

Statistik deskriptif(1)

Similaire à The importance of data

BigData-Challenges.pptx

amanyosama12

Presented at CampIT Conference on April 13th, 2017 ( http://campconferences.com/events/2017/intelligence.htm ) The typical perception of Big Data, Analytics, and Predicative/AI is that only the big companies can reap the benefits. Many believe they need a data warehouse, expensive reporting software, and an army of data scientists to get any value out of effort and cost. This session will explore and debunk that myth and showcase how companies of any size can participate in the journey. While there are many maturity models and journey maps available, most are not designed to be practical guides to solving common business problems. Because of the explosion in availability in cloud services, the barrier to entry has eroded significantly. During this session, we will look at some practical steps to access these capabilities and provide examples to where market-leading and growth companies have seen large benefits. Attendees will walk away with broader understanding of what’s possible to move their company through the journey in 2017.

The Data & Analytics Journey – Why it’s more attainable for your company than...

John Head

This proposes an initial smart data framework and structure to allow the nuggets of value contained in the deluge of largely irrelevant and useless data to be isolated and extracted. It enables your organisation to ask the questions to understand where it should be in terms of its data state and profile and what it should do to achieve the desired skills level across the competency areas of the framework. Every organisation operates within a data landscape with multiple sources of data relating to its activities that is acquired, transported, stored, processed, retained, analysed and managed. Interactions across the data landscape generate primary data. When you extend the range of possible interactions business processes outside the organisation you generate a lot more data. Smart data means being: • Smart in what data to collect, validate and transform • Smart in how data is stored, managed, operated and used • Smart in taking actions based on results of data analysis including organisation structures, roles, devolution and delegation of decision-making, processes and automation • Smart in being realistic, pragmatic and even skeptical about what can be achieved and knowing what value can be derived and how to maximise value obtained • Smart in defining an achievable, benefits-lead strategy integrated with the needs business and in its implementation • Smart in selecting the channels and interactions to include – smart data use cases Smart data competency areas comprise a complete set of required skills and abilities to design, implement and operate an appropriate smart data programme.

Forget Big Data. It's All About Smart Data

Alan McSweeney

Big data

gopichand naragam

Big data

gopichand naragam

Supporting Open Data Publishers

Derilinx

How Data-Driven Approaches are Changing Your Data Management Strategies Introducing data-driven strategies into your business model alters the way your organization manages and provides information to your customers, partners and employees. Gone are the days of “waterfall” implementation strategies from relational data to applications within a data center. Now, data-driven business models require agile implementation of applications based on information from all across an organization–on-premises, cloud, and mobile–and includes information from outside corporate walls from partners, third-party vendors, and customers. Data management strategies need to be ready to meet these challenges or your new and disruptive business models will fail at the most critical time: when your customers want to access it.

Converging your data landscape

MapR Technologies

Watch full webinar here: https://bit.ly/3Ab9gYq Imagina llegar a un parque de atracciones con tu familia y comenzar tu día sin el típico plano que te permitirá planificarte para saber qué espectáculos ver, a qué atracciones ir, donde pueden o no pueden montar los niños… Posiblemente, no podrás sacar el máximo partido a tu día y te habrás perdido muchas cosas. Hay personas que les gusta ir a la aventura e ir descubriendo poco a poco, pero cuando hablamos de negocios, ir a la aventura puede ser fatídico... En la era de la explosión de la información repartida en distintas fuentes, el gobierno de datos es clave para garantizar la disponibilidad, usabilidad, integridad y seguridad de esa información. Asimismo, el conjunto de procesos, roles y políticas que define permite que las organizaciones alcancen sus objetivos asegurando el uso eficiente de sus datos. La virtualización de datos, herramienta estratégica para implementar y optimizar el gobierno del dato, permite a las empresas crear una visión 360º de sus datos y establecer controles de seguridad y políticas de acceso sobre toda la infraestructura, independientemente del formato o de su ubicación. De ese modo, reúne múltiples fuentes de datos, las hace accesibles desde una sola capa y proporciona capacidades de trazabilidad para supervisar los cambios en los datos. En este webinar aprenderás a: - Acelerar la integración de datos provenientes de fuentes de datos fragmentados en los sistemas internos y externos y obtener una vista integral de la información. - Activar en toda la empresa una sola capa de acceso a los datos con medidas de protección. - Cómo la virtualización de datos proporciona los pilares para cumplir con las normativas actuales de protección de datos mediante auditoría, catálogo y seguridad de datos.

¿En qué se parece el Gobierno del Dato a un parque de atracciones?

Denodo

220209 nds

Kenji Hiramoto

Analyses and processing of big data in financial services

Fisnik Doko

ppt1.pptx

attalurilalitha

The typical perception of Big Data, Analytics, and Predicative/AI is that only the big companies can reap the benefits. Many believe they need a data warehouse, expensive reporting software, & an army of data scientists to get any value out of effort and cost. This session will explore and debunk that myth and showcase how companies of any size can participate. While there are many maturity models available, most are not designed to be practical guides to solving common business problems. Because of the explosion in cloud services, the barrier to entry has eroded significantly. We will look at some practical steps to access these capabilities and provide examples to where market-leading and growth companies have seen large benefits. Attendees will walk away with broader understanding of what’s possible to move their company through the journey in 2017. We will take a close look at IBM Watson solutions and how they integrate with IBM Collaboration and Social solutions.

MWLUG2017 - The Data & Analytics Journey 2.0

John Head

Big data

Dr. Wilfred Lin (Ph.D.)

Large-scale testing of new data products or enhancements to existing products in a research and development environment can be a technical challenge for data scientists. In some cases, tools available to data scientists lack production-level capacity, whereas other tools do not provide the algorithms needed to run the methodology. At Nielsen, the Databricks platform provided a solution to both of these challenges. This breakout session will cover a specific Nielsen business case where two methodology enhancements were developed and tested at large-scale using the Databricks platform. Development and large-scale testing of these enhancements would not have been possible using standard database tools.

How Nielsen Utilized Databricks for Large-Scale Research and Development with...

Spark Summit

Watch full webinar here: https://bit.ly/3lSwLyU En la era de la explosión de la información repartida en distintas fuentes, el gobierno de datos es un componente clave para garantizar la disponibilidad, usabilidad, integridad y seguridad de la información. Asimismo, el conjunto de procesos, roles y políticas que define permite que las organizaciones alcancen sus objetivos asegurando el uso eficiente de sus datos. La virtualización de datos forma parte de las herramientas estratégica para implementar y optimizar el gobierno de datos. Esta tecnología permite a las empresas crear una visión 360º de sus datos y establecer controles de seguridad y políticas de acceso sobre toda la infraestructura, independientemente del formato o de su ubicación. De ese modo, reúne múltiples fuentes de datos, las hace accesibles desde una sola capa y proporciona capacidades de trazabilidad para supervisar los cambios en los datos. Le invitamos a participar en este webinar para aprender: - Cómo acelerar la integración de datos provenientes de fuentes de datos fragmentados en los sistemas internos y externos y obtener una vista integral de la información. - Cómo activar en toda la empresa una sola capa de acceso a los datos con medidas de protección. - Cómo la virtualización de datos proporciona los pilares para cumplir con las normativas actuales de protección de datos mediante auditoría, catálogo y seguridad de datos.

Implementar una estrategia eficiente de gobierno y seguridad del dato con la ...

Denodo

mit data vr jan17

Patrick McCormick

Big data management

Soumya Soni

In:Confidence 2019 - A foundation for Insight in a data-rich world

Privitar

In order to deal with customers expecting a seamless omnichannel experience, increased regulations and speed with which innovative fin-techs enter the market, ING has formulated a customer centric strategy based on data and analytics. Last year we talked about the fact that ING developed a new architecture, the ING Data Lake. And how within ING In parallel the Big Data paradigm, based on Hadoop, appeared and how this was mapped on the Data Lake architecture to make sure Hadoop is leveraged to the maximum. This year we want to tell you how the international working group helped realizing the advanced analytic pattern on the ING private cloud, without prior management approval. This presentation will discuss the community strategy, how to stay under the radar, how to surface when actual content is strong enough to force change, open issues and the private cloud challenges ING is dealing with. Join us in this ride from community idea through architecture to private cloud implementation with some organizational challenges along the way.

ING's Customer-Centric Data Journey from Community Idea to Private Cloud Depl...

DataWorks Summit/Hadoop Summit

Australian open data presentation v2.0

Pia Waugh

Similaire à The importance of data (20)

BigData-Challenges.pptx

The Data & Analytics Journey – Why it’s more attainable for your company than...

Forget Big Data. It's All About Smart Data

Big data

Supporting Open Data Publishers

Converging your data landscape

¿En qué se parece el Gobierno del Dato a un parque de atracciones?

220209 nds

Analyses and processing of big data in financial services

ppt1.pptx

MWLUG2017 - The Data & Analytics Journey 2.0

Big data

How Nielsen Utilized Databricks for Large-Scale Research and Development with...

Implementar una estrategia eficiente de gobierno y seguridad del dato con la ...

mit data vr jan17

Big data management

In:Confidence 2019 - A foundation for Insight in a data-rich world

ING's Customer-Centric Data Journey from Community Idea to Private Cloud Depl...

Australian open data presentation v2.0

Plus de APNIC

APNIC Policy Roundup, presented by Sunny Chendi at the 5th ICANN APAC-TWNIC E...

APNIC

APNIC Updates presented by Paul Wilson at ARIN 53

APNIC

DDoS In Oceania and the Pacific, presented by Dave Phelan at NZNOG 2024

APNIC

'Future Evolution of the Internet' delivered by Geoff Huston at Everything Op...

APNIC

On Starlink, presented by Geoff Huston at NZNOG 2024

APNIC

Networking in the Penumbra presented by Geoff Huston at NZNOG

APNIC

IP addressing and IPv6, presented by Paul Wilson at IETF 119

APNIC

draft-harrison-sidrops-manifest-number-01, presented at IETF 119

APNIC

Making an RFC in Today's IETF, presented by Geoff Huston at IETF 119

APNIC

IPv6 Operational Issues (with DNS), presented by Geoff Huston at IETF 119

APNIC

Is DNS ready for IPv6, presented by Geoff Huston at IETF 119

APNIC

Benefits of doing Internet peering and running an Internet Exchange (IX) pres...

APNIC

APNIC Update and RIR Policies for ccTLDs, presented at APTLD 85

APNIC

NANOG 90: 'BGP in 2023' presented by Geoff Huston

APNIC

DNS-OARC 42: Is the DNS ready for IPv6? presentation by Geoff Huston

APNIC

APAN 57: APNIC Report at APAN 57, Bangkok, Thailand

APNIC

Lao Digital Week 2024: It's time to deploy IPv6

APNIC

AINTEC 2023: Networking in the Penumbra!

APNIC

CNIRC 2023: Global and Regional IPv6 Deployment 2023

APNIC

AFSIG 2023: APNIC Foundation and support for Internet development

APNIC

Plus de APNIC (20)