This document discusses big data and big geo data. It begins by defining big data and noting the challenges of collecting, managing, storing, searching, sharing, transferring, analyzing and visualizing large, complex datasets. It then discusses using big data as an opportunity rather than a threat by developing new ways to store and analyze diverse data to generate insights. Specific examples discussed include data used by Amazon, Obama's 2012 re-election campaign, meteorology, lidar data, and linked open data projects in the UK and Netherlands. The document raises potential applications of big data for the Dutch Cadastre, including data analysis, linking datasets, real-time access, multidimensional visualization and querying basic registrations.
Adatao Keynote Address @ UIUC Research Park Big-Data Summit, December 6, 2013
We were invited to give the Keynote address at the UIUC Research Park Big-Data Summit. We talked about (a) Why Big Data, (b) Big-Data Success Factors, and (c) The Future of Big Data. We also showed how Adatao approaches Big Data analysis for business users, via a beautiful, easy-to-use yet powerful, interactive web application.
Trends in Big Data & Business Challenges Experian_US
Join our #DataTalk on Thursdays at 5 p.m. ET. This week, we tweeted with Sushil Pramanick – who is the founder and president of the The Big Data Institute (TBDI).
You can learn about upcoming chats and see the archive of past big data tweetchats here
http://www.experian.com/blogs/news/about/datadriven
Watch talk ➟ http://bit.ly/1SGjeZD
For many companies, data science has an obvious connection to Marketing and Engineering. The analysis from data science can lead to marketing strategies that, for example, dramatically reduce customer churn or increase lifetime value, and Engineering is instrumental in capturing and storing the historical data for modeling. But what about Product?
In this talk, we’ll discuss the importance of integrating data and data science into your Product team at each stage — to drive a truly “data-driven product,” and in turn derive “product-driven data.” We’ll review examples of what happens when Data and Product work together, how it relates to the Lean Startup-inspired approach, and what happens when companies fail to bridge this gap.
Introduction to Big Data (non-technical) and the importance of Data Science to create meaning.
First of all we define Big Data in the light of the 3 Vs: volume, velocity and variety; next we move on to redefine Big Data, and we touch the topic of a data lake. We envision that Big Data will become mainstream for small organisations as well, what we can do with Big Data, how to tackle Big Data projects, what challenges lie ahead, but what opportunities are there to reap. And of course how important data science is to find the meaning in all the data.
Adatao Keynote Address @ UIUC Research Park Big-Data Summit, December 6, 2013
We were invited to give the Keynote address at the UIUC Research Park Big-Data Summit. We talked about (a) Why Big Data, (b) Big-Data Success Factors, and (c) The Future of Big Data. We also showed how Adatao approaches Big Data analysis for business users, via a beautiful, easy-to-use yet powerful, interactive web application.
Trends in Big Data & Business Challenges Experian_US
Join our #DataTalk on Thursdays at 5 p.m. ET. This week, we tweeted with Sushil Pramanick – who is the founder and president of the The Big Data Institute (TBDI).
You can learn about upcoming chats and see the archive of past big data tweetchats here
http://www.experian.com/blogs/news/about/datadriven
Watch talk ➟ http://bit.ly/1SGjeZD
For many companies, data science has an obvious connection to Marketing and Engineering. The analysis from data science can lead to marketing strategies that, for example, dramatically reduce customer churn or increase lifetime value, and Engineering is instrumental in capturing and storing the historical data for modeling. But what about Product?
In this talk, we’ll discuss the importance of integrating data and data science into your Product team at each stage — to drive a truly “data-driven product,” and in turn derive “product-driven data.” We’ll review examples of what happens when Data and Product work together, how it relates to the Lean Startup-inspired approach, and what happens when companies fail to bridge this gap.
Introduction to Big Data (non-technical) and the importance of Data Science to create meaning.
First of all we define Big Data in the light of the 3 Vs: volume, velocity and variety; next we move on to redefine Big Data, and we touch the topic of a data lake. We envision that Big Data will become mainstream for small organisations as well, what we can do with Big Data, how to tackle Big Data projects, what challenges lie ahead, but what opportunities are there to reap. And of course how important data science is to find the meaning in all the data.
Getting Ready For 3rd Generation Platform
Data Science Thailand Meetup#4
Asst. Prof. Dr. Jirapun Daengdej
Vincent Mary School of Science and Technology
Assumption University
jirapun@scitech.au.edu
My class presentation at USC. It gives an introduction about what is data science, machine learning, applications, recommendation system and infrastructure.
In this presentation, Wes Eldridge will provide a general overview on data science. The talk will cover a variety of topics, Wes will start with the dirty history of the field which will help add context. After learning about the history of data and data science Wes will discuss the common roles a data scientist holds in business and organizations. Next, he will talk about how to use data in your organization and products. Finally, he'll cover some tools to help you get started in data science. After the presentation, Wes will stick around for Q/A and data discussion.
Digital Mines ver 2.0 | 7 lessons on automation i learnt leading digital in...Coert Du Plessis (杜康)
My personal reflections on nearly 5 years of leading digital and then data at the world's largest miner; scale, business case, risks, and practical lessons
Content:
Introduction
What is Big Data?
Big Data facts
Three Characteristics of Big Data
Storing Big Data
THE STRUCTURE OF BIG DATA
WHY BIG DATA
HOW IS BIG DATA DIFFERENT?
BIG DATA SOURCES
BIG DATA ANALYTICS
TYPES OF TOOLS USED IN BIG-DATA
Application Of Big Data analytics
HOW BIG DATA IMPACTS ON IT
RISKS OF BIG DATA
BENEFITS OF BIG DATA
Future of big data
Big Data Information Architecture PowerPoint Presentation SlideSlideTeam
Feel enthralled by all the attention by our Big data information architecture PowerPoint presentation slide offers. While designing the perfect framework for a durable system, it could get tricky to represent all the data in a systematic manner. Manifesting complex ideas in a simplified manner doesn't always comes handy. That's the reason we have well-researched formats and designs for professional and prolonging solutions. Our team of experts makes sure that all the PPT slides are framed to work for the best of the client. Numerous icons and images are used here for visual engagement. We have covered up every viewpoint of data structure possible, including, data market forecast, financial aspects, social media approach and different comparisons used in data analysis for an out of box view. Our sole and intriguing PowerPoint slides are your gateway to progress and serves you in holding your viewer's consideration towards the concept of discernment and improves the quality and accuracy of the business processes. Discourage injudicious comments with our Big Data Information Architecture PowerPoint Presentation Slide. Ensure folks adhere to the decorum.
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.
Big Data Applications | Big Data Application Examples | Big Data Use Cases | ...Simplilearn
In this Big Data presentation, we will be discussing the Big data growth over the last few years followed by the various big data applications. We will look into the various sectors where big data is used such as weather forecast, healthcare, media and entertainment, logistics, travel & tourism and finally in the government & law enforcement sector.
We will be discussing how below industries are using Big Data presentation:
1. Weather forecast
2. Media and entertainment
3. Healthcare
4. Logistics
5. Travel n tourism
6. Government and law enforcement
What is this Big Data Hadoop training course about?
The Big Data Hadoop and Spark developer course have been designed to impart an in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab.
What are the course objectives?
This course will enable you to:
1. Understand the different components of Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark
2. Understand Hadoop Distributed File System (HDFS) and YARN as well as their architecture, and learn how to work with them for storage and resource management
3. Understand MapReduce and its characteristics, and assimilate some advanced MapReduce concepts
4. Get an overview of Sqoop and Flume and describe how to ingest data using them
5. Create database and tables in Hive and Impala, understand HBase, and use Hive and Impala for partitioning
6. Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution
7. Understand Flume, Flume architecture, sources, flume sinks, channels, and flume configurations
8. Understand HBase, its architecture, data storage, and working with HBase. You will also understand the difference between HBase and RDBMS
9. Gain a working knowledge of Pig and its components
10. Do functional programming in Spark
11. Understand resilient distribution datasets (RDD) in detail
12. Implement and build Spark applications
13. Gain an in-depth understanding of parallel processing in Spark and Spark RDD optimization techniques
14. Understand the common use-cases of Spark and the various interactive algorithms
15. Learn Spark SQL, creating, transforming, and querying Data frames
Learn more at https://www.simplilearn.com/big-data-and-analytics/big-data-and-hadoop-training
Challenging Problems for Scalable Mining of Heterogeneous Social and Informat...BigMine
In today’s interconnected real world, social and informational entities are interconnected, forming gigantic, interconnected, integrated social and information networks. By structuring these data objects into multiple types, such networks become semi-structured heterogeneous social and information networks. Most real world applications that handle big data, including interconnected social media and social networks, medical information systems, online e-commerce systems, or database systems, can be structured into typed, heterogeneous social and information networks. For example, in a medical care network, objects of multiple types, such as patients, doctors, diseases, medication, and links such as visits, diagnosis, and treatments are intertwined together, providing rich information and forming heterogeneous information networks. Effective analysis of large-scale heterogeneous social and information networks poses an interesting but critical challenge.
In this talk, we present a set of data mining scenarios in heterogeneous social and information networks and show that mining typed, heterogeneous networks is a new and promising research frontier in data mining research. However, such mining may raise some serious challenging problems on scalability computation. We identify a set of problems on scalable computation and calls for serious studies on such problems. This includes how to efficiently computation for (1) meta path-based similarity search, (2) rank-based clustering, (3) rank-based classification, (4) meta path-based link/relationship prediction, and (5) topical hierarchies from heterogeneous information networks. We introduce some recent efforts, discuss the trade-offs between query-independent pre-computation vs. query-dependent online computation, and point out some promising research directions.
Connexys verzorgde tijdens dit event de workshop Slimmer en Beter Werven waarbij ontwikkelingen van de arbeidsmarkt en ideeën en tips om invulling te geven aan het wervingsbeleid centraal stonden. Hierbij kun je denken aan het toepassen van nieuwe vormen van recruitment zoals het gebruik van sociale media en zoekmachine optimalisatie als onderdeel van de recruitmentstrategie. De deelnemers gingen ook nog eens interactief aan de slag en controleerden verschillende websites op Google vindbaarheid.
Jan van Goch, director marketing en sales, werd in zijn presentatie bijgestaan door Leon Willemsens van Netwerven. Hij verving de zieke Jeroen Kneppers van Detailresult.
Getting Ready For 3rd Generation Platform
Data Science Thailand Meetup#4
Asst. Prof. Dr. Jirapun Daengdej
Vincent Mary School of Science and Technology
Assumption University
jirapun@scitech.au.edu
My class presentation at USC. It gives an introduction about what is data science, machine learning, applications, recommendation system and infrastructure.
In this presentation, Wes Eldridge will provide a general overview on data science. The talk will cover a variety of topics, Wes will start with the dirty history of the field which will help add context. After learning about the history of data and data science Wes will discuss the common roles a data scientist holds in business and organizations. Next, he will talk about how to use data in your organization and products. Finally, he'll cover some tools to help you get started in data science. After the presentation, Wes will stick around for Q/A and data discussion.
Digital Mines ver 2.0 | 7 lessons on automation i learnt leading digital in...Coert Du Plessis (杜康)
My personal reflections on nearly 5 years of leading digital and then data at the world's largest miner; scale, business case, risks, and practical lessons
Content:
Introduction
What is Big Data?
Big Data facts
Three Characteristics of Big Data
Storing Big Data
THE STRUCTURE OF BIG DATA
WHY BIG DATA
HOW IS BIG DATA DIFFERENT?
BIG DATA SOURCES
BIG DATA ANALYTICS
TYPES OF TOOLS USED IN BIG-DATA
Application Of Big Data analytics
HOW BIG DATA IMPACTS ON IT
RISKS OF BIG DATA
BENEFITS OF BIG DATA
Future of big data
Big Data Information Architecture PowerPoint Presentation SlideSlideTeam
Feel enthralled by all the attention by our Big data information architecture PowerPoint presentation slide offers. While designing the perfect framework for a durable system, it could get tricky to represent all the data in a systematic manner. Manifesting complex ideas in a simplified manner doesn't always comes handy. That's the reason we have well-researched formats and designs for professional and prolonging solutions. Our team of experts makes sure that all the PPT slides are framed to work for the best of the client. Numerous icons and images are used here for visual engagement. We have covered up every viewpoint of data structure possible, including, data market forecast, financial aspects, social media approach and different comparisons used in data analysis for an out of box view. Our sole and intriguing PowerPoint slides are your gateway to progress and serves you in holding your viewer's consideration towards the concept of discernment and improves the quality and accuracy of the business processes. Discourage injudicious comments with our Big Data Information Architecture PowerPoint Presentation Slide. Ensure folks adhere to the decorum.
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.
Big Data Applications | Big Data Application Examples | Big Data Use Cases | ...Simplilearn
In this Big Data presentation, we will be discussing the Big data growth over the last few years followed by the various big data applications. We will look into the various sectors where big data is used such as weather forecast, healthcare, media and entertainment, logistics, travel & tourism and finally in the government & law enforcement sector.
We will be discussing how below industries are using Big Data presentation:
1. Weather forecast
2. Media and entertainment
3. Healthcare
4. Logistics
5. Travel n tourism
6. Government and law enforcement
What is this Big Data Hadoop training course about?
The Big Data Hadoop and Spark developer course have been designed to impart an in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab.
What are the course objectives?
This course will enable you to:
1. Understand the different components of Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark
2. Understand Hadoop Distributed File System (HDFS) and YARN as well as their architecture, and learn how to work with them for storage and resource management
3. Understand MapReduce and its characteristics, and assimilate some advanced MapReduce concepts
4. Get an overview of Sqoop and Flume and describe how to ingest data using them
5. Create database and tables in Hive and Impala, understand HBase, and use Hive and Impala for partitioning
6. Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution
7. Understand Flume, Flume architecture, sources, flume sinks, channels, and flume configurations
8. Understand HBase, its architecture, data storage, and working with HBase. You will also understand the difference between HBase and RDBMS
9. Gain a working knowledge of Pig and its components
10. Do functional programming in Spark
11. Understand resilient distribution datasets (RDD) in detail
12. Implement and build Spark applications
13. Gain an in-depth understanding of parallel processing in Spark and Spark RDD optimization techniques
14. Understand the common use-cases of Spark and the various interactive algorithms
15. Learn Spark SQL, creating, transforming, and querying Data frames
Learn more at https://www.simplilearn.com/big-data-and-analytics/big-data-and-hadoop-training
Challenging Problems for Scalable Mining of Heterogeneous Social and Informat...BigMine
In today’s interconnected real world, social and informational entities are interconnected, forming gigantic, interconnected, integrated social and information networks. By structuring these data objects into multiple types, such networks become semi-structured heterogeneous social and information networks. Most real world applications that handle big data, including interconnected social media and social networks, medical information systems, online e-commerce systems, or database systems, can be structured into typed, heterogeneous social and information networks. For example, in a medical care network, objects of multiple types, such as patients, doctors, diseases, medication, and links such as visits, diagnosis, and treatments are intertwined together, providing rich information and forming heterogeneous information networks. Effective analysis of large-scale heterogeneous social and information networks poses an interesting but critical challenge.
In this talk, we present a set of data mining scenarios in heterogeneous social and information networks and show that mining typed, heterogeneous networks is a new and promising research frontier in data mining research. However, such mining may raise some serious challenging problems on scalability computation. We identify a set of problems on scalable computation and calls for serious studies on such problems. This includes how to efficiently computation for (1) meta path-based similarity search, (2) rank-based clustering, (3) rank-based classification, (4) meta path-based link/relationship prediction, and (5) topical hierarchies from heterogeneous information networks. We introduce some recent efforts, discuss the trade-offs between query-independent pre-computation vs. query-dependent online computation, and point out some promising research directions.
Connexys verzorgde tijdens dit event de workshop Slimmer en Beter Werven waarbij ontwikkelingen van de arbeidsmarkt en ideeën en tips om invulling te geven aan het wervingsbeleid centraal stonden. Hierbij kun je denken aan het toepassen van nieuwe vormen van recruitment zoals het gebruik van sociale media en zoekmachine optimalisatie als onderdeel van de recruitmentstrategie. De deelnemers gingen ook nog eens interactief aan de slag en controleerden verschillende websites op Google vindbaarheid.
Jan van Goch, director marketing en sales, werd in zijn presentatie bijgestaan door Leon Willemsens van Netwerven. Hij verving de zieke Jeroen Kneppers van Detailresult.
The event program included the release of the 2015 GRESB Survey results and presentations on "Sustainability in Action" by Olaf Rutten, Commercial Clients Real Estate, ABN AMRO;
Bernardo Korenberg, Bouwinvest; Marieke van Kamp, Real Estate & Alternatives, NN Group; Rinus Vader, Leading Professional Asset & Facility Management, Royal Haskoning.
Kennisalliantie Nieuwjaarsreceptie 31 januari 2013:
Mark van Rijmenam MSc: "Big Data is nu net zo ver als het Internet was in 1993"
Ondernemer (bureau Kiura) en oprichter/blogger www.bigdata-startups.com
Presentation was held at the Meet-the-Press event, March 22nd 2013 in Hoofddorp The Netherlands. Presenters were Marcel Warmerdam from The METISfiles and Ruud Aleards from Keala Consulting
Kennisssessie Google Analytics | 2013 | Estate Internet tilburgTom Broekhoven
Deze kennissessie behandeld in het kort een aantal vragen die je als gebruiker van Google Analytics zou kunnen stellen ter ondersteuning van het betekenis geven aan je statistieken.
Hoe kan analytics je helpen?
- Wat wil je weten van bezoekers?
- Welke data helpt om inzicht te krijgen in gedrag en acties?
- Welke data helpt je beslissingen te nemen?
Wat levert analytics wel en wat niet:
- (Ordening van) ruwe data;
- Interpretatie en keuzes.
Van bezoekersstromen, verkeersbronnen, mobiele statistieken en plaats gegevens tot aan conversies en realtime gebeurtenissen.
Meetplan, implementatie en inrichting:
- Welk stappenplan volg je;
- Wat moet er worden gemetenl
- Wat dient er te worden gerapporteerd;
- Wat zijn de KPi's;
- Welke technische aanpassingen heb je nodig om alles door te meten.
Welke doelen zijn er:
- Verkopen;
- Leads genereren
- Informeren en ontzorgen
Wat je standaard niet kunt meten, maar je wel kunt implementeren:
- Doelen;
- Campagnes;
- Klikken op elementen zoals e-mail adressen en uitgaande links;
- E-commerce;
- Downloaden van bestanden;
- Sociale interactie;
- Eigen variabelen (bijv. is de gebruiker een man of vrouw).
Welke data wil je meten:
- Zijn rapporten wel zuiver (sluit je eigen organisatie uit/neem deze apart op)
- Gebruik extra profielen;
- Maak gebruik van filters.
Houd je rekening met:
- Aanpassingen werken nooit met terugwerkende kracht;
- Verwijderde informatie = en blijft verwijderd;
- Dat is niet exact en 100% betrouwbaar;
- Gebruik het programma voor trends.
Trends op het gebied van webanalytics:
- De cookiewetgeving;
- Live segmentatie
- Conversie attributie;
- Remarketing;
- Integratie van online/offline.
Summary of Multi Client study on Big Data in the Netherlands
combining end-user perceptions of medium and large organizations and vendor product/market strategies.
Beter onderbouwde business beslissingen en effectiever beleid dankzijn een strategie op basis van location analytics. Haal meer uit bedrijfsgegevens door de locatie beter te benutten. Geografische kaarten en analyses geven aanvullende inzichten, leggen verborgen patronen bloot en inspireren tot nieuwe en scherpere strategische keuzes.
Esri Maps for Office is add-on die een set geografische functionaliteit toevoegt aan Excel. Uniek, eenvoudig in gebruik maar krachtig in zijn uitkomsten.
Robert Dackus - Change in Real Estate | Masterclass Vastgoed 3.0 | www.vastgo...Roger
Op 9 februari 2011 vond de Masterclass Vastgoed 3.0 plaats, georganiseerd door Robert Dackus (3W Vastgoed) & Roger Heijsters (Smartcheck SME). Een bijeenkomst waar 40 vastgoedprofessionals hun ziel bloot gaven en zich openstelden voor een nieuwe toekomst aan de in zwaar weer verkerende vastgoedmarkt. Een zeer geslaagde dag met zeer inspirerende sprekers. Meer details op www.vastgoed30.com.
Info.nl organized a knowledge session on Big Data on August 9. In this presentation strategy director Iskander Smit introduces the Big Data developments.
Big Data Expo 2015 - Doorbraakproject Big DataBigDataExpo
Big data komt in vele vormen en maten en biedt een breed scala aan mogelijkheden, zoals het categoriseren van alle vacatures van alle websites waar ook en het voorspellen van product-populariteit door sentimentanalyse van Twitterberichten. Door de snelle vooruitgang van mogelijkheden voor data opslag en analyse komen Big Data toepassingen in het bereik van kleinere bedrijven. Open data, cloud opslag, open source software en crowdsourcing dragen daar aan bij.
Is het iets voor jou? Hoe pak je dat aan? Waar begin je? Wie kunnen helpen? Eric van Tol neemt je mee in de eerste stappen naar een succesvolle big data business case.
Marketing wordt data! Door Big Data kunnen we veel meer intelligentie toevoegen aan marketing. Denk aan profiling, personalisatie en verbetering advertising. Arjan Burger gaat hier tijdens het webinar dieper op in. Meer info: http://eduvision.nl of http://eduvision.be
Gartner webinar social media analytics 23.10.2014Irene Ventayol
Virtually every modern marketer has a presence in social channels, and many use social listening tools to monitor what people say about their brands. Yet despite being a maturing discipline, social analytics remains stubbornly difficult and frustrating to apply. How much is a Facebook fan worth? Does it matter that your "net sentiment" is in the single digits? Your "share of voice" on Twitter is down this week – should you panic? This presentation focuses on the social analytics vendors, techniques, metrics and cases that can help you most.
Big data is a term that describes the large volume of data may be both structured and unstructured.
That inundates a business on a day-to-day basis. But it’s not the amount of data that’s important. It’s what organizations do with the data that matters.
The success of an organization increasingly depends on their ability to draw conclusions regarding the various types of data available. Staying ahead of competitors requires many times to identify a trend, problem or opportunity microseconds before anyone else. That's why organizations must be able to analyze this information if they want to find insights that will help them to identify new opportunities underlying this phenomenon.
People are spontaneously uploading large amounts of information on the internet and this represents a great opportunity for companies to segment according to their behavior and not only socio-demographic factors. Companies store transactional information from their customers by making them fill in forms but the challenge for brands is to enrich these databases with information describing their customer’s behavior and daily habits. This info can be obtained through the online conversation and can be processed, crossed and enriched with many other types of information through different models based on Big Data. Following this procedure, we can complement the information we already have from our customers without having to ask them directly and therefor providing more value-added proposals to clients from a brand perspective.
Using the same technology with the right platform and the correct tactic, companies can achieve more ambitious goals that provide valuable information for the brand, which in turn could also enrich the customer’s experience, improving the customer journey for all types of clients.
less
Big Data has recently gained relevance because companies are realizing what it can do for them and that it is a gold mine for finding competitive advantages. Proximity’s Juan Manuel Ramírez, Director of Strategy and...
Presentation: Big Data 101, What It Means for Business
Presented by: David Ray, Corporate Vice President, Corporate Internet, New York Life Insurance Company
Big Data is the latest buzzword inside the C-suite, but what does it mean, how are other industries using it to competitive advantage, and what are the real opportunities for business? Does big data require massive amounts of data to be considered or is there success to be found in unifying myriad data sources? Join us for an interesting peek.
www.bdionline.com
The REAL Impact of Big Data on PrivacyClaudiu Popa
The awesome promise of Big Data is tempered by the need to protect personal information. Data scientists must expertly navigate the legislative waters and acquire the skills to protect privacy and security. This talk provides enterprise leaders with answers and suggests questions to ask when the time comes to consider the vast opportunities offered by big data.
Abstract:
Big Data concern large-volume, complex, growing data sets with multiple, autonomous sources. With the fast development of networking, data storage, and the data collection capacity, Big Data are now rapidly expanding in all science and engineering domains, including physical, biological and biomedical sciences. This paper presents a HACE theorem that characterizes the features of the Big Data revolution, and proposes a Big Data processing model, from the data mining perspective. This data-driven model involves demand-driven aggregation of information sources, mining and analysis, user interest modeling, and security and privacy considerations. We analyze the challenging issues in the data-driven model and also in the Big Data revolution.
Data-Ed Webinar: Demystifying Big Data DATAVERSITY
We are in the middle of a data flood and we need to figure out how to tame it without drowning. Most of what has been written about Big Data is focused on selling hardware and services. But what about a Big Data Strategy that guides hardware and software decisions? While virtually every major organization is faced with the challenge of figuring out the approach for and the requirements of this new development, jumping into the fray hastily and unprepared will only reproduce the same dismal IT project results as previously experienced. Join Dr. Peter Aiken as he will debunk a number of misconceptions about Big Data as your un-typical IT project. He will provide guidance on how to establish realistic Big Data management plans and expectations, and help demonstrate the value of such actions to both internal and external decision makers without getting lost in the hype.
Takeaways:
- The means by which Big Data techniques can complement existing data management practices
- The prototyping nature of practicing Big Data techniques
- The distinct ways in which utilizing Big Data can generate business value
- Bigger Data isn’t always Better Data
Similar to Big Data - Introduction and Research Topics - for Dutch Kadaster (20)
Slides originally used in interview by Jonna on De Grote Geo Show, a live-streaming webshow by OSGeo.nl. Aired on oct 1, 2020. Video is on YouTube: https://www.youtube.com/watch?v=3l_a5Up8Rgc
Later adapted/expanded for general online interviews.
THIS IS VERSION 2 AND CURRENT, on SlideShare! Version 1 is still on SlideShare as it is linked...
Some highlights of my professional career.
PLEASE SEE VERSION 2 FOR CURRENT
Slides originally used in interview by Jonna on De Grote Geo Show, a live-streaming webshow by OSGeo.nl. Aired on oct 1, 2020. Video is on YouTube: https://www.youtube.com/watch?v=3l_a5Up8Rgc
Later adapted/expanded for general online interviews.
Some highlights of my professional career.
Presentation on Open Sensor Networks, Smart Emission, SensorThings API, TheThingsNetwork,
@pycomIOT
etc. Presented at SenseMakersAms Meetup: https://meetup.com/sensemakersams/events/pwflgryzmbxb/
Presentation at LoRaWAN TheThingsNetwork makers event (make a Pet-Tracker with LoRa) organized by Ruimteschepper at Warehouse of Innovation Eindhoven (also home to IoT Eindhoven Meetup Group). Summarizes Smart Emission architecture, thoughts on tech for Spatio-Temporal Data, Internet of Things sorry Internet of Silos. Ending with a demo on LoRaWAN TheThingsNetwork integration with the OGC SensorThings API using MQTT Bridging.
Presentation provided at "Geo Gebruikersfestival", okt 31, 2018, Amersfoort, The Netherlands. Sketches how from several Sensor projects the Smart Emission Platform emerged and migrated to the PDOK Platform. How a next step could be be a Dutch national Sensor SDI asa a federated/distributed architecture. Special attention is given to APIs, in particular the SensorThings API.
Opening by me as Chair OSGeo.nl Foundation, the Dutch Local Chapter of OSGeo.org at FOSS4GNL Conference on July 11, 2018 at Aeres Highschool, Almere, the Netherlands.
Introduces the Stetl (Streaming ETL) spatial ETL framework and its application in specific cases: Dutch National GML Dataset to PostGIS conversion and its use in the Smart Emission SensorWeb Platform. Stetl is written in Python and Open Source (GNU GPL), utilizing powerful libs like GDAl/OGR, libxml2, libxslt and Jinja2 templating.
Opening words by Just van den Broecke - Chair of OSGeo.nl Foundation, the Dutch local Chapter of OSGeo.org on joint OSGeo.nl OpenStreetMap NL NJ Party in cafe Dudok Hilversum. Review of OSGeo.nl Events in 2017 and upcoming events in 2018, also international events.
Slides used at the opening of the OSGeo.nl Day on nov 22, 2017 at GeoBuzz in Den Bosch, The Netherlands. Note the new designs of OSGeo localized for OSGeo.nl.
Presented together with Jan-Willem van Aalst and Frank Steggink at the Dutch CartoDay, March 15, 2017. See full program here: http://www.cartodag.nl/programma-cartodag-2017. Subject was how to eventually create online topographical maps from Open but Raw datasets: how to transform (ETL), create maps (QGIS), and publish on the web using Open Source service components like MapServer and MapProxy via http://map5.nl
Abstract in Dutch:
Om bruikbare kaarten te maken is tegenwoordig veel goede open geodata beschikbaar. Maar wat komt er allemaal bij kijken om dat zo praktisch mogelijk te doen? Deze sessie neemt je mee in de levenscyclus van open geodata met tooling zoals NLExtract , GDAL en QGIS . Een greep uit wat er langs komt in dit uur: het maken van PostGIS databases uit PDOK data; het maken van hillshading (reliëfschaduw) uit de AHN2/3; het maken van de OpenTopo kaartbeelden uit combinaties van PDOK bestanden; en het tegelen en opnieuw publiceren van allerlei kaartproducten, bijvoorbeeld op map5.nl .
5 minute pitch held at GeoBuzz 2016 Den Bosch for the OGT Award (which we received in Category "Developers"!). It introduces NLExtract, a toolset to convert Dutch National Open Geodata sets to manageable formats such as PostGIS.
Slides presented by me on behalf of Geonovum and the project on the Geospatial Sensor Webs conference 2016 organized by 52North in Münster, Germany:
http://52north.org/about/other-activities/geospatial-sensor-webs-conference
The slides give an overview of the Smart Emission project with a focus on the data infrastructure, data management (ETL) and providing access to sensor data via OGC-standards (SOS, WMS, WFS, STA).
Explains basics of Stetl, an Open Source spatial ETL framework. More on http://stetl.org. Talk given on GeoPython conference, June 24, 2016, Basel, Switserland.
High-level presentation on the Data-infastructure for project-team and participating citizens at Radboud Univeristy Nijmegen, may 26, 2016 for the Smart Emission project: "Het Smart Emission project draait om het in kaart brengen van luchtkwaliteit, geluid, trillingen en meteorologische indicatoren in de stad op een fijnmazig schaalniveau, door inwoners met zogenoemde burger-sensor-netwerken." (Bron: http://smartemission.nl). Project partners: Radboud Universiteit, Gemeente Nijmegen, Rijksinstituut voor Volksgezondheid en Milieu (RIVM), Geonovum, Intemo, CityGIS and offcourse Nijmegen citizens.
Presentation given at the OSGeo.nl Day http://osgeo.nl at GeoBuzz Conference on nov 25, 2015. Overview of NLExtract and in particular ETL (conversion) for BAG, the open geo-dataset for Dutch Addresses and Buildings.
Slides I presented at the Dutch "Doorbraak 3D - Trekkersoverleg" ( 3D Breakthrough Representatives Meetup) at Geonovum, sept 3, 2015. Trying to provide an overview of 3D Open Standards efforts and suggestions for future actions/pilots with some of the CesiumJS-based tiling standards using Dutch public open base registry data ("Basis Registraties").
Eng: originally planned as a talk/workshop on hiking with GPS, but evolving into a wider talk about the evolution of navigation and Natural Navigation techniques.
See also the main website: http://gps.justobjects.nl.
Below Dutch:
Plaatsbepaling en navigatie is iets van alle tijden. Zij is mee-geëvolueerd met de mensheid. Vandaag de dag doen we navigatie met GPS via bijv “De TomTom” of steeds vaker via onze Smartphone. We dreigen daarmee echter belangrijke vaardigheden te verliezen zoals kaartlezen en het gebruik van kompas. Maar deze laatste twee middelen waren ook weer een stap in de lange evolutie van Navigatie. Zoals de meesten van jullie weten heb ik veel interesse in de evolutie van de mensheid. In die context heb ik de laatste tijd nagedacht hoe navigatie zich heeft ontwikkeld. Ik zal dit praatje chronologisch opbouwen. Dan komen we vanzelf uit bij "Wandelen met de GPS" waar de nadruk op gaat liggen deze middag.
Highlights and achievements in 2014 from the OSGeo.nl, the Dutch-speaking Local Chapter of the Open Source Geospatial Foundation, OSGeo.org. Presented jan 11 2015 by Gert-Jan and Just at the OSGeo.nl/OpenStreetMap NL new years party. See more presentations from that meeting on our website: http://osgeo.nl
My talk on the OSGeo.nl Day 2014 on nov 25, 2014, Den Bosch. This event was organized by the OSGeo.nl, the Dutch Language Chapter of OSGeo.org and embedded in the GeoBuzz conference. Main subject is how to transform and visualize (unlock) Dutch Open Geo-datasets using open source tools like NLExtract (http://nlextract.nl), Stetl (http://www.stetl.org). In particular, there is a last minute addition on unlocking 3D data, Top10NL3D, using CesiumJS (http://www.cesiumjs.org) , an Open Source browser/WebGL-based 3D visualization framework ala Google Earth (but open and without plugins). The 3D part of this talk was also given the same day at the "3D Doorbraak" workshop (Jantien Stoter et al).
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4. Big Data Onderzoek
Wat is Big Data?
4
Big data is the term for a collection of
data sets so large and complex that it
becomes difficult to process using
on-hand database management tools
or traditional data processing
applications. http://en.wikipedia.org/wiki/Big_data
6. Big Data Onderzoek
Opportunity or Threat?
6
The opportunity of big data is also its challenge. We are drowning
in data, and tweets, posts and video are not the structured data
that fits well into relational databases for traditional querying. As
a result, big data simply requires a new way of thinking about
how to store and analyze data to accommodate these new
realities and turn insights into actionable decisions.
http://www.greenbookblog.org/2012/03/21/big-data-opportunity-or-threat-for-market-research
7. Big Data Onderzoek
Gartner 2012 - 3V’s
7
Big data is high volume, high velocity,
and/or high variety information assets that
require new forms of processing to enable
enhanced decision making, insight
discovery and process optimization.
8. Big Data Onderzoek
Actually 4thV...
8
Veracity: Professional managers are wary of
unverified data. Since much of the data deluge
comes from anonymous and unverified sources, it
is necessary to establish and flag the quality of the
data before it is included in any ensemble.
www.geospatialworld.net
9. Big Data Onderzoek
Gartner 2013 - Not Just 3V’s
1. 3Vs
Volume, Velocity, Variety
2. Cost-Effective, Innovative Forms of Information Processing
viz. technologies for storing, linking and analysis
3. Enhanced Insight and Decision Making
“...the ultimate goal. Business value is in the insights, which were not available before...”
9
http://www.forbes.com/sites/gartnergroup/2013/03/27/gartners-big-data-definition-consists-of-three-parts-not-to-be-confused-with-three-vs
Three Parts
13. Big Data Onderzoek
Use Cases
13
http://www-01.ibm.com/software/data/bigdata/use-cases.html
14. Big Data Onderzoek
Case - Obama Re-election
14
http://rasiej.com/news/2013/1/15/big-data-helped-obama-win-the-election
15. Big Data Onderzoek15
Inside the Secret World of the Data Crunchers Who Helped Obama Win
http://swampland.time.com/2012/11/07/inside-the-secret-world-of-quants-and-data-crunchers-who-helped-obama-win/
18. Big Data Onderzoek
Amazon - Case 1
18
Amazon pioneered the use of big data analytics in
e-commerce, web personalization, multivariate
testing of product offerings, and inference engines
to predict consumer preferences.
http://www.citeworld.com/business/22263/bezos-post-big-data
19. Big Data Onderzoek
Amazon - Case 1 + others
19
http://www.business2community.com/infographics/amazon-netflix-and-twitter-put-big-data-to-good-use-0574652
23. Big Data Onderzoek
New?
23
Geospatial Data has always been Big
Data. Now Big Data Analytics for
geospatial data is available to allow
users to analyze massive volumes of
geospatial data.
http://www.opengeospatial.org/blog/1866
24. Big Data Onderzoek
Big Data in Geographic Information Science Panel 2012
24
Big Data is not only big because it involves a huge amount of
data, but also because of the high-dimensionality and inter-
linkage of the involved data sets. The on-the-fly integration of
heterogeneous data from various sources has been named
one of the frontiers of Digital Earth research, Bioinformatics, the
Digital Humanities, and other emerging research visions.
http://stko.geog.ucsb.edu/bigdatagiscience2012