1) How to think in the age of Dataism with LEO CDP ?
2) Why is Dataism for human, business and society ?
3) How should LEO Customer Data Platform (LEO CDP) work ?
4) How to use LEO CDP for your business ?
Data collection, processing & organization with USPA frameworkTrieu Nguyen
1) How to think in the age of Dataism with USPA framework ?
2) How to collect customer data
3) Data Segmentation Processing for flexibility and scalability
4) Data Organization for personalization and business activation
[Notes] Customer 360 Analytics with LEO CDPTrieu Nguyen
Part 1: Why should every business need to deploy a CDP ?
1. Big data is the reality of business today
2. What are technologies to manage customer data ?
3. The rise of first-party data and new technologies for Digital Marketing
4. How to apply USPA mindset to build your CDP for data-driven business
Part 2: How to use LEO CDP for your business
1. Core functions of LEO CDP for marketers and IT managers
2. Data Unification for Customer 360 Analytics
3. Data Segmentation
4. Customer Personalization
5. Customer Data Activation
Part 3: Case study in O2O Retail and Ecommerce
1. How to build customer journey map for ecommerce and retail
2. How to do customer analytics to find ideal customer profiles
The ideal customer profile in a B2B context
The ideal customer profile in a B2C context
3. Manage product catalog for customer personalization
4. Monitoring Data of Customer Experience (CX Analytics)
CX Data Flow
CX Rating plugin is embedded in the website, to collect feedback data
An overview of CX Report
A CX Report in a customer profile
5. Monitoring data with real-time event tracking reports
Event Data Flow
Summary Event Data Report
Event Data Report in a Customer Profile
Part 4: How to setup an instance of LEO CDP for free
1. Technical architecture
2. Server infrastructure
3. Setup middlewares: Nginx, ArangoDB, Redis, Java and Python
Network requirements
Software requirements for new server
ArangoDB
Nginx Proxy
SSL for Nginx Server
Java 8 JVM
Redis
Install Notes for Linux Server
Clone binary code for new server
Set DNS hosts for LEO CDP workers
4. Setup data for testing and system verification
Part 5: Summary all key ideas
Part 1: Introduction to digital marketing technologyTrieu Nguyen
Outline of this course
1. Digital Media Models in the age of marketing 4.0
2. Strategic Thought as It Relates to Digital Marketing
3. Web: The Center of Digital Marketing Delivery Mix
4. Content Management System (CMS) and headless CMS
5. Search Engine Marketing
6. Email Marketing
7. Social Media and Mobile Marketing
8. Introduction to Advertising Technology (Ad Tech)
9. Introduction to Customer Database and Customer Data Platform (CDP)
10. Legal Issues: Data privacy, Security, and Intellectual Property
11. Case study: IKEA - from business strategy to digital marketing strategy
12. Recommended books for self-study
Transform your marketing and sales capabilities with Big Data and A.I
1) Why is Customer Data Platform (CDP) ?
Case study: Enhancing the revenue of your restaurant with CDP and mobile app marketing
Question: Why can CDP disrupt business model for restaurant industry (B2C) ?
2) How would CDP work in practice ?
Introducing USPA.tech as logical framework for implementing CDP in practice
How Can a Customer Data Platform Enhance Your Account-Based Marketing Strategy (B2B) ?
3) How can we implement CDP for business?
Introducing the CDP as customer-first marketing platform for all industries (my key idea in this slide)
I gave a talk at North California Business Marketing Association on Customer Data Platform with examples ranging from Uber Grayballing to Zoom's customer retention email and "dogs or muffins".
Data collection, processing & organization with USPA frameworkTrieu Nguyen
1) How to think in the age of Dataism with USPA framework ?
2) How to collect customer data
3) Data Segmentation Processing for flexibility and scalability
4) Data Organization for personalization and business activation
[Notes] Customer 360 Analytics with LEO CDPTrieu Nguyen
Part 1: Why should every business need to deploy a CDP ?
1. Big data is the reality of business today
2. What are technologies to manage customer data ?
3. The rise of first-party data and new technologies for Digital Marketing
4. How to apply USPA mindset to build your CDP for data-driven business
Part 2: How to use LEO CDP for your business
1. Core functions of LEO CDP for marketers and IT managers
2. Data Unification for Customer 360 Analytics
3. Data Segmentation
4. Customer Personalization
5. Customer Data Activation
Part 3: Case study in O2O Retail and Ecommerce
1. How to build customer journey map for ecommerce and retail
2. How to do customer analytics to find ideal customer profiles
The ideal customer profile in a B2B context
The ideal customer profile in a B2C context
3. Manage product catalog for customer personalization
4. Monitoring Data of Customer Experience (CX Analytics)
CX Data Flow
CX Rating plugin is embedded in the website, to collect feedback data
An overview of CX Report
A CX Report in a customer profile
5. Monitoring data with real-time event tracking reports
Event Data Flow
Summary Event Data Report
Event Data Report in a Customer Profile
Part 4: How to setup an instance of LEO CDP for free
1. Technical architecture
2. Server infrastructure
3. Setup middlewares: Nginx, ArangoDB, Redis, Java and Python
Network requirements
Software requirements for new server
ArangoDB
Nginx Proxy
SSL for Nginx Server
Java 8 JVM
Redis
Install Notes for Linux Server
Clone binary code for new server
Set DNS hosts for LEO CDP workers
4. Setup data for testing and system verification
Part 5: Summary all key ideas
Part 1: Introduction to digital marketing technologyTrieu Nguyen
Outline of this course
1. Digital Media Models in the age of marketing 4.0
2. Strategic Thought as It Relates to Digital Marketing
3. Web: The Center of Digital Marketing Delivery Mix
4. Content Management System (CMS) and headless CMS
5. Search Engine Marketing
6. Email Marketing
7. Social Media and Mobile Marketing
8. Introduction to Advertising Technology (Ad Tech)
9. Introduction to Customer Database and Customer Data Platform (CDP)
10. Legal Issues: Data privacy, Security, and Intellectual Property
11. Case study: IKEA - from business strategy to digital marketing strategy
12. Recommended books for self-study
Transform your marketing and sales capabilities with Big Data and A.I
1) Why is Customer Data Platform (CDP) ?
Case study: Enhancing the revenue of your restaurant with CDP and mobile app marketing
Question: Why can CDP disrupt business model for restaurant industry (B2C) ?
2) How would CDP work in practice ?
Introducing USPA.tech as logical framework for implementing CDP in practice
How Can a Customer Data Platform Enhance Your Account-Based Marketing Strategy (B2B) ?
3) How can we implement CDP for business?
Introducing the CDP as customer-first marketing platform for all industries (my key idea in this slide)
I gave a talk at North California Business Marketing Association on Customer Data Platform with examples ranging from Uber Grayballing to Zoom's customer retention email and "dogs or muffins".
Gartner named customer data platforms (CDPs) one of the key technologies that will demand marketers’ attention in 2018. Michael Katz, Cofounder and CEO of mParticle, explains why CDPs are not just another acronym and how consumer brands ranging from Airbnb to NBCUniversal to Zappos are using them to optimize omnichannel customer experiences and marketing outcomes, in all the moments that matter.
Originally presented at AdExchanger Industry Preview 2018 by Michael Katz, Cofounder and CEO, mParticle.
Concepts, use cases and principles to build big data systems (1)Trieu Nguyen
1) Introduction to the key Big Data concepts
1.1 The Origins of Big Data
1.2 What is Big Data ?
1.3 Why is Big Data So Important ?
1.4 How Is Big Data Used In Practice ?
2) Introduction to the key principles of Big Data Systems
2.1 How to design Data Pipeline in 6 steps
2.2 Using Lambda Architecture for big data processing
3) Practical case study : Chat bot with Video Recommendation Engine
4) FAQ for student
Video Ecosystem and some ideas about video big dataTrieu Nguyen
Introduction to Video Ecosystem Mind Map
Video Streaming Platform
Video Ad Tech Platform
Video Player Platform
Video Content Distribution Platform
Video Analytics Platform
Summary of key ideas
Q & A
Ad Week Europe, B2B Forum- The Future of B2B: The Rise of the Data-Driven, Cu...LinkedIn Europe
Russell Glass-Head of Marketing Products at LinkedIn presentation deck from the LinkedIn B2B Forum, March 24th 2015 at the Hamyard Hotel as part of Advertising Week Europe.
Why Do Banks Need A Customer Data Platform?Lemnisk
Banks traditionally have been known to amass customer information across both online and offline data channels. However, a lot of this data resides in silos and marketers have been unable to leverage this data to run targeted marketing campaigns. Here are the top four reasons why a Customer Data Platform would be best suited for Banks.
[Webinar] The Best Kept Marketing Secret to Achieving Complete Customer ViewsTealium
There’s no question that Customer Data Platforms are changing the way organizations engage with their customers. Truth be told, if this tool is missing from your martech stack, you’re probably missing out on crucial customer insights.
That’s why in the first webinar in our Guide to CDP Success series, Director of Product Marketing, Matt Parisi, explained how a CDP can be your greatest competitive advantage. We covered topics like:
- See how you can create dynamic customer identities for better segmentation
- Discover how a CDP provides your entire tech stack with unified data in real time
- Understand why this technology is critical to your current and future success
You can view the on-demand session on our website in our Resource Hub
As the MarTech space gets more and more crowded we often find we don’t use our existing tools to their full potential. We end up with products that don’t always live up to all the hype we were promised. Find out how to enhance the tools you already have without having to replace them. See how two of Australia’s biggest corporates utilised a Customer Data Platform (CDP) to access data that’s always seemed too far out of reach and supercharged the tools they already had.
TechConnectr's Big Data Connection. Digital Marketing KPIs, Targeting, Analy...Bob Samuels
This presentation was given at the Deep Dive Conference in November. 2013.
Big Data Applications... example, digital marketing, and targeting and optimization...
Feedback, and additional perspectives, is appreciated.
Thank you,
Bobby Samuels
TechConnectr.com
Teradata Integrated Web Intelligence captures detailed data from online behavior and integrates it with other interactive channels and enterprise data to turn your Enterprise Data Warehouse from Teradata into a powerful marketing tool. Now you can combine online data with traditional offline data in a single location to gain insights into customer behavior that increase the effectiveness and efficiency of your marketing spend across all channels.
For more information, visit www.teradata.com
The Cloud Analytics Reference Architecture: Harnessing Big Data to Solve Comp...Booz Allen Hamilton
Booz Allen’s Cloud Analytics Reference Architecture is an entirely new approach for the implementation of big data in the digital enterprise - a way of using technology, machine-based analytics, and human-powered analysis to create competitive and mission advantage.
Andreas Grasel & Thorsten Feldhege (Adform) Wir haben eine DMP - Was nun? - P...e-dialog GmbH
Nach der positiven Entscheidung zum Einsatz einer eigenen DMP stellt sich die Frage nach dem Vorhandensein einer nachhaltigen Datenstrategie. Wir zeigen die vier relevanten Eckpunkte dazu auf: Collection, Hierarchy, Management, Activation
A vision for sustainable analytics implementations - Superweek 2020Jente De Ridder
Marketing automation, machine learning models, customer data platforms; at least one of these is included in your company’s ambitions for 2020. But is you analytics implementation prepared for it? Many companies struggle to implement ambitious data projects because of a lack of data standards and ownership, specialy in the digital analytics sphere.
We introduce the GDDL, a digital data layer framework developed by Stitchd but available as open source solution for everyone that is looking for a sustainable approach to a data layer implementation.
Presentation held at Superweek conference, Hungary, January 2020.
Siamac Alexander Rahnavard (Echte Liebe) Programmatic Creativity - Programmat...e-dialog GmbH
Programmatic Marketing bietet Werbetreibenden neue Möglichkeiten der kreativen Ansprache. Neben eigenen First Party Daten können Advertiser event- oder situationsbezogene, aber auch interessensbasierte Daten wie Kaufabsichten für eine gezieltere Werbeansprache mit einbeziehen. Programmatic Creativity ist dabei wesentlicher Kerne einer ganzheitlich gedachten programmatischen Strategie, da sie maßgeblich zur Erreichung des Users zur richtigen Zeit am richtigen Ort beiträgt. Programmatic Creativity geht dabei weit über den rein technischen Mediaeinkauf hinaus.
Everybody talks about Digital Transformation and Digital Disruption and the impact on Marketing. Marketing needs to find new ways to interact, sure. But do digital transformation of marketing and digital marketing even exist? Not sure! Whatever, you still need to get ready for new technologies like Voice. And you should do it fast.
Thorsten Sachtje (Senior Consultant Digital Strategy @ metapeople - Part of Artefact) held this presentation as part of a 1,5 hour lecture to Marketing Management BSc students of Ruhr University Bochum (Germany) on June 7th, 2018.
B2B marketing can be very different from B2C. The buying process is more complex and requires expertise and targeted audiences. LinkedIn is uniquely positioned to help your agency succeed in the B2B marketing space.
In this presentation, Aishwarya introduces SMAC and associated trends. Aishwarya's interest areas lies in data mining to find out "Why a customer buys a certain product" which will help business in making better product decisions.
Gartner named customer data platforms (CDPs) one of the key technologies that will demand marketers’ attention in 2018. Michael Katz, Cofounder and CEO of mParticle, explains why CDPs are not just another acronym and how consumer brands ranging from Airbnb to NBCUniversal to Zappos are using them to optimize omnichannel customer experiences and marketing outcomes, in all the moments that matter.
Originally presented at AdExchanger Industry Preview 2018 by Michael Katz, Cofounder and CEO, mParticle.
Concepts, use cases and principles to build big data systems (1)Trieu Nguyen
1) Introduction to the key Big Data concepts
1.1 The Origins of Big Data
1.2 What is Big Data ?
1.3 Why is Big Data So Important ?
1.4 How Is Big Data Used In Practice ?
2) Introduction to the key principles of Big Data Systems
2.1 How to design Data Pipeline in 6 steps
2.2 Using Lambda Architecture for big data processing
3) Practical case study : Chat bot with Video Recommendation Engine
4) FAQ for student
Video Ecosystem and some ideas about video big dataTrieu Nguyen
Introduction to Video Ecosystem Mind Map
Video Streaming Platform
Video Ad Tech Platform
Video Player Platform
Video Content Distribution Platform
Video Analytics Platform
Summary of key ideas
Q & A
Ad Week Europe, B2B Forum- The Future of B2B: The Rise of the Data-Driven, Cu...LinkedIn Europe
Russell Glass-Head of Marketing Products at LinkedIn presentation deck from the LinkedIn B2B Forum, March 24th 2015 at the Hamyard Hotel as part of Advertising Week Europe.
Why Do Banks Need A Customer Data Platform?Lemnisk
Banks traditionally have been known to amass customer information across both online and offline data channels. However, a lot of this data resides in silos and marketers have been unable to leverage this data to run targeted marketing campaigns. Here are the top four reasons why a Customer Data Platform would be best suited for Banks.
[Webinar] The Best Kept Marketing Secret to Achieving Complete Customer ViewsTealium
There’s no question that Customer Data Platforms are changing the way organizations engage with their customers. Truth be told, if this tool is missing from your martech stack, you’re probably missing out on crucial customer insights.
That’s why in the first webinar in our Guide to CDP Success series, Director of Product Marketing, Matt Parisi, explained how a CDP can be your greatest competitive advantage. We covered topics like:
- See how you can create dynamic customer identities for better segmentation
- Discover how a CDP provides your entire tech stack with unified data in real time
- Understand why this technology is critical to your current and future success
You can view the on-demand session on our website in our Resource Hub
As the MarTech space gets more and more crowded we often find we don’t use our existing tools to their full potential. We end up with products that don’t always live up to all the hype we were promised. Find out how to enhance the tools you already have without having to replace them. See how two of Australia’s biggest corporates utilised a Customer Data Platform (CDP) to access data that’s always seemed too far out of reach and supercharged the tools they already had.
TechConnectr's Big Data Connection. Digital Marketing KPIs, Targeting, Analy...Bob Samuels
This presentation was given at the Deep Dive Conference in November. 2013.
Big Data Applications... example, digital marketing, and targeting and optimization...
Feedback, and additional perspectives, is appreciated.
Thank you,
Bobby Samuels
TechConnectr.com
Teradata Integrated Web Intelligence captures detailed data from online behavior and integrates it with other interactive channels and enterprise data to turn your Enterprise Data Warehouse from Teradata into a powerful marketing tool. Now you can combine online data with traditional offline data in a single location to gain insights into customer behavior that increase the effectiveness and efficiency of your marketing spend across all channels.
For more information, visit www.teradata.com
The Cloud Analytics Reference Architecture: Harnessing Big Data to Solve Comp...Booz Allen Hamilton
Booz Allen’s Cloud Analytics Reference Architecture is an entirely new approach for the implementation of big data in the digital enterprise - a way of using technology, machine-based analytics, and human-powered analysis to create competitive and mission advantage.
Andreas Grasel & Thorsten Feldhege (Adform) Wir haben eine DMP - Was nun? - P...e-dialog GmbH
Nach der positiven Entscheidung zum Einsatz einer eigenen DMP stellt sich die Frage nach dem Vorhandensein einer nachhaltigen Datenstrategie. Wir zeigen die vier relevanten Eckpunkte dazu auf: Collection, Hierarchy, Management, Activation
A vision for sustainable analytics implementations - Superweek 2020Jente De Ridder
Marketing automation, machine learning models, customer data platforms; at least one of these is included in your company’s ambitions for 2020. But is you analytics implementation prepared for it? Many companies struggle to implement ambitious data projects because of a lack of data standards and ownership, specialy in the digital analytics sphere.
We introduce the GDDL, a digital data layer framework developed by Stitchd but available as open source solution for everyone that is looking for a sustainable approach to a data layer implementation.
Presentation held at Superweek conference, Hungary, January 2020.
Siamac Alexander Rahnavard (Echte Liebe) Programmatic Creativity - Programmat...e-dialog GmbH
Programmatic Marketing bietet Werbetreibenden neue Möglichkeiten der kreativen Ansprache. Neben eigenen First Party Daten können Advertiser event- oder situationsbezogene, aber auch interessensbasierte Daten wie Kaufabsichten für eine gezieltere Werbeansprache mit einbeziehen. Programmatic Creativity ist dabei wesentlicher Kerne einer ganzheitlich gedachten programmatischen Strategie, da sie maßgeblich zur Erreichung des Users zur richtigen Zeit am richtigen Ort beiträgt. Programmatic Creativity geht dabei weit über den rein technischen Mediaeinkauf hinaus.
Everybody talks about Digital Transformation and Digital Disruption and the impact on Marketing. Marketing needs to find new ways to interact, sure. But do digital transformation of marketing and digital marketing even exist? Not sure! Whatever, you still need to get ready for new technologies like Voice. And you should do it fast.
Thorsten Sachtje (Senior Consultant Digital Strategy @ metapeople - Part of Artefact) held this presentation as part of a 1,5 hour lecture to Marketing Management BSc students of Ruhr University Bochum (Germany) on June 7th, 2018.
B2B marketing can be very different from B2C. The buying process is more complex and requires expertise and targeted audiences. LinkedIn is uniquely positioned to help your agency succeed in the B2B marketing space.
In this presentation, Aishwarya introduces SMAC and associated trends. Aishwarya's interest areas lies in data mining to find out "Why a customer buys a certain product" which will help business in making better product decisions.
Why should you invest in LEO CDP ?
Purpose: Big data and AI democracy for SMEs companies
Problem: Customer Analytics and Customer Personalization
Solutions: CDP + CX + Personalization Engine
Product demo: LEO CDP for Ecommerce and Fintech
Business model: Freemium → Ecosystem → Subscription
Market size: 20 billion USD in 2026 and CAGR 34.6%
Differentiation: cloud-native software
Go-to-market approach: Community → Free → Paid
Team: 1 full-stack dev, 1 data scientist and 12,000 fans of BigDataVietnam.org Community
Need 150,000 USD for scaling business (you get 20% share)
A look at digital marketing in the not-too-distant future. From shifting privacy norms, evolving SERPs, the game-ification of everything, social business, and more. Implications and business application included as well.
Answer to the most commonly used terminology Data Science with their areas of crucial roles in solving issues with case studies.
Likewise, let me know if anything is required. Ping me at google #bobrupakroy
WHY DO SO MANY ANALYTICS PROJECTS STILL FAIL?Haluk Demirkan
“KEY CONSIDERATIONS FOR DEEP ANALYTICS ON BIG DATA FOR DEEP LEARNING”
What is Big Data? Big Data, which means many things to many people, is not a new technological fad. In addition to providing innovative solutions and operational insights to enduring challenges and opportunuties, big data with deep analytics instigate new ways to transform processes, organizations, entire industries, and even society all together. Pushing the boundaries of deep data analytics uncovers new.
Big Data is not just “big.” The exponentially growing volume of the data is only one of many characteristics that are often associated with Big Data, such as variety, velocity, veracity and others (6Vs).
By now, we should already have knowledge and experience to have successful data and analytics enabled decision support systems. So why do these projects still fail, and why are executives and users are still so unhappy? While there are many reasons for this high failure rate, the biggest is that companies still treat these projects as just another IT project. Big data analytics is neither a product nor a computer system. It is, rather, a constantly evolving strategy, vision and architecture that continuously seek to align an organization’s operations and direction with its strategic business goals with strategic, tactical and operational decisions.
Big Data Expo 2015 - Savision Optimizing IT OperationsBigDataExpo
Today’s IT Operations are more complex than ever; Private Clouds, Public Clouds, users accessing the datacenters from any device, have dramatically increased the number of data points for IT Operations. We will discuss how IT Operations Analytics and Business Service Management can help with these big data challenges.
CDP - 101 Everything you need to know about Customer Data PlatformsEddy Widerker
There has been a lot of buzz around Customer Data Platforms (CDP) in the past months/years. This presentation gives you a great overview of what a CDP is, the similarities across different systems such as a DMP or CRM. As well as valuable questions that help you determine if your organization needs a Customer Data Platform.
At the same time, if you find yourself being a bit overwhelmed with all of the 1st 2nd or 3rd party data targeting options from, I'd highly recommend using a service like ClearSegment to understand various data providers - it's data collection methodologies as well as their individual segments. https://clearsegment.com/
The Analytic Platform: Empowering the Business NowInside Analysis
The Briefing Room with Dr. Robin Bloor and Actuate
Live Webcast on October 7, 2014
Watch the archive:
https://bloorgroup.webex.com/bloorgroup/lsr.php?RCID=475312d15f46d095797f5842de84925f
As businesses grapple with more and more data, analysts and data consumers have a growing expectation to get at those assets fast. All too often, business users are stymied by governance and performance roadblocks, making time-to-insight a relatively slow process. One solution is to leverage the power of an analytic platform, one that keeps data management in IT’s hands, and lets business analysts jump right in without the need for modeling and provisioning.
Register for this episode of The Briefing Room to hear veteran Analyst Dr. Robin Bloor as he explains the principles behind a meaningful analytic platform. He’ll be briefed by Peter Hoopes and Allen Bonde of Actuate, who will tout their company’s BIRT Analytics, a solution that combines columnar database technology with pre-built algorithms and puts analytics in the hands of the business user in minutes, not days. They will show how their platform makes it easy to perform complex analytics on enterprise data and visualize results, without slowing down other systems or interfering with governance needs.
Visit InsideAnlaysis.com for more information.
There are more and more organisations thinking about Open Data. We do think that Open Data needs tools. The Business Model Canvas could be one, but it's not totally appropriate. Here is the Open Data Canvas. Let's try it and improve it !
How to track and improve Customer Experience with LEO CDPTrieu Nguyen
1) Why CX measurement is so important
2) Introduction to key metrics of CX
2.1 Customer Feedback Score (CFS)
2.2 Customer Effort Score (CES)
2.3 Customer Satisfaction Score (CSAT)
2.4 Net Promoter Score (NPS)
3) Using Journey Map to CX Data Management
4) Introduction to LEO CDP and demo
Lộ trình triển khai LEO CDP cho ngành bất động sảnTrieu Nguyen
1) Hiểu bài toán số hoá trải nghiệm khách hàng
2) Nghiên cứu giải pháp LEO CDP
3) Lộ trình triển khai
Phát triển / số hoá điểm chạm khách hàng
Xây dựng bản đồ hành trình khách hàng
Định nghĩa các metrics và KPI quan trọng
Xây dựng web portal và mobile data hub
Xây dựng kế hoạch Digital Marketing
Triển khai CDP và Marketing Automation
Xây dựng đội Analytics để phân tích dữ liệu
Apache Hadoop and Spark: Introduction and Use Cases for Data AnalysisTrieu Nguyen
Growth of big datasets
Introduction to Apache Hadoop and Spark for developing applications
Components of Hadoop, HDFS, MapReduce and HBase
Capabilities of Spark and the differences from a typical MapReduce solution
Some Spark use cases for data analysis
Introduction to Recommendation Systems (Vietnam Web Submit)Trieu Nguyen
1) Why do we need recommendation systems ?
2) How can we think with recommendation systems ?
3) How can we implement a recommendation system with open source technologies ?
RFX framework https://github.com/rfxlab
Apache Kafka: https://kafka.apache.org
Apache Spark: https://spark.apache.org
Giới thiệu cơ bản về Big Data và các ứng dụng thực tiễnTrieu Nguyen
1. Các ứng dụng Big Data thực tiễn trên thế giới
2. Các lĩnh vực đang ứng dụng Big Data ở Việt
Nam
3. Các bài toán Big Data tiêu biểu ở Vietnam
a. Quản lý chăm sóc khách hàng (CRM)
b. Tối ưu hoá trải nghiệm truyền hình Internet
c. Quảng cáo trực tuyến AdsPlay.net
4. Giới thiệu về công việc và thị trường việc làm
Big Data ở Việt Nam
5. Kiến thức nền tảng cho các bạn sinh viên
Agenda:
• Background for the development: From commodity
to experience
• Indirect use of experiences: Experience as value
adding
• Experience process
• Selling pure experiences: Using the experience realm
model
• How to develop experiences
• Creating the experience settings
Introduction to Human Data Theory for Digital EconomyTrieu Nguyen
Key ideas in this slide:
1) Knowledge about the theory of “Human Data World”
2) Examples about Data Product in real life
3) How to build a Data Product
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
1. From Dataism to
Customer Data Platform
How to think in the age of Dataism with LEO CDP ?
Presented by Trieu Nguyen (Thomas)
LinkedIn: https://www.linkedin.com/in/tantrieuf31
Facebook: https://www.facebook.com/tantrieuf31
2. Have you seen “The Great Hack” ?
An awesome movie about Dataism and its dark side
3. Key questions
Why is Dataism for human, business and society ?
How should LEO Customer Data Platform (LEO CDP) work ?
In the mindset of U. S. P. A Technology
How to use LEO CDP for your business ?
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4. The first question
Why is Dataism for human, business and society ?
How should LEO Customer Data Platform (LEO CDP) work ?
In the mindset of U. S. P. A Technology
How to use LEO CDP for your business ?
1.
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5. So what is Dataism ?
Source: https://www.theguardian.com/books/2016/aug/24/homo-deus-by-yuval-noah-harari-review
12. The second question
Why is Dataism for human, business and society ?
How should LEO Customer Data Platform (LEO CDP) work ?
in the mindset of U. S. P. A Technology
How to use LEO CDP for your business ?
1.
2.
3.
14. CRM can manage lower funnel only (Action,Loyalty and Advocacy)
CDP can manage the whole data funnel (Awareness to Advocacy)
Customer Data Funnel and its solutions
25. The third question
Why is Dataism for human, business and society ?
How should LEO Customer Data Platform (LEO CDP) work ?
In the mindset of U. S. P. A Technology
How to use LEO CDP for your business ?
1.
2.
3.