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Big Data LDN
Big Data LDN 2019 | Real-time Personalised Customer Interaction at Scale | Rares Rusu and Alexandru Objelean
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Big Data LDN 2019 | Real-time Personalised Customer Interaction at Scale | Rares Rusu and Alexandru Objelean
Read more
Big Data LDN 2019 | Real-time Personalised Customer Interaction at Scale | Rares Rusu and Alexandru Objelean
How do you build a customer interaction platform that is agile enough to respond to constantly changing requirements and still able to perform at scale? This is the challenge the Customer Interaction team set out to solve at Paddy Power Betfair. You will learn how they rebuilt their promotional platform moving from one based on a closed slow relational database to a high-performance agile platform that integrates promotions from 3rd parties. You will see how this transformation has enabled marketing to continuously innovate and apply timely, relevant personalized offers to hundreds of thousands of customers across two brands, even during massive spikes in traffic.
This course is no longer available. Find a similar course by searching these:
real-time data architecture
personalized customer interaction
big data architecture
large-scale data processing
customer experience management
personalization techniques
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What's inside
Syllabus
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Taught by Big Data LDN, recognized experts in big data
Relevant to marketing, data science, and software engineering professionals
Covers a comprehensive approach to building and managing customer interaction platforms
May require some foundational knowledge in big data and software development concepts
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Career center
Learners who complete Real-time Personalised Customer Interaction at Scale will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
Data Analysts gather, clean, and analyze data to extract meaningful insights. They use statistical techniques and programming languages to identify trends, patterns, and relationships in data. This course can help you build a foundation in data analysis and prepare you for a career as a Data Analyst. You will learn how to use SQL and Python to query and analyze data, and how to use statistical techniques to identify trends and patterns.
Data Scientist
Data Scientist
Data Scientists use their knowledge of statistics, programming, and machine learning to build models that can predict future outcomes. They work with large datasets to identify patterns and trends, and they develop algorithms to solve business problems. This course can help you build a foundation in data science and prepare you for a career as a Data Scientist. You will learn how to use Python and R to analyze data, and you will learn how to use machine learning techniques to build predictive models.
Data Engineer
Data Engineer
Data Engineers design, build, and maintain the infrastructure that supports data analysis and machine learning. They work with large datasets to ensure that they are accessible, reliable, and secure. This course can help you build a foundation in data engineering and prepare you for a career as a Data Engineer. You will learn how to use SQL and Python to query and analyze data, and you will learn how to use cloud computing platforms to build and manage data pipelines.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, build, and maintain machine learning models. They work with large datasets to train and evaluate models, and they develop software to deploy models into production. This course can help you build a foundation in machine learning and prepare you for a career as a Machine Learning Engineer. You will learn how to use Python and R to train and evaluate machine learning models, and you will learn how to use cloud computing platforms to deploy models into production.
Software Engineer
Software Engineer
Software Engineers design, build, and maintain software applications. They work with a variety of programming languages and technologies to develop software solutions for businesses. This course can help you build a foundation in software engineering and prepare you for a career as a Software Engineer. You will learn how to use Python and Java to develop software applications, and you will learn how to use cloud computing platforms to deploy software into production.
Business Analyst
Business Analyst
Business Analysts gather and analyze data to help businesses make better decisions. They work with stakeholders to understand their needs and develop solutions to business problems. This course can help you build a foundation in business analysis and prepare you for a career as a Business Analyst. You will learn how to use SQL and Python to query and analyze data, and you will learn how to use statistical techniques to identify trends and patterns.
Product Manager
Product Manager
Product Managers are responsible for the development and launch of new products. They work with engineers, designers, and marketers to bring products to market. This course can help you build a foundation in product management and prepare you for a career as a Product Manager. You will learn how to use SQL and Python to query and analyze data, and you will learn how to use statistical techniques to identify trends and patterns.
Marketing Manager
Marketing Manager
Marketing Managers are responsible for the development and execution of marketing campaigns. They work with a variety of marketing channels to reach target audiences. This course can help you build a foundation in marketing and prepare you for a career as a Marketing Manager. You will learn how to use SQL and Python to query and analyze data, and you will learn how to use statistical techniques to identify trends and patterns.
Sales Manager
Sales Manager
Sales Managers are responsible for the development and execution of sales strategies. They work with a team of sales representatives to achieve sales targets. This course may help you build a foundation in sales and prepare you for a career as a Sales Manager. You will learn how to use SQL and Python to query and analyze data, and you will learn how to use statistical techniques to identify trends and patterns.
Customer Success Manager
Customer Success Manager
Customer Success Managers are responsible for the satisfaction of customers. They work with customers to ensure that they are successful with their products or services. This course may help you build a foundation in customer success and prepare you for a career as a Customer Success Manager. You will learn how to use SQL and Python to query and analyze data, and you will learn how to use statistical techniques to identify trends and patterns.
Operations Manager
Operations Manager
Operations Managers are responsible for the day-to-day operations of a business. They work with a variety of departments to ensure that the business runs smoothly. This course may help you build a foundation in operations management and prepare you for a career as an Operations Manager. You will learn how to use SQL and Python to query and analyze data, and you will learn how to use statistical techniques to identify trends and patterns.
Financial Analyst
Financial Analyst
Financial Analysts are responsible for the analysis of financial data. They work with a variety of financial institutions to provide insights into investment decisions. This course may help you build a foundation in financial analysis and prepare you for a career as a Financial Analyst. You will learn how to use SQL and Python to query and analyze data, and you will learn how to use statistical techniques to identify trends and patterns.
Consultant
Consultant
Consultants provide advice to businesses on a variety of topics. They work with clients to identify problems and develop solutions. This course may help you build a foundation in consulting and prepare you for a career as a Consultant. You will learn how to use SQL and Python to query and analyze data, and you will learn how to use statistical techniques to identify trends and patterns.
Project Manager
Project Manager
Project Managers are responsible for the planning, execution, and closure of projects. They work with a team of project stakeholders to achieve project goals. This course may help you build a foundation in project management and prepare you for a career as a Project Manager. You will learn how to use SQL and Python to query and analyze data, and you will learn how to use statistical techniques to identify trends and patterns.
Data Visualization Specialist
Data Visualization Specialist
Data Visualization Specialists are responsible for the creation of visual representations of data. They work with data analysts and scientists to communicate insights to a wider audience. This course may help you build a foundation in data visualization and prepare you for a career as a Data Visualization Specialist. You will learn how to use SQL and Python to query and analyze data, and you will learn how to use data visualization tools to create visual representations of data.
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Time
27 hours
Level
Intermediate
Via
Pluralsight
Instructor
Big Data LDN
Language
English
This course belongs to a
collection
called
Big Data LDN 2019 . It's comprised of 101 courses:
- The Database Is Only Half Done
- Your AI Is Wrong! Lessons from Decision-making with Imperfect AI
- Multiparadigm Data Science: The Next Frontier in Decision Making
- Achieving 100% Adoption of Analytics in the Enterprise
- Data Skills: How Mondi Does Digital
- Building a Modern Data Architecture for the Data Driven Enterprise
- Harnessing the Power of Data to Improve Public Health
- Real-time Data Analytics at Scale Using Cloud Services
- Quick and Easy Access to Data through a Logical Data Warehouse Environment
- The Promise of Data Mastering at Scale
- Research vs. Reality in AI: Would You Trust Your Model with Your Life?
- Modernise Your IT Infrastructure for AI
- Scaling Machine Learning at Holiday Extras
- Why Do Some Machine Learning Models Fail?
- AI: Lessons Learned from the Front Line
- Machine Learning in Real-time: Predicting Taxi Fare in NYC
- How AI and Automated Machine Learning Will Disrupt the Organisational Alignment of Businesses
- Multi-model Powered Machine Learning
- ML in Production: Serverless and Painless
- Leveraging Data Virtualization to Maximize Advanced Analytics and Machine Learning Potential in Your Data Architecture
- Bring the Power of Watson to AWS and Azure: Watson Anywhere Powered by Cloud Pak for Data
- Modern Data Warehousing at Scale Using Azure Data Factory
- Balancing Performance, Scalability, and High Availability in Your Database Environment
- Enabling Microservices for Big Data On-demand in the Cloud
- From ETL to ELT: Building a Scalable Data Stack with SQL
- Data, Governance, and Freedom
- How to Get the Technology Stack Right for Your Business
- Data Modelling with Apache Cassandra
- How to Orchestrate Your ML Pipelines in Hybrid Cloud
- Full Stack Metadata Driven Thinking to Drive Business Agility
- Enhance Developer Experience Using OpenShift on Azure
- Fast Data for Faster Business
- Driving Faster, Smarter Actions on IoT Data with New Real-time Analytics Capabilities
- Introduction to Adept and How Big Data and Analytics Is Transforming the Connected Car Ecosystem
- Bridge to Cloud
- How to Train Your AI Models at Scale
- 99% of Your IoT Data Is Worthless, but Which 99%?
- Data Engineering in MagicLab: The Birth and Life of an Event
- RNA - Event Stream Processing Made Simple
- When Data Leads, Transformation Follows - A Look at Qlik's Data Integration Portfolio
- Saving Energy in Homes with a Unified Approach to Data and AI
- Building Stream Processing Applications with Apache Kafka Using KSQL
- Real-world, Real-time Digital Transformation
- Machine Data in Industry 4.0: How to Handle It Better
- Why CockroachDB in the Kindred Platform?
- The Hardest Part of AI & Analytics Is Not AI, It Is Data Management
- Effective Cloud Migration Strategies for Your Modern Data Applications
- Snowflake? Why Should I Care?
- The Future of Business Intelligence Isn't a Tool
- AI-driven Retail for the 21st Century
- The Next Generation of Data Architecture
- Modern Enterprise Data Engineering
- Taking Control of User Analytics with Snowplow
- Flex Your Data(Ops) Muscles
- You Love Big Data, so Does R
- Building Predictive Maintenance Solutions
- Quickly, Codelessly Connect Any Application to Any REST API
- Rethinking Data Warehouse Modernization in the Age of Hybrid Cloud/On-premise Data Warehouses
- From Waterfall to Agile – A Data Warehouse Modernisation Story
- Freeing up Engineering and Infrastructure Resources to Scale with DataOps
- Unit Testing with pytest
- Credit Card Fraud – Why the Database Matters
- Data Science at SEGA
- British Telecom: Data-driven Digital Transformation
- Using Cloud Solution Platforms to Drive Business Value and Cost Optimization
- Data Analytics & IoT Innovations at Bosch
- Converting the CDO to a Profit Centre
- Why Self-service Data Analytics Usually Fails & Ideas for Succeeding
- Governed Data Discovery
- Journey to Create a Great Analytic Culture
- Something Amazing for Everyone: Embracing Inclusive Design to Deliver Accessible Experiences
- Democratising Data – How We Built a Self-serve Data Platform
- Discover the “Why” You Didn't Know Existed
- Selecting Your Fantasy Premier League Team with Advanced Analytics
- Decouple Storage from Compute
- Data Skills: Building a Data Team Fit for a Data-driven Enterprise
- Consent, Compliance, and the Impact on Customer Experience
- AI & Communication: Meaningful Data from New Sources
- Real-time Personalised Customer Interaction at Scale (viewing)
- Data: The Musical, with LW Theatres
- Self-service and Tableau Community at Lloyds Banking Group
- The Digital Hero’s Journey: Using Big Data to Uncover Business Value and Meaning at Work
- Using Location Intelligence to Place Solar Panels in Rwanda
- Embedding Intelligence into the Heart of Customer Operations
- The Art of Customer Conversations
- How to Build a Fully Autonomous Card Fraud Detection System
- At Last! The Real-time Customer Experience
- Data Privacy Mythbusting
- Demystifying Data – What They Don’t Tell You at Data School
- Optimizing Your Data Value Chain with Agile Data Management
- Data at SEGA Europe
- Keep Your Data Lake from Getting Hadooped
- Top 10 Privacy Tips & Tricks in Big Data
- Data Governance as a Customer Service
- 7 AI Quick Win Projects
- Delivering Value with Intelligent Data Governance
- The Culture Competition – Personalisation vs. Privacy
- DataOps for AI and Digital Transformation
- Big Data LDN: A GDPR Retrospective
- GDPR: A Sword Not a Shield
- Drive Business Growth While Satisfying GDPR and CCPA
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