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Big Data LDN
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Real-Time Data
Streaming Data
Big Data
Apache Kafka
Amazon Kinesis
Lambda Architecture
Serverless Computing
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Covers streaming data processing from beginners to advanced learners, with a focus on Amazon Web Services (AWS)
Taught by Big Data LDN, recognized for their expertise in streaming data
Develops skills highly relevant to cloud computing and real-time data analytics
Uses a combination of open source tools and managed services, making it applicable to various skill levels and budgets
Focuses on practical implementation, providing hands-on experience in working with streaming data at scale
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Real-time Data Analytics at Scale Using Cloud Services.
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Career center
Learners who complete Real-time Data Analytics at Scale Using Cloud Services will develop knowledge and skills
that may be useful to these careers:
Data Engineer
Data Engineer
Data Engineers create and maintain data pipelines for their organization. They may also design the architecture for both small and large-scale data solutions. This course would help build a foundation in streaming data processing necessary for effective Data Engineering.
Data Architect
Data Architect
Data Architects plan the design, creation, and implementation of an organization's data infrastructure. They may also provide guidance for how data can best be used by the organization. This course would help build a foundation in streaming data processing necessary for effective Data Architecture.
Software Engineer
Software Engineer
Software Engineers design, develop, test, and maintain software applications. They may also participate in the design of the overall system architecture and provide guidance on how best to collect and process data. This course may be helpful for Software Engineers who are working with streaming data systems or who want to learn more about this topic.
Data Analyst
Data Analyst
Data Analysts collect, clean, transform, and analyze data to extract meaningful insights and present them in a clear and concise manner. This course may be helpful for Data Analysts who are working with streaming data systems or who want to learn more about this topic.
Data Scientist
Data Scientist
Data Scientists use statistical and machine learning techniques to build predictive models and analyze data to extract meaningful insights. This course may be helpful for Data Scientists who are working with streaming data systems or who want to learn more about this topic.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, develop, and deploy machine learning models and systems. They also ensure that these models are efficient, reliable, and perform as expected in production environments. This course may be helpful for Machine Learning Engineers who are working with streaming data systems or who want to learn more about this topic.
Business Analyst
Business Analyst
Business Analysts help organizations to understand their business processes and make data-driven decisions. They may also provide guidance on how data can best be used to improve the organization's performance. This course may be helpful for Business Analysts who are working with streaming data systems or who want to learn more about this topic.
Cloud Engineer
Cloud Engineer
Cloud Engineers design, develop, and manage cloud-based solutions and applications. They may also provide guidance on how to use cloud services to support data processing and storage. This course may be helpful for Cloud Engineers who are working with streaming data systems or who want to learn more about this topic.
Database Administrator
Database Administrator
Database Administrators design, implement, and maintain database systems and applications. They may also provide guidance on how to optimize database performance and ensure data integrity. This course may be helpful for Database Administrators who are working with streaming data systems or who want to learn more about this topic.
Data Integration Specialist
Data Integration Specialist
Data Integration Specialists design, develop, and deploy data integration solutions. They may also provide guidance on how to integrate data from different sources and ensure data quality.
Data Governance Specialist
Data Governance Specialist
Data Governance Specialists develop and implement data governance policies and procedures to ensure that data is accurate, complete, consistent, and accessible. They may also provide guidance on how to protect data from unauthorized access and use.
Data Visualization Specialist
Data Visualization Specialist
Data Visualization Specialists design and develop data visualizations to communicate data insights to a variety of audiences. They may also provide guidance on how to use data visualization techniques to improve decision-making.
Information Security Analyst
Information Security Analyst
Information Security Analysts design, implement, and manage security measures to protect data from unauthorized access and use. They may also provide guidance on how to investigate and respond to security incidents.
Business Intelligence Analyst
Business Intelligence Analyst
Business Intelligence Analysts collect, analyze, and interpret data to provide businesses with insights into their operations and performance. They may also provide guidance on how to use data to improve decision-making.
Project Manager
Project Manager
Project Managers plan, execute, and close projects to achieve specific goals and objectives. They may also provide guidance on how to manage resources and ensure project success.
For more career information including salaries, visit:
OpenCourser.com/course/87a3tp/real
Reading list
We've selected eight books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Real-time Data Analytics at Scale Using Cloud Services.
Focuses on Apache Flink, a popular stream processing framework used with AWS. It provides a deep dive into Flink's architecture, programming model, and real-world use cases.
Provides a thorough introduction to Python for data analysis, including best practices and techniques for working with large datasets, which is essential knowledge for real-time data analytics.
While it doesn't directly cover real-time data analytics, this book provides a solid foundation in Hadoop, which is relevant for understanding the distributed processing aspects of stream data.
Focuses on deep learning using TensorFlow 2 and Keras, providing valuable knowledge for applying deep learning models in real-time data analytics for tasks such as image/video processing and anomaly detection.
Offers a broad overview of data science and big data analytics concepts, providing context for the specific topics covered in the course.
Provides a comprehensive overview of natural language processing (NLP) using Python, which can be useful for understanding how to integrate NLP techniques in real-time data analytics applications.
Covers machine learning algorithms and techniques for processing large datasets, which can be valuable knowledge for working with real-time data.
Provides an in-depth look at the architectural patterns and best practices for designing and building data-intensive applications.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/87a3tp/real
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Big Data LDN
This course belongs to a
collection
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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 (viewing)
- 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
- 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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