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Big Data LDN
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Data Warehousing
Azure Data Factory
ETL/ELT
Data Integration
Big Data
Register for this course and see more details by visiting:
OpenCourser.com/course/6yj82d/modern
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Explores data integration and ETL/ELT pipelines, which are widely used in data analytics
Taught by Big Data LDN, who are known for their expertise in data management and analytics
Covers key challenges, common patterns, and best practices based on real-world case studies
Offers demos to illustrate how to build, operationalize, and monitor pipelines in a code-free manner
Suitable for both enterprise and ISV professionals looking to build data pipelines for data warehouses
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Modern Data Warehousing at Scale Using Azure Data Factory.
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Career center
Learners who complete Modern Data Warehousing at Scale Using Azure Data Factory will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
Data Analysts translate raw data into meaningful information that can be used to drive decision-making within an organization. As an industry standard tool, this course will help you build a foundation in Azure Data Factory to ETL/ELT data and create scalable data pipelines for advanced analytics.
Data Engineer
Data Engineer
Data Engineers build and maintain data management systems, including data pipelines, data warehouses, and data lakes. This course will help you develop the skills needed to design, build, and manage ETL/ELT pipelines using Azure Data Factory, a widely-used tool in the data engineering field.
Business Intelligence Analyst
Business Intelligence Analyst
Business Intelligence Analysts use data to identify trends and patterns that can help businesses make better decisions. This course will help you build a foundation in Azure Data Factory, a powerful tool for extracting, transforming, and loading data into data warehouses and data lakes, which are essential for business intelligence.
Data Scientist
Data Scientist
Data Scientists use scientific methods to analyze data and extract meaningful insights. This course will help you build a foundation in Azure Data Factory, a platform that is widely used by data scientists to integrate data from various sources, prepare it for analysis, and build machine learning models.
Database Administrator
Database Administrator
Database Administrators manage and maintain databases, ensuring that they are available, secure, and performant. This course will help you build a foundation in Azure Data Factory, a tool that can be used to automate database administration tasks, such as data integration, data cleansing, and data backup and recovery.
Cloud Architect
Cloud Architect
Cloud Architects design and implement cloud computing solutions. This course will help you build a foundation in Azure Data Factory, a fully managed cloud-based data integration service, which is essential for building scalable and performant data pipelines in the cloud.
Data Integration Specialist
Data Integration Specialist
Data Integration Specialists design and implement data integration solutions. This course will help you build a foundation in Azure Data Factory, a popular tool for data integration, which is essential for building and maintaining data pipelines.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. This course may be useful for Software Engineers who want to build or work with data pipelines using Azure Data Factory.
IT Manager
IT Manager
IT Managers plan, implement, and manage IT systems. This course may be useful for IT Managers who want to learn more about Azure Data Factory, a powerful tool for data integration and data management.
Big Data Engineer
Big Data Engineer
Big Data Engineers design and manage big data systems. This course may be useful for Big Data Engineers who want to learn more about Azure Data Factory, a tool that is used to integrate and process big data.
Data Management Consultant
Data Management Consultant
Data Management Consultants help organizations manage their data effectively. This course may be useful for Data Management Consultants who want to learn more about Azure Data Factory, a tool that is used to integrate and manage data.
Data Warehouse Architect
Data Warehouse Architect
Data Warehouse Architects design and implement data warehouses. This course may be useful for Data Warehouse Architects who want to learn more about Azure Data Factory, a tool that is used to build and manage data warehouses.
Data Analyst Manager
Data Analyst Manager
Data Analyst Managers lead and manage teams of data analysts. This course may be useful for Data Analyst Managers who want to learn more about Azure Data Factory, a tool that is used by data analysts to build and manage data pipelines.
Data Governance Specialist
Data Governance Specialist
Data Governance Specialists develop and implement data governance policies and procedures. This course may be useful for Data Governance Specialists who want to learn more about Azure Data Factory, a tool that can be used to enforce data governance policies.
Data Privacy Analyst
Data Privacy Analyst
Data Privacy Analysts develop and implement data privacy policies and procedures. This course may be useful for Data Privacy Analysts who want to learn more about Azure Data Factory, a tool that can be used to protect and manage sensitive data.
For more career information including salaries, visit:
OpenCourser.com/course/6yj82d/modern
Reading list
We've selected seven 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
Modern Data Warehousing at Scale Using Azure Data Factory.
Classic guide to dimensional modeling, the most widely used data modeling technique for data warehouses. It must-read for anyone who wants to design and build a data warehouse.
Provides a comprehensive overview of data warehousing. It covers all aspects of data warehousing, from data integration to data modeling to data analytics.
Provides a comprehensive overview of data integration with Microsoft Azure Data Factory. It covers all aspects of data integration, from data extraction to data loading to data transformation.
Provides a comprehensive overview of data warehousing concepts and best practices. It valuable resource for anyone who wants to learn more about data warehousing and how to use it to support their business.
Provides a comprehensive overview of machine learning for data warehousing and analytics. It covers all aspects of machine learning, from data preparation to model training to model evaluation.
Save
Provides a comprehensive overview of the Azure Data Platform. It covers all aspects of the Azure Data Platform, from data storage to data analytics to data visualization.
Provides a comprehensive overview of big data analytics. It covers all aspects of big data analytics, from data collection to data analysis to data visualization.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/6yj82d/modern
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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
- 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 (viewing)
- 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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