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Big Data LDN
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DataOps
GitOps
Lenses.io
Babylon Health
Data Platform Engineering
Health industry
Scaling
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Provides a case study of the real-world application of data engineering practices at Babylon Health, a leading healthcare provider
Meant for those interested in the practical implementation of DataOps tools and practices to scale data engineering teams in the healthcare industry
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Freeing up Engineering and Infrastructure Resources to Scale with DataOps.
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Career center
Learners who complete Freeing up Engineering and Infrastructure Resources to Scale with DataOps will develop knowledge and skills
that may be useful to these careers:
Data Engineer
Data Engineer
Data Engineers design, create, and maintain the infrastructure that supports a company's data needs. They work with data scientists, data analysts, and other stakeholders to ensure that data is accessible, reliable, and secure. This course can help Data Engineers learn the tools and techniques needed to scale their data infrastructure.
DataOps Engineer
DataOps Engineer
DataOps Engineers work to automate and streamline the data lifecycle. They work with developers, operations engineers, and other stakeholders to ensure that data is flowing smoothly from source to target. This course provides DataOps Engineers with the skills and knowledge needed to implement DataOps best practices at their company.
Data Architect
Data Architect
Data Architects design and implement the data architecture for an organization. They work with stakeholders to understand the business needs and translate them into a technical solution. This course can help Data Architects learn the principles of data architecture and how to apply them in the real world.
Software Engineer, Data Platform
Software Engineer, Data Platform
Software Engineers who specialize in data platforms design and develop the software that supports data-intensive applications. They work with data engineers, data scientists, and other stakeholders to ensure that data is accessible, reliable, and secure. This course provides Software Engineers with the skills and knowledge needed to build scalable data platforms.
Business Intelligence Analyst
Business Intelligence Analyst
Business Intelligence Analysts use data to help businesses make better decisions. They work with data from a variety of sources to identify trends, patterns, and insights that can be used to improve business performance. This course can help Business Intelligence Analysts learn the tools and techniques needed to gather, clean, and analyze data.
Data Scientist
Data Scientist
Data Scientists use data to solve problems and make predictions. They work with data from a variety of sources to build models that can be used to automate decisions and improve business outcomes. This course can help Data Scientists learn the tools and techniques needed to build and deploy machine learning models.
Data Analyst
Data Analyst
Data Analysts gather, clean, and analyze data to provide insights to businesses. They work with data from a variety of sources to identify trends, patterns, and insights that can be used to improve business performance. This course can help Data Analysts learn the tools and techniques needed to gather, clean, and analyze data.
DevOps Engineer
DevOps Engineer
DevOps Engineers work to bridge the gap between development and operations teams. They work with developers and operations engineers to ensure that applications are deployed and maintained efficiently and reliably. This course can help DevOps Engineers learn the tools and techniques needed to implement DevOps best practices.
Cloud Engineer
Cloud Engineer
Cloud Engineers design, build, and manage cloud-based applications and infrastructure. They work with developers and operations engineers to ensure that cloud-based applications are deployed and maintained efficiently and reliably. This course can help Cloud Engineers learn the tools and techniques needed to build and manage cloud-based applications.
Data Governance Analyst
Data Governance Analyst
Data Governance Analysts develop and implement policies and procedures to ensure that data is managed in a consistent and compliant manner. They work with data owners, data stewards, and other stakeholders to ensure that data is used ethically and responsibly. This course can help Data Governance Analysts learn the principles of data governance and how to apply them in the real world.
Data Protection Officer
Data Protection Officer
Data Protection Officers are responsible for ensuring that an organization complies with data protection laws and regulations. They work with data owners, data processors, and other stakeholders to ensure that data is processed in a compliant manner. This course can help Data Protection Officers learn the principles of data protection and how to apply them in the real world.
Data Privacy Analyst
Data Privacy Analyst
Data Privacy Analysts develop and implement policies and procedures to protect the privacy of personal data. They work with data owners, data processors, and other stakeholders to ensure that personal data is collected, used, and disclosed in a compliant manner. This course can help Data Privacy Analysts learn the principles of data privacy and how to apply them in the real world.
Database Administrator
Database Administrator
Database Administrators design, implement, and maintain databases. They work with data engineers, data analysts, and other stakeholders to ensure that databases are performant, reliable, and secure. This course can help Database Administrators learn the tools and techniques needed to build and manage databases.
Data Warehouse Architect
Data Warehouse Architect
Data Warehouse Architects design and implement data warehouses. They work with data engineers, data analysts, and other stakeholders to ensure that data is stored and organized in a way that makes it easy to access and analyze. This course can help Data Warehouse Architects learn the principles of data warehousing and how to apply them in the real world.
Big Data Engineer
Big Data Engineer
Big Data Engineers design and implement systems for processing and analyzing large amounts of data. They work with data engineers, data analysts, and other stakeholders to ensure that data is processed and analyzed efficiently and effectively. This course can help Big Data Engineers learn the tools and techniques needed to build and manage big data systems.
For more career information including salaries, visit:
OpenCourser.com/course/9yo79v/freeing
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deeper understanding of the topics covered in
Freeing up Engineering and Infrastructure Resources to Scale with DataOps.
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Provides a comprehensive overview of DataOps, including key concepts, tools, and best practices. It great resource for beginners who want to learn more about DataOps.
For more information about how these books relate to this course, visit:
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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
- 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 (viewing)
- 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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