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Big Data LDN
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Apache Spark
Databricks
Google BigQuery
Looker
AWS S3
Data Democratization
Data Warehousing
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OpenCourser.com/course/5udy6a/democratising
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Highly relevant to data engineers, data architects, data scientists, and solution architects
Provides strong foundation for data platform architecture
Led by experienced instructors with recognized expertise in data engineering
Teaches tools and technologies core to data platform engineering
Collaborates with a provider that adds to course legitimacy
Explicitly designed for self-service access to data
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Democratising Data – How We Built a Self-serve Data Platform.
These are activities you can do either before, during, or after a course.
Career center
Learners who complete Democratising Data – How We Built a Self-serve Data Platform will develop knowledge and skills
that may be useful to these careers:
Data Engineer
Data Engineer
Data Engineers use their knowledge of data platforms, data storage, data modeling, and data integration to design, build, test, and maintain data management systems. This course may be useful for those who wish to enter this field, as it provides an overview of the architecture of a multi-cloud data platform and the various tools used to fulfill this mission, including AWS S3, Apache Spark, Databricks, Google BigQuery, and Looker.
Data Architect
Data Architect
Data Architects design, build, and manage data systems that meet the needs of an organization. This course may be useful for those who wish to enter this field, as it provides an overview of the architecture of a multi-cloud data platform and the various tools used to fulfill this mission, including AWS S3, Apache Spark, Databricks, Google BigQuery, and Looker.
Data Analyst
Data Analyst
Data Analysts collect, clean, and analyze data to help businesses make informed decisions. This course may be useful for those who wish to enter this field, as it provides an overview of the tools and technologies used to build a self-serve data platform.
Database Administrator
Database Administrator
Database Administrators design, implement, and maintain databases. This course may be useful for those who wish to enter this field, as it provides an overview of the tools and technologies used to build a self-serve data platform.
Data Scientist
Data Scientist
Data Scientists use their knowledge of data analysis, machine learning, and statistics to solve business problems. This course may be useful for those who wish to enter this field, as it provides an overview of the tools and technologies used to build a self-serve data platform.
Business Analyst
Business Analyst
Business Analysts use their knowledge of business processes and data analysis to help businesses improve their operations. This course may be useful for those who wish to enter this field, as it provides an overview of the tools and technologies used to build a self-serve data platform.
Product Manager
Product Manager
Product Managers are responsible for managing the development and launch of new products. This course may be useful for those who wish to enter this field, as it provides an overview of the tools and technologies used to build a self-serve data platform.
Software Engineer
Software Engineer
Software Engineers design, build, and maintain software applications. This course may be useful for those who wish to enter this field, as it provides an overview of the tools and technologies used to build a self-serve data platform.
Data Visualization Engineer
Data Visualization Engineer
Data Visualization Engineers design and develop data visualizations that help businesses understand their data. This course may be useful for those who wish to enter this field, as it provides an overview of the tools and technologies used to build a self-serve data platform.
Data Journalist
Data Journalist
Data Journalists use their knowledge of data analysis and journalism to tell stories with data. This course may be useful for those who wish to enter this field, as it provides an overview of the tools and technologies used to build a self-serve data platform.
Marketing Analyst
Marketing Analyst
Marketing Analysts use their knowledge of data analysis and marketing to help businesses improve their marketing campaigns. This course may be useful for those who wish to enter this field, as it provides an overview of the tools and technologies used to build a self-serve data platform.
Financial Analyst
Financial Analyst
Financial Analysts use their knowledge of data analysis and finance to help businesses make informed financial decisions. This course may be useful for those who wish to enter this field, as it provides an overview of the tools and technologies used to build a self-serve data platform.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use their knowledge of data analysis and operations research to help businesses improve their operations. This course may be useful for those who wish to enter this field, as it provides an overview of the tools and technologies used to build a self-serve data platform.
Risk Analyst
Risk Analyst
Risk Analysts use their knowledge of data analysis and risk management to help businesses identify and mitigate risks. This course may be useful for those who wish to enter this field, as it provides an overview of the tools and technologies used to build a self-serve data platform.
Auditor
Auditor
Auditors use their knowledge of data analysis and accounting to help businesses ensure that their financial records are accurate and complete. This course may be useful for those who wish to enter this field, as it provides an overview of the tools and technologies used to build a self-serve data platform.
For more career information including salaries, visit:
OpenCourser.com/course/5udy6a/democratising
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
Democratising Data – How We Built a Self-serve Data Platform.
Comprehensive and practical guide to empowering business users with self-service data analytics tools. It covers the benefits, challenges, and best practices of self-service data analytics, as well as how to implement and manage a self-service data analytics program.
Comprehensive guide to Google BigQuery, a cloud-based data warehouse. It covers the architecture and components of BigQuery, as well as how to use BigQuery for a variety of data analysis tasks.
Comprehensive guide to Hadoop, a popular open-source big data platform. It covers the architecture and components of Hadoop, as well as how to use Hadoop for a variety of data processing tasks.
Provides an overview of big data analytics using Spark. It covers the different types of big data analytics applications, as well as how to use Spark to develop and deploy big data analytics applications.
Comprehensive guide to data analysis using Python. It covers the different types of data analysis tasks, as well as how to use Python to perform data analysis.
Comprehensive guide to machine learning using Python. It covers the different types of machine learning algorithms, as well as how to use Python to develop and deploy machine learning models.
Comprehensive guide to deep learning using Python. It covers the different types of deep learning models, as well as how to use Python to develop and deploy deep learning models.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/5udy6a/democratising
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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
- 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 (viewing)
- 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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