We may earn an affiliate commission when you visit our partners.
Big Data LDN
Read more
Read more
This course is no longer available. Find something similar by browsing:
Time Series Data
IoT Data Management
Data Reduction
Gallium
Register for this course and see more details by visiting:
OpenCourser.com/course/z2798c/99
Traffic lights
Traffic lights
Read about what's good
what should give you pause and
possible dealbreakers
Explores data reduction methods that optimize speed and accuracy, which is highly relevant to IoT
Led by industry professionals, Datalytyx, which gives students access to expertise and real-world insights
Develops skills in handling large data volumes, which is essential for IoT professionals
Save this course
Create your own learning path.
Save this course to your list so you can find it easily later.
Save
Save
Activities
Coming soon
We're preparing activities for
99% of Your IoT Data Is Worthless, but Which 99%?.
These are activities you can do either before, during, or after a course.
Career center
Learners who complete 99% of Your IoT Data Is Worthless, but Which 99%? will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data Scientists collect raw data from a variety of sources and transform it into useful information that businesses can use to make better decisions. This course could be especially useful to Data Scientists because it discusses the importance of discarding worthless data, as well as the most efficient way to do so.
Data Architect
Data Architect
Data Architects are responsible for overseeing the design, construction and management of the systems that make up an organization's data ecosystem. This course may be especially helpful to Data Architects because it will help them to scale their data pipelines, which will lead to better decision-making.
Data Engineer
Data Engineer
Data Engineers are responsible for designing and building the systems that collect, store, and process data. This course could help Data Engineers better design their data pipelines through a more efficient use of data.
Database Administrator
Database Administrator
Database Administrators are responsible for ensuring that their organization's databases are running smoothly and efficiently. This course may be especially helpful to Database Administrators because it teaches them new techniques to efficiently handle large amounts of data.
Data Analyst
Data Analyst
Data Analysts are responsible analyzing data to help businesses make better decisions. This course may be especially helpful to Data Analysts as it can help them to perform faster and more accurate analysis.
Business Analyst
Business Analyst
Business Analysts are responsible for identifying and solving business problems through the use of data. This course may be especially helpful to Business Analysts because it can help them to gather and process data more efficiently.
Software Engineer
Software Engineer
Software Engineers are responsible for designing, developing, and maintaining software systems. This course could be especially helpful to Software Engineers because it will help them to optimize their code for handling large amounts of data.
Statistician
Statistician
Statisticians are responsible for collecting, analyzing, and interpreting data. This course could help Statisticians to perform analysis on larger quantities of data, and to do so more efficiently.
Computer Programmer
Computer Programmer
Computer Programmers are responsible for developing and maintaining computer software. This course could be especially helpful to Computer Programmers because it will help them to write more efficient code for handling large amounts of data.
Information Security Analyst
Information Security Analyst
Information Security Analysts are responsible for protecting an organization's data from unauthorized access, use, disclosure, disruption, modification, or destruction. This course may be especially helpful to Information Security Analysts as it will help them to identify and protect data more efficiently.
Product Manager
Product Manager
Product Managers are responsible for overseeing the development and marketing of products. This course could be especially helpful to Product Managers because it can help them to make better decisions about how to collect and use data.
Project Manager
Project Manager
Project Managers are responsible for planning, executing, and closing projects. This course may be especially helpful to Project Managers because it can help them to better manage their data and resources.
Quality Assurance Analyst
Quality Assurance Analyst
Quality Assurance Analysts are responsible for testing software to ensure that it meets quality standards. This course could help Quality Assurance Analysts to more efficiently test software.
Technical Writer
Technical Writer
Technical Writers are responsible for writing documentation for software and other technical products. This course could be especially helpful to Technical Writers because it will help them to write more efficient documentation for data-intensive products.
Systems Analyst
Systems Analyst
Systems Analysts are responsible for studying an organization's business needs and recommending solutions. This course may be especially helpful to Systems Analysts because it can help them to better understand the data needs of their clients.
For more career information including salaries, visit:
OpenCourser.com/course/z2798c/99
Reading list
We've selected 16 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
99% of Your IoT Data Is Worthless, but Which 99%?.
Save
Provides a comprehensive overview of TensorFlow, including its architecture, components, and ecosystem. It also covers advanced topics such as model training, evaluation, and deployment.
Save
Provides a comprehensive overview of deep learning, including neural networks, convolutional neural networks, and recurrent neural networks. It also covers advanced topics such as generative adversarial networks and reinforcement learning.
Provides a comprehensive overview of Spark, including its architecture, components, and ecosystem. It also covers advanced topics such as machine learning, graph processing, and streaming on Spark.
Save
Provides a comprehensive overview of causal inference, including its theory, methods, and applications. It valuable resource for anyone who wants to learn how to draw causal conclusions from data.
Provides a comprehensive overview of machine learning, including its theory, methods, and applications. It valuable resource for anyone who wants to learn how to apply machine learning to real-world problems.
Provides a practical introduction to machine learning for data science. It covers supervised and unsupervised learning algorithms, as well as model evaluation and selection.
Save
Provides a comprehensive overview of cloud computing, including its architecture, components, and ecosystem. It also covers advanced topics such as cloud security, cloud management, and cloud economics.
Save
Provides a comprehensive overview of big data analytics, including strategic planning, data management, and data analysis techniques. It also includes case studies to illustrate real-world applications of big data analytics.
Provides a comprehensive overview of Hadoop, including its architecture, components, and ecosystem. It also covers advanced topics such as data warehousing, data mining, and machine learning on Hadoop.
Provides a comprehensive overview of econometrics, including its theory, methods, and applications. It valuable resource for anyone who wants to learn how to use econometrics to analyze economic data.
Save
Provides a comprehensive overview of time series analysis, including its theory, methods, and applications. It valuable resource for anyone who wants to learn how to analyze time series data.
Provides a comprehensive overview of data mining, including its theory, methods, and applications. It valuable resource for anyone who wants to learn how to use data mining to extract knowledge from data.
Provides a comprehensive overview of Bayesian statistics, including its theory, methods, and applications. It valuable resource for anyone who wants to learn how to apply Bayesian statistics to real-world problems.
Provides a practical guide to data science for business professionals. It covers data collection, data analysis, and data visualization, and includes case studies to illustrate real-world applications of data science.
Save
Provides a practical introduction to data visualization, covering topics such as data exploration, data visualization techniques, and data presentation. It useful resource for anyone who wants to learn how to create effective data visualizations.
Provides a gentle introduction to data analytics, making it an excellent resource for beginners in the field. It covers essential concepts and techniques, and is particularly useful for readers who lack a strong background in mathematics or statistics.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/z2798c/99
Share
Similar courses
Similar courses are unavailable at this time. Please try again later.
Via
Pluralsight
Instructor
Big Data LDN
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%? (viewing)
- 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
Our mission
OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.
Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.
Find this site helpful? Tell a friend about us.
Affiliate disclosure
We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.
Your purchases help us maintain our catalog and keep our servers humming without ads.
Thank you for supporting OpenCourser.
© 2016 - 2025 OpenCourser