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María del Pilar Ángeles
Welcome to the specialization course of Designing data-intensive applications.
This course will be completed on four weeks, it will be supported with videos and exercises.
Read more
Welcome to the specialization course of Designing data-intensive applications.
This course will be completed on four weeks, it will be supported with videos and exercises.
Read more
Welcome to the specialization course of Designing data-intensive applications.
This course will be completed on four weeks, it will be supported with videos and exercises.
By the end of this specialization, learners will be able to propose, design, justify and develop high reliable information systems according to type of data and volume of information, response time, type of processing and queries in order to support scalability, maintainability, security and reliability considering the last information technologies.
Software to download:
MySQL Workbench
Rapidminer
Hadoop framework Hortonworks
MongoDB
In case you have a Mac / IOS operating system you need to perform an action called VirtualBox.
Register for this course and see more details by visiting:
OpenCourser.com/course/n0yadu/designing
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What's inside
Syllabus
Designing a transaccional system
After completing this module, a learner will learn how to distinguish a transactional from an analytical information system according to consistency, concurrency and integrity, and how to propose an architecture that suits user requirements.
Read more
Syllabus
Designing a transaccional system
After completing this module, a learner will learn how to distinguish a transactional from an analytical information system according to consistency, concurrency and integrity, and how to propose an architecture that suits user requirements.
Read more
Designing an analytical system
After completing this module, a learner will learn how to distinguish a transactional from an analytical information system according to the queries required on a huge amount of historical structured data that requires fast processing.
Designing an alternative to relational databases
After completing this module, a learner will learn how to distinguish which database technology to use to suit the user requirements, detect frauds and support ACID properties.
Designing an analytical system within a data lake
After completing this module, a learner will identify the architecture and technologies required to analyse a huge volume of structured and semistructured data.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Covers the full spectrum of data-intensive system designs, including transactional, analytical, alternative, and data lake systems
Offers hands-on labs and interactive materials to reinforce concepts
Builds a strong foundation for understanding data-intensive applications, making it suitable for beginners
Instructs learners on the latest information technologies, ensuring their knowledge is current
Explores both structured and semi-structured data, providing a comprehensive understanding of data types
Requires proficiency in software download and installation, which may be a barrier for some learners
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Save Designing data-intensive applications to your list so you can find it easily later:
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Reviews summary
Avoid at all costs
Learners say that this course is frustrating and poorly designed. Reviewers complain that videos simply read bullet points with no real substance. Assignments are broken and have incorrect content. Even quizzes have basic mistakes that don't get corrected.
The course design lacks professionalism.
"the worst offerings I've seen from Coursera"
"The marking scheme, which in a proper peer-grading system shouldn't be available until after you have submitted an assignment!"
The course includes incorrect information.
"The quizzes too followed the general theme of absolute minimal design effort to the point of leaving open the possibility that this course was put together by people who genuinely have no knowledge of the subject at all."
Course structure and grading criteria are not clear.
"Real minimal-effort syllabus design, the videos involved just reading bullet points with zero in-depth information, general advice or tips."
"For all I could tell, the instructor could have been someone that was pulled in from the street that day and asked to read some course notes to a camera."
"The most horrifyingly half-arsed, broken part of the course, however, had to be the assignments."
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Designing data-intensive applications with these
activities:
Connect with Data Analytics Professionals
Show steps
Expand your network and gain guidance by connecting with data analytics professionals, allowing you to learn from their experiences and insights.
Show steps
-
Identify data analytics professionals in your field or area of interest
-
Reach out to them via LinkedIn or email, expressing your interest in connecting
Review SQL
Show steps
Refresh your knowledge of SQL to enhance your understanding of data management fundamentals, which are essential for designing data-intensive applications.
Browse courses on
SQL
Show steps
-
Review SQL syntax and commands
-
Practice writing SQL queries to retrieve and manipulate data
Explore Data Analytics Resources and Courses
Show steps
Enrich your learning journey by exploring data analytics resources and courses, allowing you to expand your knowledge and stay updated on the latest advancements.
Show steps
-
Search for and identify reputable data analytics resources, such as online courses, tutorials, and articles
-
Review the content and find resources that align with your interests and learning goals
Five other activities
Expand to see all activities and additional details
Show all eight activities
Solve Data Analytics Case Studies
Show steps
Challenge yourself and improve your problem-solving skills by solving data analytics case studies, allowing you to apply your knowledge to real-world scenarios.
Show steps
-
Read and analyze data analytics case studies
-
Identify the key issues and challenges presented in the case studies
-
Develop and evaluate potential solutions using data analytics techniques
Design and Implement a Simple Data Analytics System
Show steps
Put your skills into practice by designing and implementing a data analytics system, allowing you to apply the principles learned in the course to a real-world scenario.
Show steps
-
Define the scope and requirements of your data analytics system
-
Choose appropriate tools and technologies for data collection, processing, and analysis
-
Implement your data analytics system and test its functionality
Participate in a Data Analytics Project
Show steps
Gain hands-on experience and contribute to the field by participating in a data analytics project, allowing you to apply your skills and learn from others.
Show steps
-
Research and identify data analytics projects
-
Contact the project organizers and express your interest in volunteering
-
Contribute to data collection, analysis, or visualization tasks
Write a Blog Post on Data Analytics Best Practices
Show steps
Share your knowledge and reinforce your understanding by creating a blog post on data analytics best practices, allowing you to synthesize and communicate your learnings.
Show steps
-
Research and gather information on data analytics best practices
-
Outline the key points you want to cover in your blog post
-
Write and edit your blog post, ensuring clarity and conciseness
Develop a Data Analytics Dashboard
Show steps
Demonstrate your ability to visualize and communicate data insights by developing a data analytics dashboard, allowing you to showcase your skills in presenting information effectively.
Show steps
-
Identify the key metrics and data sources for your dashboard
-
Select appropriate visualization techniques
-
Design and implement your data analytics dashboard
Connect with Data Analytics Professionals
Show steps
Expand your network and gain guidance by connecting with data analytics professionals, allowing you to learn from their experiences and insights.
Show steps
Show steps
Show steps
- Identify data analytics professionals in your field or area of interest
- Reach out to them via LinkedIn or email, expressing your interest in connecting
Review SQL
Show steps
Refresh your knowledge of SQL to enhance your understanding of data management fundamentals, which are essential for designing data-intensive applications.
Browse courses on
SQL
Show steps
Show steps
Show steps
- Review SQL syntax and commands
- Practice writing SQL queries to retrieve and manipulate data
Explore Data Analytics Resources and Courses
Show steps
Enrich your learning journey by exploring data analytics resources and courses, allowing you to expand your knowledge and stay updated on the latest advancements.
Show steps
Show steps
Show steps
- Search for and identify reputable data analytics resources, such as online courses, tutorials, and articles
- Review the content and find resources that align with your interests and learning goals
Five other activities
Expand to see all activities and additional details
Show all eight activities
Solve Data Analytics Case Studies
Show steps
Challenge yourself and improve your problem-solving skills by solving data analytics case studies, allowing you to apply your knowledge to real-world scenarios.
Show steps
Show steps
Show steps
- Read and analyze data analytics case studies
- Identify the key issues and challenges presented in the case studies
- Develop and evaluate potential solutions using data analytics techniques
Design and Implement a Simple Data Analytics System
Show steps
Put your skills into practice by designing and implementing a data analytics system, allowing you to apply the principles learned in the course to a real-world scenario.
Show steps
Show steps
Show steps
- Define the scope and requirements of your data analytics system
- Choose appropriate tools and technologies for data collection, processing, and analysis
- Implement your data analytics system and test its functionality
Participate in a Data Analytics Project
Show steps
Gain hands-on experience and contribute to the field by participating in a data analytics project, allowing you to apply your skills and learn from others.
Show steps
Show steps
Show steps
- Research and identify data analytics projects
- Contact the project organizers and express your interest in volunteering
- Contribute to data collection, analysis, or visualization tasks
Write a Blog Post on Data Analytics Best Practices
Show steps
Share your knowledge and reinforce your understanding by creating a blog post on data analytics best practices, allowing you to synthesize and communicate your learnings.
Show steps
Show steps
Show steps
- Research and gather information on data analytics best practices
- Outline the key points you want to cover in your blog post
- Write and edit your blog post, ensuring clarity and conciseness
Develop a Data Analytics Dashboard
Show steps
Demonstrate your ability to visualize and communicate data insights by developing a data analytics dashboard, allowing you to showcase your skills in presenting information effectively.
Show steps
Show steps
Show steps
- Identify the key metrics and data sources for your dashboard
- Select appropriate visualization techniques
- Design and implement your data analytics dashboard
Career center
Learners who complete Designing data-intensive applications will develop knowledge and skills
that may be useful to these careers:
Data Architect
Data Architect
Data Architects design and implement data management solutions to meet the needs of an organization. They work with business stakeholders to understand their data requirements and then design and build data systems to meet those needs. This course provides a foundation in data modeling, data warehousing, and data integration, which are all essential skills for Data Architects. Additionally, the course covers topics such as data security and data governance, which are increasingly important in today's data-driven world.
Data Engineer
Data Engineer
Data Engineers build and maintain the data infrastructure that supports an organization's data needs. They work with data architects to design and implement data systems and then work with data scientists and other data users to ensure that they have the data they need to do their jobs. This course provides a foundation in data engineering principles and practices, including data storage, data processing, and data security. Additionally, the course covers topics such as cloud computing and big data, which are increasingly important in today's data-driven world.
Data Scientist
Data Scientist
Data Scientists use data to solve business problems. They work with data engineers to access and clean data, and then use statistical and machine learning techniques to analyze data and build models. This course provides a foundation in data science principles and practices, including data analysis, machine learning, and data visualization. Additionally, the course covers topics such as cloud computing and big data, which are increasingly important in today's data-driven world.
Database Administrator
Database Administrator
Database Administrators (DBAs) manage and maintain databases. They work with database designers to create and implement databases, and then work with database users to ensure that they have the data they need to do their jobs. This course provides a foundation in database administration principles and practices, including database design, database performance tuning, and database security. Additionally, the course covers topics such as cloud computing and big data, which are increasingly important in today's data-driven world.
Information Architect
Information Architect
Information Architects design and implement information systems. They work with business stakeholders to understand their information needs and then design and build information systems to meet those needs. This course provides a foundation in information architecture principles and practices, including information modeling, information retrieval, and information security. Additionally, the course covers topics such as cloud computing and big data, which are increasingly important in today's data-driven world.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. They work with software architects to design and implement software systems, and then work with software testers to ensure that software applications are working as expected. This course provides a foundation in software engineering principles and practices, including software design, software development, and software testing. Additionally, the course covers topics such as cloud computing and big data, which are increasingly important in today's data-driven world.
Systems Analyst
Systems Analyst
Systems Analysts design and implement computer systems. They work with business stakeholders to understand their system needs and then design and build computer systems to meet those needs. This course provides a foundation in systems analysis principles and practices, including systems design, systems development, and systems testing. Additionally, the course covers topics such as cloud computing and big data, which are increasingly important in today's data-driven world.
Business Analyst
Business Analyst
Business Analysts work with business stakeholders to understand their business needs and then design and implement solutions to meet those needs. This course provides a foundation in business analysis principles and practices, including business process modeling, business requirements gathering, and business solution design. Additionally, the course covers topics such as cloud computing and big data, which are increasingly important in today's data-driven world.
Data Analyst
Data Analyst
Data Analysts use data to describe and explain business performance. They work with data scientists to analyze data and build models, and then work with business stakeholders to communicate the results of their findings. This course provides a foundation in data analysis principles and practices, including data analysis, data visualization, and data communication. Additionally, the course covers topics such as cloud computing and big data, which are increasingly important in today's data-driven world.
ETL Developer
ETL Developer
ETL Developers design and implement data integration solutions. They work with data engineers to extract, transform, and load data into data warehouses and other data stores. This course provides a foundation in ETL development principles and practices, including data extraction, data transformation, and data loading. Additionally, the course covers topics such as cloud computing and big data, which are increasingly important in today's data-driven world.
Database Designer
Database Designer
Database Designers design and implement databases. They work with database administrators to create and implement databases, and then work with database users to ensure that they have the data they need to do their jobs. This course provides a foundation in database design principles and practices, including database modeling, database normalization, and database optimization. Additionally, the course covers topics such as cloud computing and big data, which are increasingly important in today's data-driven world.
Data Warehouse Architect
Data Warehouse Architect
Data Warehouse Architects design and implement data warehouses. They work with data engineers to create and implement data warehouses, and then work with data analysts and other data users to ensure that they have the data they need to do their jobs. This course provides a foundation in data warehouse architecture principles and practices, including data warehouse design, data warehouse implementation, and data warehouse maintenance. Additionally, the course covers topics such as cloud computing and big data, which are increasingly important in today's data-driven world.
Data Governance Analyst
Data Governance Analyst
Data Governance Analysts develop and implement data governance policies and procedures. They work with data stakeholders to define data governance requirements, and then work with data engineers and other data professionals to implement data governance solutions. This course provides a foundation in data governance principles and practices, including data governance planning, data governance implementation, and data governance monitoring. Additionally, the course covers topics such as cloud computing and big data, which are increasingly important in today's data-driven world.
Data Privacy Analyst
Data Privacy Analyst
Data Privacy Analysts develop and implement data privacy policies and procedures. They work with data stakeholders to define data privacy requirements, and then work with data engineers and other data professionals to implement data privacy solutions. This course provides a foundation in data privacy principles and practices, including data privacy planning, data privacy implementation, and data privacy monitoring. Additionally, the course covers topics such as cloud computing and big data, which are increasingly important in today's data-driven world.
Data Security Analyst
Data Security Analyst
Data Security Analysts develop and implement data security policies and procedures. They work with data stakeholders to define data security requirements, and then work with data engineers and other data professionals to implement data security solutions. This course provides a foundation in data security principles and practices, including data security planning, data security implementation, and data security monitoring. Additionally, the course covers topics such as cloud computing and big data, which are increasingly important in today's data-driven world.
For more career information including salaries, visit:
OpenCourser.com/course/n0yadu/designing
Reading list
We've selected nine 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
Designing data-intensive applications.
Provides a comprehensive overview of the principles and practices of designing and building data-intensive applications. It covers a wide range of topics, including data modeling, storage, processing, and analysis.
Provides an overview of the principles and practices of designing and building scalable data-intensive computing systems. It covers a wide range of topics, including data modeling, storage, processing, and analysis.
Save
Provides a practical guide to designing and building scalable real-time data systems. It covers a wide range of topics, including data modeling, storage, processing, and analysis.
Provides a comprehensive overview of the Hadoop ecosystem. It covers a wide range of topics, including Hadoop architecture, data storage, processing, and analysis.
Provides a comprehensive overview of the Spark ecosystem. It covers a wide range of topics, including Spark architecture, data storage, processing, and analysis.
Provides a comprehensive overview of the MongoDB ecosystem. It covers a wide range of topics, including MongoDB architecture, data storage, processing, and analysis.
Provides a comprehensive overview of the Elasticsearch ecosystem. It covers a wide range of topics, including Elasticsearch architecture, data storage, processing, and analysis.
Provides a comprehensive overview of the Apache Kafka ecosystem. It covers a wide range of topics, including Kafka architecture, data storage, processing, and analysis.
Provides a comprehensive overview of the principles and practices of big data analytics. It covers a wide range of topics, including data mining, machine learning, and data visualization.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/n0yadu/designing
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Level
Intermediate
Via
Coursera
Institution
Universidad Nacional Autónoma de México
Instructor
María del Pilar Ángeles
Language
English
Transcripts
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آذربایجان دیلی
This course belongs to a
collection
called
Database systems. It's comprised of four courses:
- Designing data-intensive applications (viewing)
- Business intelligence and data warehousing
- Relational database systems
- NoSQL systems
Good to know
Covers the full spectrum of data-intensive system designs, including transactional, analytical, alternative, and data lake systems
Offers hands-on labs and interactive materials to reinforce concepts
Builds a strong foundation for understanding data-intensive applications, making it suitable for beginners
Instructs learners on the latest information technologies, ensuring their knowledge is current
Explores both structured and semi-structured data, providing a comprehensive understanding of data types
Requires proficiency in software download and installation, which may be a barrier for some learners
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