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Graph Databases
Gremlin API
Common Data Problems
Azure Cosmos DB
Data Modeling
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OpenCourser.com/course/thvq6w/common
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Targeted to learners who want to solve common business data problems, making it useful for professionals in a variety of industries
Provides practical examples of how to use graph databases to solve real-world problems
Taught by Chad Green, an expert in the use of graph databases
Involves using the Gremlin API within Azure Cosmos DB, which is a popular graph database platform
Useful for learners who want to gain a better understanding of graph databases and their applications
Requires learners to have some familiarity with data modeling and database concepts
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Common Data Problems Solved with Graphs: CodeMash.
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Career center
Learners who complete Common Data Problems Solved with Graphs: CodeMash will develop knowledge and skills
that may be useful to these careers:
Data Engineer
Data Engineer
Data Engineers design and implement data pipelines that move data from source systems to data warehouses and other data stores. This course provides a foundation in using graph databases and the Gremlin API to store and retrieve data. This knowledge can be useful for designing and implementing data pipelines that handle complex and interconnected datasets.
Data Architect
Data Architect
Data Architects design and implement data management solutions, working with stakeholders to understand their needs and develop a data strategy. This course teaches how to use graph databases to store and retrieve data. This knowledge is useful for designing and implementing data solutions that handle complex and interconnected data.
Data Scientist
Data Scientist
Data Scientists use scientific methods, processes, algorithms, and systems to extract knowledge and insights from data in various forms, both structured and unstructured. This course helps build a foundation for this role by providing an understanding of how to use graph databases to store and retrieve complex and interconnected datasets.
Database Designer
Database Designer
Database Designers create and maintain the structure of databases, ensuring data is stored and organized efficiently. This course provides a foundation for this role by teaching how to use graph databases to store and retrieve data in a way that models real-world relationships.
Data Warehouse Architect
Data Warehouse Architect
Data Warehouse Architects design and implement data warehouses, working with stakeholders to understand their needs and develop a data strategy. This course teaches how to use graph databases to store and retrieve data. This knowledge is useful for designing and implementing data warehouses that handle complex and interconnected data.
Data Analyst
Data Analyst
Data Analysts collect, clean, and analyze data to identify trends and patterns. The insights they provide can be used to make informed business decisions. This course teaches how to use graph databases to store and retrieve data, which can be useful for analyzing complex and interconnected datasets. This skill is in high demand for Data Analysts working with big data.
Business Intelligence Analyst
Business Intelligence Analyst
Business Intelligence Analysts gather and analyze data to identify trends and patterns. The insights they provide can be used to make informed business decisions. This course teaches how to use graph databases to store and retrieve data, which can be useful for analyzing complex and interconnected datasets. This skill is in high demand for Business Intelligence Analysts working with big data.
Software Engineer
Software Engineer
Software Engineers design, develop, test, and maintain software systems. This course provides a foundation for this role by teaching how to use graph databases to store and retrieve data in a way that models real-world relationships. This knowledge is applicable to building software systems that handle complex and interconnected data.
Systems Analyst
Systems Analyst
Systems Analysts analyze and design business systems, working with users and stakeholders to understand their needs and develop solutions. This course teaches how to use graph databases to store and retrieve data. This skill is useful for analyzing and designing business systems that handle complex and interconnected data.
Information Architect
Information Architect
Information Architects design and organize information systems, working with stakeholders to understand their needs and develop solutions. This course teaches how to use graph databases to store and retrieve data. This knowledge is useful for designing and organizing information systems that handle complex and interconnected data.
Database Administrator
Database Administrator
Database Administrators oversee all database management operations, which include database design, database security, storage management, maintenance, and performance tuning. This course helps build a foundation for this role by providing an understanding of how to store and retrieve data using graph databases and the Gremlin API. This can be useful for managing complex and interconnected datasets commonly found in enterprise environments.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, develop, and deploy machine learning models. This course may be useful for Machine Learning Engineers who need to use graph databases to store and retrieve data for training and deploying machine learning models.
Data Science Manager
Data Science Manager
Data Science Managers lead teams of data scientists and oversee data science projects. This course may be useful for Data Science Managers who need to understand how to use graph databases to store and retrieve data for data science projects.
Product Manager
Product Manager
Product Managers lead the development and launch of new products and features. This course may be useful for Product Managers who need to understand how to use graph databases to store and retrieve data for product development and marketing.
Technical Writer
Technical Writer
Technical Writers create and maintain technical documentation, such as user manuals, white papers, and knowledge base articles. This course may be useful for Technical Writers who need to document how to use graph databases and the Gremlin API to store and retrieve data.
For more career information including salaries, visit:
OpenCourser.com/course/thvq6w/common
Reading list
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Provides a comprehensive overview of graph databases, covering the basics of graph theory, different types of graph databases, and how to use them effectively.
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Provides a step-by-step guide to using Neo4j, one of the most popular graph databases.
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Provides a simplified approach to the topic of graph databases, ideal for beginners or non-technical readers.
Explores the theoretical foundations of graph theory, providing a solid understanding of graph structures and algorithms.
Provides a detailed examination of graph algorithms and their applications, particularly in the context of computer science.
This practical guide focuses on using the Python programming language to work with graph databases, specifically Neo4j.
This beginner-friendly guide provides a clear and concise introduction to graph databases, making it accessible to individuals with no prior knowledge.
Collection of recipes for solving common problems with Azure Cosmos DB. It covers a wide range of topics, including data modeling, performance tuning, and security. The author is an Azure Cosmos DB engineer at Microsoft, and he provides practical advice and best practices.
Focuses on aligning data modeling with business needs and strategy. It emphasizes the importance of involving business stakeholders in the modeling process and provides techniques for creating high-level data models that have significant business impact. It's particularly relevant for business analysts and data professionals working closely with business teams.
Does a good job in providing a thorough introduction to data modeling and database design. It describes the different data modeling techniques and provides a step-by-step guide on how to create a data model. It is helpful for those who want to learn the basics of data modeling and database design and how to apply them in practice.
Provides a practical approach to data modeling. It does not go too much into the theoretical details but instead focuses on providing a step-by-step guide on how to create a data model. It covers the different types of data models and how to use them, as well as how to design and implement a database.
Is not a beginner's guide; rather, it deals with deeper topics within data modeling and database design. It covers advanced topics such as dimensional modeling, data warehousing, and performance tuning with real-world case studies.
Focuses on data modeling using Microsoft SQL Server 2012. It covers the different features of SQL Server 2012 that can be used for data modeling, such as the new table types and columnstore indexes. It also provides a step-by-step guide on how to create a data model in SQL Server 2012.
Focuses on data modeling using MongoDB. It covers the different features of MongoDB that can be used for data modeling, such as the new table types and columnstore indexes. It also provides a step-by-step guide on how to create a data model in MongoDB.
Is an introduction to data modeling with UML. It covers the different types of UML diagrams and how to use them to create a data model. It also provides a step-by-step guide on how to create a data model using UML.
Is an excellent starting point for anyone new to data modeling. It covers the fundamental concepts, including conceptual, logical, and physical data models, and provides practical guidance for gathering requirements and building models. It's often recommended as a foundational text for beginners and is suitable for high school students through working professionals seeking a broad understanding.
A cornerstone in data warehousing, this book focuses on dimensional modeling, a key technique for designing analytical databases. It's essential for anyone working with data warehouses or business intelligence, providing detailed patterns and case studies across various industries. is highly valuable for undergraduate students and professionals specializing in data analytics and warehousing.
Considered a classic introduction to data modeling, this book provides a comprehensive overview of the principles and techniques. It delves into the 'what' and 'why' of data modeling, making it suitable for students and professionals who want to solidify their foundational knowledge. It is often used as a textbook.
Offers a rigorous approach to logical database design, covering various data models and their translation into relational schemas. It's a good resource for those seeking a deeper, more theoretical understanding of data modeling principles. It is particularly useful for undergraduate and graduate students in computer science and related fields.
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Explores reusable data model patterns for common business structures. It helps in applying data modeling rules in an enterprise context and provides high-level models for various business areas. This valuable resource for experienced modelers and professionals looking for proven solutions to recurring modeling challenges.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/thvq6w/common
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