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Andrew Brust
An investigation into the convergence of relational SQL database technologies from several vendors and Big Data technologies like Apache Hadoop
This course explains what Big Data, Hadoop and Massively Parallel Processing (MPP) data warehouse technologies are, and how the latter two are converging technologically. Products from Hadapt, Teradata, ParAccel, Microsoft and Cloudera -- all of which integrate with Apache Hadoop -- are investigated
Register for this course and see more details by visiting:
OpenCourser.com/course/4htyqx/sql
What's inside
Syllabus
Introduction
Concepts and Background
Convergence/Hybridization of Hadoop and MPP
Vendors and Their Approaches
Read more
Syllabus
Introduction
Concepts and Background
Convergence/Hybridization of Hadoop and MPP
Vendors and Their Approaches
Read more
Benefits to You
Strategy: What Should You Do?
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Covers different approaches vendors such as Hadapt, Teradata, ParAccel, Microsoft, and Cloudera take to integrate with Apache Hadoop
Investigates convergence of relational SQL database technology and Big Data technologies
Teaches Massively Parallel Processing (MPP) data warehouse technologies and their convergence with Apache Hadoop
Explores what Big Data, Hadoop, and Massively Parallel Processing (MPP) data warehouse technologies are
Develops knowledge about vendor approaches to Apache Hadoop integrations
Investigates how to integrate Hadoop and MPP technologies
Save this course
Save SQL Big Data Convergence - The Big Picture to your list so you can find it easily later:
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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 SQL Big Data Convergence - The Big Picture with these
activities:
Review databases
Show steps
Review the fundamentals of database systems, including data models, query languages, and database design.
Browse courses on
Database Systems
Show steps
-
Review notes and textbooks from previous database courses.
-
Complete practice problems and exercises on basic database concepts.
-
Attend a refresher workshop or online course on database fundamentals.
Read 'Hadoop: The Definitive Guide'
Show steps
Gain a comprehensive understanding of Hadoop's architecture, components, and applications.
View
Hadoop: The Definitive Guide: Storage and...
on Amazon
Show steps
-
Read and understand the chapters covering Hadoop's core concepts.
-
Focus on chapters that discuss data storage, processing, and analysis using Hadoop.
-
Refer to the book for additional insights and examples during your course assignments and projects.
Join a Hadoop and MPP study group
Show steps
Connect with other students or professionals to discuss Hadoop and MPP concepts, share experiences, and collaborate on projects.
Browse courses on
Hadoop
Show steps
-
Identify or create a study group focused on Hadoop and MPP.
-
Meet regularly to discuss course materials, assignments, and industry trends.
-
Collaborate on projects or case studies to apply Hadoop and MPP technologies.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Follow tutorials on Hadoop and MPP
Show steps
Explore the concepts and practical applications of Hadoop and Massively Parallel Processing (MPP) data warehouse technologies.
Browse courses on
Hadoop
Show steps
-
Identify reputable online tutorials or courses on Hadoop and MPP.
-
Follow the tutorials step-by-step, completing all exercises and assignments.
-
Experiment with Hadoop and MPP technologies using a cloud-based platform or local sandbox environment.
Solve Hadoop and MPP exercises
Show steps
Reinforce your understanding of Hadoop and MPP concepts by solving practice exercises and problems.
Browse courses on
Hadoop
Show steps
-
Find online resources or textbooks that provide Hadoop and MPP exercises.
-
Attempt to solve the exercises independently, referring to course materials or online documentation as needed.
-
Review your solutions and identify areas for improvement.
Create a Hadoop and MPP resource collection
Show steps
Gather and organize useful resources related to Hadoop and MPP technologies.
Browse courses on
Hadoop
Show steps
-
Identify and collect articles, tutorials, videos, and other materials on Hadoop and MPP.
-
Organize the resources into categories or topics.
-
Share your resource collection with classmates and other professionals.
Design a data warehouse architecture
Show steps
Apply the concepts of Hadoop and MPP to design a data warehouse architecture that meets specific business requirements.
Browse courses on
Data Warehousing
Show steps
-
Gather requirements and define the scope of the data warehouse.
-
Select and justify the appropriate Hadoop or MPP technology stack.
-
Design the data model, including tables, columns, and relationships.
-
Develop a data ingestion and processing strategy.
-
Create a prototype or proof-of-concept implementation.
Contribute to open-source Hadoop or MPP projects
Show steps
Gain hands-on experience with Hadoop and MPP technologies by contributing to open-source projects.
Browse courses on
Hadoop
Show steps
-
Identify open-source Hadoop or MPP projects that align with your interests.
-
Review the project documentation and contribute to bug fixes, feature enhancements, or documentation updates.
-
Engage with the project community to learn best practices and stay up-to-date with the latest developments.
Review databases
Show steps
Review the fundamentals of database systems, including data models, query languages, and database design.
Browse courses on
Database Systems
Show steps
Show steps
Show steps
- Review notes and textbooks from previous database courses.
- Complete practice problems and exercises on basic database concepts.
- Attend a refresher workshop or online course on database fundamentals.
Read 'Hadoop: The Definitive Guide'
Show steps
Gain a comprehensive understanding of Hadoop's architecture, components, and applications.
View
Hadoop: The Definitive Guide: Storage and...
on Amazon
Show steps
Show steps
Show steps
- Read and understand the chapters covering Hadoop's core concepts.
- Focus on chapters that discuss data storage, processing, and analysis using Hadoop.
- Refer to the book for additional insights and examples during your course assignments and projects.
Join a Hadoop and MPP study group
Show steps
Connect with other students or professionals to discuss Hadoop and MPP concepts, share experiences, and collaborate on projects.
Browse courses on
Hadoop
Show steps
Show steps
Show steps
- Identify or create a study group focused on Hadoop and MPP.
- Meet regularly to discuss course materials, assignments, and industry trends.
- Collaborate on projects or case studies to apply Hadoop and MPP technologies.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Follow tutorials on Hadoop and MPP
Show steps
Explore the concepts and practical applications of Hadoop and Massively Parallel Processing (MPP) data warehouse technologies.
Browse courses on
Hadoop
Show steps
Show steps
Show steps
- Identify reputable online tutorials or courses on Hadoop and MPP.
- Follow the tutorials step-by-step, completing all exercises and assignments.
- Experiment with Hadoop and MPP technologies using a cloud-based platform or local sandbox environment.
Solve Hadoop and MPP exercises
Show steps
Reinforce your understanding of Hadoop and MPP concepts by solving practice exercises and problems.
Browse courses on
Hadoop
Show steps
Show steps
Show steps
- Find online resources or textbooks that provide Hadoop and MPP exercises.
- Attempt to solve the exercises independently, referring to course materials or online documentation as needed.
- Review your solutions and identify areas for improvement.
Create a Hadoop and MPP resource collection
Show steps
Gather and organize useful resources related to Hadoop and MPP technologies.
Browse courses on
Hadoop
Show steps
Show steps
Show steps
- Identify and collect articles, tutorials, videos, and other materials on Hadoop and MPP.
- Organize the resources into categories or topics.
- Share your resource collection with classmates and other professionals.
Design a data warehouse architecture
Show steps
Apply the concepts of Hadoop and MPP to design a data warehouse architecture that meets specific business requirements.
Browse courses on
Data Warehousing
Show steps
Show steps
Show steps
- Gather requirements and define the scope of the data warehouse.
- Select and justify the appropriate Hadoop or MPP technology stack.
- Design the data model, including tables, columns, and relationships.
- Develop a data ingestion and processing strategy.
- Create a prototype or proof-of-concept implementation.
Contribute to open-source Hadoop or MPP projects
Show steps
Gain hands-on experience with Hadoop and MPP technologies by contributing to open-source projects.
Browse courses on
Hadoop
Show steps
Show steps
Show steps
- Identify open-source Hadoop or MPP projects that align with your interests.
- Review the project documentation and contribute to bug fixes, feature enhancements, or documentation updates.
- Engage with the project community to learn best practices and stay up-to-date with the latest developments.
Career center
Learners who complete SQL Big Data Convergence - The Big Picture will develop knowledge and skills
that may be useful to these careers:
MPP Developer
MPP Developer
A MPP Developer designs, develops, and deploys MPP applications. MPP Developers may work with a variety of MPP technologies, including Greenplum, Vertica, and ParAccel. This course may be useful for a MPP Developer who wants to learn more about the convergence of relational SQL database technologies and Big Data technologies. The course can help MPP Developers understand how to use Hadoop and MPP data warehouse technologies to build and deploy MPP applications on large-scale data sets.
Chief Data Officer
Chief Data Officer
A Chief Data Officer (CDO) is responsible for the overall data strategy and governance within an organization. CDOs may work with a variety of data technologies, including relational databases, Big Data technologies, and cloud computing platforms. This course may be useful for a CDO who wants to learn more about the convergence of relational SQL database technologies and Big Data technologies. The course can help CDOs understand how to use Hadoop and MPP data warehouse technologies to build and manage data strategies and governance frameworks on large-scale data sets.
Data Governance Analyst
Data Governance Analyst
A Data Governance Analyst designs and implements data governance policies and procedures. Data Governance Analysts may work with a variety of data technologies, including relational databases, Big Data technologies, and cloud computing platforms. This course may be useful for a Data Governance Analyst who wants to learn more about the convergence of relational SQL database technologies and Big Data technologies, and understands how to use the two together. The course can help Data Governance Analysts understand how to use Hadoop and MPP data warehouse technologies to build and implement data governance policies and procedures on large-scale data sets.
Cloud Data Engineer
Cloud Data Engineer
A Cloud Data Engineer designs, builds, and manages cloud data platforms. Cloud Data Engineers may work with a variety of cloud computing platforms, including AWS, Azure, and GCP. This course may be useful for a Cloud Data Engineer who wants to learn more about the convergence of relational SQL database technologies and Big Data technologies, and understands how to use the two together. The course can help Cloud Data Engineers understand how to use Hadoop and MPP data warehouse technologies to build and manage cloud data platforms on large-scale data sets.
Data Integration Engineer
Data Integration Engineer
A Data Integration Engineer designs, develops, and deploys data integration solutions. Data Integration Engineers may work with a variety of data integration technologies, including ETL tools, data virtualization tools, and big data integration tools. This course may be useful for a Data Integration Engineer who wants to learn more about the convergence of relational SQL database technologies and Big Data technologies. The course can help Data Integration Engineers understand how to use Hadoop and MPP data warehouse technologies to build and deploy data integration solutions on large-scale data sets.
Hadoop Developer
Hadoop Developer
A Hadoop Developer designs, develops, and deploys Hadoop applications. Hadoop Developers may work with a variety of Hadoop technologies, including MapReduce, Hive, and Pig. This course may be useful for a Hadoop Developer who wants to learn more about the convergence of relational SQL database technologies and Big Data technologies, and understands how to use the two together. The course can help Hadoop Developers understand how to use Hadoop and MPP data warehouse technologies to build and deploy Hadoop applications on large-scale data sets.
Data Privacy Analyst
Data Privacy Analyst
A Data Privacy Analyst designs and implements data privacy policies and procedures. Data Privacy Analysts may work with a variety of data technologies, including relational databases, Big Data technologies, and cloud computing platforms. This course may be useful for a Data Privacy Analyst who wants to learn more about the convergence of relational SQL database technologies and Big Data technologies. The course can help Data Privacy Analysts understand how to use Hadoop and MPP data warehouse technologies to build and implement data privacy policies and procedures on large-scale data sets.
Big Data Engineer
Big Data Engineer
A Big Data Engineer designs, builds, and manages big data systems. Big Data Engineers may work with a variety of big data technologies, including Hadoop, NoSQL databases, and cloud computing platforms. This course may be useful for a Big Data Engineer who wants to learn more about the convergence of relational SQL database technologies and Big Data technologies. The course can help Big Data Engineers understand how to use Hadoop and MPP data warehouse technologies to build and manage big data systems.
Data Security Analyst
Data Security Analyst
A Data Security Analyst designs and implements data security policies and procedures. Data Security Analysts may work with a variety of data technologies, including relational databases, Big Data technologies, and cloud computing platforms. This course may be useful for a Data Security Analyst who wants to learn more about the convergence of relational SQL database technologies and Big Data technologies. The course can help Data Security Analysts understand how to use Hadoop and MPP data warehouse technologies to build and implement data security policies and procedures on large-scale data sets.
Data Quality Analyst
Data Quality Analyst
A Data Quality Analyst designs and implements data quality policies and procedures. Data Quality Analysts may work with a variety of data technologies, including relational databases, Big Data technologies, and cloud computing platforms. This course may be useful for a Data Quality Analyst who wants to learn more about the convergence of relational SQL database technologies and Big Data technologies. The course can help Data Quality Analysts understand how to use Hadoop and MPP data warehouse technologies to build and implement data quality policies and procedures on large-scale data sets.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer designs, develops, and deploys machine learning models. Machine Learning Engineers may work with a variety of data sources, including relational databases, Big Data technologies, and social media data. This course may be useful for a Machine Learning Engineer who wants to learn more about the convergence of relational SQL database technologies and Big Data technologies. The course can help Machine Learning Engineers understand how to use Hadoop and MPP data warehouse technologies to build and deploy machine learning models on large-scale data sets.
Data Scientist
Data Scientist
A Data Scientist uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from data. Data Scientists may work with a variety of data sources, including relational databases, Big Data technologies, and social media data. This course may be useful for a Data Scientist who wants to learn more about the convergence of relational SQL database technologies and Big Data technologies. The course can help Data Scientists understand how to use Hadoop and MPP data warehouse technologies to extract knowledge and insights from large-scale data sets.
Data Analyst
Data Analyst
A Data Analyst collects, analyzes, and interprets data to help businesses make informed decisions. Data Analysts may work with a variety of data sources, including relational databases, Big Data technologies, and social media data. This course may be useful for a Data Analyst who wants to learn more about the convergence of relational SQL database technologies and Big Data technologies. The course can help Data Analysts understand how to use Hadoop and MPP data warehouse technologies to collect, analyze, and interpret large-scale data sets.
Database Administrator
Database Administrator
A Database Administrator (DBA) manages and maintains the database systems within an organization. This includes installing, configuring, and monitoring databases, as well as performing backups and recoveries. A DBA may also work with developers to design and implement new database solutions. This course may be useful for a DBA who wants to learn more about the convergence of relational SQL database technologies and Big Data technologies. The course can help DBAs understand how to use Hadoop and MPP data warehouse technologies to manage and maintain large-scale data systems.
Data Architect
Data Architect
A Data Architect designs, manages, and implements a data architecture that meets the needs of the business. A Data Architect may also convert business requirements into logical and physical data models. This course may be useful for a Data Architect who wants to learn more about the convergence of relational SQL database technologies and Big Data technologies. The course can help Data Architects understand how to use Hadoop and MPP data warehouse technologies to build and manage data architectures.
For more career information including salaries, visit:
OpenCourser.com/course/4htyqx/sql
Reading list
We've selected 11 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
SQL Big Data Convergence - The Big Picture.
Comprehensive guide to Hadoop, providing a thorough overview of the platform and its components. It is particularly useful for those who are new to Hadoop or who want to deepen their understanding of the technology.
Save
A practical guide to implementing and managing big data systems using Apache Hadoop and other technologies. It offers insights into data processing, data analysis, and real-time data streaming.
Save
Provides a practical guide to using Hadoop, covering topics such as data ingestion, data storage, data processing, and data analysis. It valuable resource for those who want to learn how to use Hadoop to solve real-world problems.
A comprehensive book on MongoDB, a popular NoSQL database. It covers the core concepts, features, and uses of MongoDB.
A guide to building data pipelines using Apache Kafka. It covers the architecture, design, and implementation of Kafka-based data pipelines.
Provides a comprehensive overview of SQL performance, covering topics such as query optimization, indexing, and caching. It valuable resource for those who want to learn how to improve the performance of their SQL queries.
Save
Provides a comprehensive overview of SQL tuning, covering topics such as query optimization, indexing, and caching. It valuable resource for those who want to learn how to improve the performance of their SQL queries.
A comprehensive overview of data science and big data analytics. It covers the fundamentals of data science, big data, and data analytics.
A practical guide to using Python for artificial intelligence tasks. It covers data preprocessing, model building, and model evaluation.
Provides a comprehensive overview of PostgreSQL 9.6, covering topics such as data types, tables, queries, and subqueries. It valuable resource for those who want to learn how to use PostgreSQL 9.6 to manage and analyze data.
A practical guide to using Python for deep learning. It covers neural networks, convolutional neural networks, and recurrent neural networks.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/4htyqx/sql
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Time
81 hours
Level
Intermediate
Via
Pluralsight
Instructor
Andrew Brust
Language
English
Good to know
Covers different approaches vendors such as Hadapt, Teradata, ParAccel, Microsoft, and Cloudera take to integrate with Apache Hadoop
Investigates convergence of relational SQL database technology and Big Data technologies
Teaches Massively Parallel Processing (MPP) data warehouse technologies and their convergence with Apache Hadoop
Explores what Big Data, Hadoop, and Massively Parallel Processing (MPP) data warehouse technologies are
Develops knowledge about vendor approaches to Apache Hadoop integrations
Investigates how to integrate Hadoop and MPP technologies
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