Johns Hopkins University
Large-Scale Database Systems Specialization
Johns Hopkins University

Large-Scale Database Systems Specialization

Master Distributed Databases and Cloud Analytics. Gain advanced skills in distributed database systems, cloud computing, data reliability, and machine learning to design and optimize large-scale data solutions.

David Silberberg

Instructor: David Silberberg

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Get in-depth knowledge of a subject
Intermediate level

Recommended experience

12 weeks to complete
at 5 hours a week
Flexible schedule
Learn at your own pace
Earn a Certificate
With paid plans
Get in-depth knowledge of a subject
Intermediate level

Recommended experience

12 weeks to complete
at 5 hours a week
Flexible schedule
Learn at your own pace
Earn a Certificate
With paid plans

What you'll learn

  • Master database systems, including transaction management, query optimization, and data warehousing principles for large-scale environments.

  • Develop proficiency in cloud computing concepts, using Hadoop and Accumulo for data processing and storage in distributed systems.

  • Apply machine learning techniques such as clustering and collaborative filtering to analyze big data and enhance system reliability.

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Taught in English
26 practice exercises

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  • Develop a deep understanding of key concepts
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Specialization - 3 course series

What you'll learn

  • Understand distributed database architectures and translate SQL queries into relational algebra expressions for optimization.

  • Apply horizontal partitioning techniques to enhance database performance and scalability based on query patterns.

  • Implement vertical partitioning strategies to improve query response times and manage data more efficiently in distributed systems.

Skills you'll gain

Distributed Computing, Database Architecture and Administration, Database Design, Scalability, Database Systems, Database Management, Performance Tuning, Data Integrity, SQL, Database Management Systems, Relational Databases, Query Languages, and Databases

What you'll learn

  • Learners will gain skills in implementing database security through views, dynamic authorization, and semantic integrity rules.

  • Students will understand query optimization techniques, cost evaluation, and the creation of optimized query plans to enhance database performance.

  • Learners will master distributed query optimization, using cost models, MapReduce, and HDFS for efficient data storage, compression, and processing.

Skills you'll gain

Distributed Computing, Data Storage Technologies, Big Data, Data Access, Apache Hadoop, Database Architecture and Administration, Query Languages, Databases, Algorithms, Data Integrity, Data Processing, SQL, and Performance Tuning

What you'll learn

  • Learn transaction management principles, including ACID properties, concurrency control, and deadlock management techniques for distributed systems.

  • Explore reliability protocols, recovery algorithms, and commit protocols like ARIES, ensuring data consistency and durability.

  • Understand cloud computing with Hadoop, utilizing MapReduce for large-scale data processing, and apply machine learning techniques like clustering.

Skills you'll gain

Transaction Processing, Cloud Computing, Apache Hadoop, Scalability, Data Warehousing, Machine Learning, Database Architecture and Administration, Data Processing, Distributed Computing, Disaster Recovery, Database Systems, Relational Databases, Data Integrity, and Big Data

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Instructor

David Silberberg
Johns Hopkins University
3 Courses714 learners

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