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Data Storage and Queries

In this course, you will learn about the raw ingredients and processes that are used to physically store data on disk and in memory. You’ll explore different storage systems, including object, block, and file storage, as well as databases, that are built on top of these raw ingredients. You’ll also get a chance to use the Cypher language to query a Neo4j graph database, and perform vector similarity search, a key feature behind generative AI and large language models. You will explore the evolution of data storage abstractions, from data warehouses, to data lakes, and data lakehouses, while comparing the advantages and drawbacks of each architectural paradigm. With hands-on practice, you will design a simple data lake using Amazon Glue, and build a data lakehouse using AWS LakeFormation and Apache Iceberg. In the last week of this course, you’ll see how queries work behind the scenes, practice writing more advanced SQL queries, compare the query performance in row vs column-oriented storage, and perform streaming queries using Apache Flink.
Duration 4 Months
Institution DeepLearning.AI
Format Online

Eligibility Criteria

school

Academic Foundation

A recognized Bachelor’s degree or high school equivalent required for admission into DeepLearning.AI.

language

Language Proficiency

English proficiency required. IELTS, TOEFL, or standard medium-of-instruction certificates accepted.

Detailed Fees Breakdown

Base Tuition Fee $269
Total Est. Investment $269

Scholarships and early-bird waivers may apply. Contact admissions for exact institutional fees.

Academic Trajectory

Program Outcome

Graduates of the Data Storage and Queries program at DeepLearning.AI are equipped with global perspectives, ready to excel in international markets and top-tier career opportunities.

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