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Microsoft Azure Data Fundamentals DP-900/Acronyms/Part 2

Acronym study

DP-900 Acronyms — Part 2 of 5

Terms 31–60 of 136 DP-900 acronyms and key terms. Each entry includes a plain-English definition and a link to the full 800-word glossary page with exam context and practice questions.

← Part 1Part 2 of 5Part 3 →

Term 31

Cosmos DB API

Cosmos DB API is a collection of interfaces that lets applications interact with Azure Cosmos DB, a globally distributed NoSQL database, using different data models and query languages.

Full entry →
Full Cosmos DB API glossary entry →

Term 32

Cross-Region Replication

Cross-Region Replication is the automated copying of data from a storage bucket in one geographic region to a bucket in a different geographic region for disaster recovery, compliance, or lower latency access.

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Full Cross-Region Replication glossary entry →

Term 33

Dashboard

A dashboard is a visual display of key metrics and data points that helps IT professionals monitor, analyze, and manage systems or processes in real time.

Full entry →
Full Dashboard glossary entry →

Term 34

Data

Data is raw, unprocessed information, like numbers, words, or measurements, that can be stored, processed, and analyzed by computers.

Full entry →
Full Data glossary entry →

Term 35

Data catalog

A data catalog is a centralized inventory of data assets that helps people find, understand, and trust the data they need for analytics or business decisions.

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Full Data catalog glossary entry →

Term 36

Data Center Interconnect

A Data Center Interconnect is a network connection that links two or more separate data centers together so they can share data, resources, and services as if they were a single facility.

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Full Data Center Interconnect glossary entry →

Term 37

Data classification

Data classification is the process of organizing data into categories based on its sensitivity, value, and criticality to an organization, so that appropriate security controls can be applied.

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Full Data classification glossary entry →

Term 38

Data governance

Data governance is the overall process of managing the availability, usability, integrity, and security of data used in an organization, based on internal standards and policies.

Full entry →
Full Data governance glossary entry →

Term 39

Data ingestion

Data ingestion is the process of moving data from various sources into a storage system where it can be accessed, analyzed, and used.

Full entry →
Full Data ingestion glossary entry →

Term 40

Data lake

A data lake is a centralized storage repository that holds vast amounts of raw data in its native format until it is needed for analysis.

Full entry →
Full Data lake glossary entry →

Term 41

Data Lake Storage Gen2

Data Lake Storage Gen2 is a cloud-based storage service that combines a scalable data lake with enterprise-grade file system capabilities for big data analytics.

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Full Data Lake Storage Gen2 glossary entry →

Term 42

Data lakehouse

A data lakehouse is a modern data architecture that combines the flexibility of a data lake with the reliability and performance of a data warehouse on a single platform.

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Full Data lakehouse glossary entry →

Term 43

Data Lifecycle Manager

A Data Lifecycle Manager is a system or set of policies that automates the movement, protection, retention, and deletion of data from creation to disposal, ensuring compliance and efficient storage usage.

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Full Data Lifecycle Manager glossary entry →

Term 44

Data lineage

Data lineage is the process of tracking the origin, movement, and transformation of data as it flows through various systems and steps in a data pipeline.

Full entry →
Full Data lineage glossary entry →

Term 45

Data model

A data model is a blueprint that defines how data is organized, stored, and accessed in a database or data system.

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Full Data model glossary entry →

Term 46

Data retention

Data retention is the practice of keeping data for a specific period to meet legal, business, or compliance needs, and then securely disposing of it.

Full entry →
Full Data retention glossary entry →

Term 47

Data security

Data security is the practice of protecting digital information from unauthorized access, corruption, or theft throughout its lifecycle.

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Full Data security glossary entry →

Term 48

Data transformation

Data transformation is the process of converting data from one format, structure, or value into another to make it usable for analysis, storage, or reporting.

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Full Data transformation glossary entry →

Term 49

Data visualization

Data visualization is the practice of translating data and information into visual context, such as charts and graphs, to make complex data easier to understand and use for decision-making.

Full entry →
Full Data visualization glossary entry →

Term 50

Data warehouse

A data warehouse is a central repository that stores large amounts of structured data from multiple sources, optimized for querying and analysis rather than day-to-day transactions.

Full entry →
Full Data warehouse glossary entry →

Term 51

Dataproc

Dataproc is a managed cloud service for running Apache Spark and Apache Hadoop clusters, allowing you to process large datasets quickly and economically.

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Full Dataproc glossary entry →

Term 52

Dataset

A dataset is a collection of related data, usually in a structured format, that can be used for analysis, training models, or reporting in Azure data services.

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Full Dataset glossary entry →

Term 53

Datastream

A datastream is a continuous, ordered flow of data that is generated and transmitted from a source to a destination for real-time processing or analysis.

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Full Datastream glossary entry →

Term 54

DAX

DAX (DynamoDB Accelerator) is a fully managed, highly available, in-memory cache for Amazon DynamoDB that provides microsecond read latency.

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Full DAX glossary entry →

Term 55

Dedicated SQL pool

A Dedicated SQL pool is a cloud-based analytics service in Azure Synapse Analytics that provides a managed, scalable environment for running large-scale data warehousing queries using Transact-SQL.

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Full Dedicated SQL pool glossary entry →

Term 56

Denormalization

Denormalization is a database design strategy that adds redundant data to one or more tables to reduce the number of joins needed in queries, improving read performance at the cost of extra storage and more complex writes.

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Full Denormalization glossary entry →

Term 57

DocumentDB

Amazon DocumentDB is a fully managed, MongoDB-compatible document database service that stores, queries, and indexes JSON-like data for scalable applications.

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Full DocumentDB glossary entry →

Term 58

EBS encryption

EBS encryption is a security feature that automatically encrypts data stored on Amazon Elastic Block Store volumes, protecting it at rest and in transit between the volume and the attached EC2 instance.

Full entry →
Full EBS encryption glossary entry →

Term 59

EBS snapshot

An EBS snapshot is a point-in-time backup of an Amazon Elastic Block Store volume that you can use for recovery, cloning, or migration.

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Full EBS snapshot glossary entry →

Term 60

EBS volume types

Amazon Elastic Block Store (EBS) volume types are different categories of block-level storage volumes optimized for specific performance, cost, and use case requirements in the AWS cloud.

Full entry →
Full EBS volume types glossary entry →
← Part 1Part 3 →

Acronym parts

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Study resources

All DP-900 Acronyms→DP-900 Practice Tests→DP-900 Study Guide→Exam Domains→