Azure Data Explorer Flashcards
What is Azure Data Explorer?
- Fully managed data analytics service.
- For real-time analysis of large volumes of data.
- Suited for time series data
What are the three primary use cases for Azure Data Explorer?
- Log and telemetry data analysis
- Real-time data exploration
- Big data analytics.
What are four of the data sources Azure Data Explorer ingest from?
- Event Hub,
- Blob Storage,
- IoT Hub
- databases.
Explain how Azure Data Explorer stores its data.
- In a distributed columnar storage format
- optimized for high-performance querying
- Data at rest and memory is compression.
What is the query language used in Azure Data Explorer and what is it used for?
KQL is used to query data in Azure Data Explorer for real-time analysis.
Explain data retention in Azure Data Explorer?
Data can be retained for specific durations based on retention policies, allowing for time-bound data storage.
Explain how Azure Data Explorer scales?
It can scale horizontally by adding nodes and scale vertically by upgrading storage and compute resources.
Explain Azure Data Explorer security?
- Azure Active Directory (AAD) authentication
- RBAC for role-based access control (RBAC)
- Encryption at rest
- Encryption for data in transit
List Azure Data Explorer integrate with other Azure services?
It integrates with services such as Power BI, Azure Synapse, Azure Machine Learning, and Logic Apps.
What is the purpose of the Hot and Cold storage in Azure Data Explorer?
Hot storage is for fast query performance, while cold storage is for long-term retention of data at a lower cost.
How is disaster recovery implemented in Azure Data Explorer?
Azure Data Explorer supports geo-redundancy and automated backups to ensure disaster recovery.
How is governance implemented in Azure Data Explorer?
It includes features like access control, auditing, and data classification for governance.
How can data be ingested from IoT Hub into Azure Data Explorer?
IoT Hub data is ingested using a built-in connector that sends telemetry data directly into Azure Data Explorer.
What is the function of a cluster in Azure Data Explorer?
A cluster is a set of virtual machines that process and store data for querying in Azure Data Explorer.
What are the primary functions provided by Azure Data Explorer?
Real-time analytics, data exploration, monitoring, and alerting on large data volumes.
What types of data can be analyzed using Azure Data Explorer?
Azure Data Explorer can analyze structured, semi-structured, and unstructured data.
What is the role of data sharding in Azure Data Explorer?
Data sharding distributes data across multiple nodes for faster query processing and scalability.
How does Azure Data Explorer handle high availability?
High availability is achieved through cluster redundancy and automatic failover.
What is the purpose of Kusto Triggers in Azure Data Explorer?
Kusto Triggers are used to automate actions based on query results, such as sending alerts.
How does Azure Data Explorer optimize query performance?
It uses a columnar storage format, indexing, and data partitioning to optimize query performance.
What is the role of the ingestion batching policy in Azure Data Explorer?
Ingestion batching policy defines how frequently data is ingested based on volume and time thresholds.
What is the role of RBAC in Azure Data Explorer?
RBAC allows fine-grained control over data and resource access within the service.
How does Azure Data Explorer provide real-time analytics?
It ingests and queries data in real time, allowing for instant insights from logs and telemetry data.
What is the retention policy in Azure Data Explorer?
Retention policies allow data to be stored for a predefined period, after which it is purged.
How does Azure Data Explorer handle schema evolution?
It allows flexible schema updates to accommodate changes in data structure without downtime.
What is the role of Continuous Data Export in Azure Data Explorer?
It allows data to be continuously exported to other storage solutions like Blob Storage for archival or further processing.
How is data encrypted in Azure Data Explorer?
Data is encrypted at rest using Microsoft-managed or customer-managed keys, and encrypted in transit using TLS.
What is the difference between a table and a database in Azure Data Explorer?
A database stores multiple tables, each containing specific types of data for querying.
How does Azure Data Explorer support time-series analysis?
It has built-in support for time-series data with functions to analyze trends, anomalies, and forecasts.
What is the purpose of indexing in Azure Data Explorer?
Indexing improves query performance by creating searchable fields in the stored data.
What is the role of ingestion control commands in Azure Data Explorer?
These commands allow control over data ingestion processes, such as pausing or resuming ingestion pipelines.
What is the role of diagnostic logs in Azure Data Explorer?
Diagnostic logs provide insights into cluster performance and resource usage for troubleshooting.
How can Azure Data Explorer be integrated with Azure Synapse?
Azure Data Explorer can serve as a data source for Azure Synapse, enabling advanced analytics and big data processing.
What are materialized views in Azure Data Explorer?
Materialized views store query results to improve performance for frequent queries.
How does Azure Data Explorer handle batch processing?
Batch processing is supported through ingestion policies that process data in chunks.
What is the purpose of the ingestion failure policy in Azure Data Explorer?
It defines actions to take when data ingestion fails, such as retries or logging errors.
How does Azure Data Explorer enable governance and compliance?
It provides auditing, access control, and encryption to help meet governance and compliance requirements.
What is the function of cluster autoscaling in Azure Data Explorer?
Cluster autoscaling automatically adjusts compute resources based on workload demand.
How can Azure Data Explorer be used for anomaly detection?
KQL functions and time-series analysis allow for detecting anomalies in data patterns.
What are the retention limits in Azure Data Explorer?
Data retention can range from days to years, depending on policies set for hot and cold storage.
How is data access managed in Azure Data Explorer?
Data access is managed using RBAC and AAD authentication, restricting access to authorized users.
What is the role of caching in Azure Data Explorer?
Caching improves performance by storing frequently accessed data in memory for faster queries.
What is the Kusto Engine in Azure Data Explorer?
The Kusto Engine is responsible for processing queries and managing data ingestion, storage, and retrieval.
What disaster recovery options are available for Azure Data Explorer?
It provides geo-replication, automatic backups, and failover support for disaster recovery.
How does Azure Data Explorer manage compute and storage separately?
Compute and storage are decoupled, allowing independent scaling and optimization.
What is the purpose of query throttling in Azure Data Explorer?
Query throttling prevents overloading the system by limiting the resources allocated to queries.
How does Azure Data Explorer handle multi-tenancy?
It supports multi-tenancy through resource isolation and separate access controls for each tenant.
What are the benefits of using Azure Data Explorer for IoT analytics?
Azure Data Explorer enables fast ingestion, storage, and querying of large IoT telemetry data streams.
What monitoring tools are available for Azure Data Explorer?
Azure Monitor, Log Analytics, and KQL queries can be used to monitor performance and resource usage.
What is the purpose of the ingestion retry policy in Azure Data Explorer?
It defines the number of retry attempts for failed data ingestion processes before logging an error.
Describes the Azure Data Explorer architecture
- Cluster of nodes
- Node size is described in the deployment config
Does ADX support injection of streaming data
Yes
