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AI/ML Tools
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General Data Sources (Data Aggregators)
DLZP Solutions
Simultaneous localization and Mapping
Contact your DLZP Group Account Manager if you're unable to View Security Resources
AI/ML Tools
Data Sources
General Data Sources (Data Aggregators)
DLZP Solutions
Simultaneous localization and Mapping
Contact your DLZP Group Account Manager if you're unable to View Security Resources
Athena helps you analyze unstructured, semi-structured, and structured data stored in Amazon S3. Examples include CSV, JSON, or columnar data formats such as Apache Parquet and Apache ORC. You can use Athena to run ad-hoc queries using ANSI SQL, without the need to aggregate or load the data into Athena.
Quicksight - Athena integrates with Amazon QuickSight for easy data visualization. You can use Athena to generate reports or to explore data with business intelligence tools or SQL clients connected with a JDBC or an ODBC driver.
Glue - Athena integrates with the AWS Glue Data Catalog, which offers a persistent metadata store for your data in Amazon S3. This allows you to create tables and query data in Athena based on a central metadata store available throughout your AWS account and integrated with the ETL and data discovery features of AWS Glue.
Additional Integration Information - https://docs.aws.amazon.com/athena/latest/ug/athena-aws-service-integrations.html
Connecting using JDBC Tools You can use a JDBC connection to connect Athena to business intelligence tools and other applications, such as SQL Workbench. https://docs.aws.amazon.com/athena/latest/ug/connect-with-jdbc.html
Using ODBC Drivers - https://docs.aws.amazon.com/athena/latest/ug/connect-with-odbc.html
| Function | Description | Example | More Details |
|---|---|---|---|
| regexp_replace | Searches a string for a regular expression pattern and replaces every occurrence of the pattern with the specified string. REGEXP_REPLACE ( source_string, pattern [, replace_string [ , position ] ] ) | “regexp_replace”(“c”.“address1”, '[0-9A-Za-z]','') | https://docs.aws.amazon.com/redshift/latest/dg/REGEXP_REPLACE.html |
For dates you will have to truncate the field to get the portion of the date you want.