AWS Machine Learning Blog

NOVEMBER 12, 2024

NOTE : Since we used an SQL query engine to query the dataset for this demonstration, the prompts and generated outputs mention SQL below. The question in the preceding example doesn’t require a lot of complex analysis on the data returned from the ETF dataset. A user can ask a business- or industry-related question for ETFs.

SQL 101

SQL AWS AI AI 101

AWS Machine Learning Blog

JANUARY 4, 2024

One such area that is evolving is using natural language processing (NLP) to unlock new opportunities for accessing data through intuitive SQL queries. Instead of dealing with complex technical code, business users and data analysts can ask questions related to data and insights in plain language.

SQL 137

SQL Database AI AI 137

phData

NOVEMBER 8, 2024

Note : Cloud Data warehouses like Snowflake and Big Query already have a default time travel feature. However, this feature becomes an absolute must-have if you are operating your analytics on top of your data lake or lakehouse. It can also be integrated into major data platforms like Snowflake. Contact phData Today!

Data Lakes 52

Data Lakes Data Warehouse Database Azure 52

AWS Machine Learning Blog

JUNE 13, 2023

The natural language capabilities allow non-technical users to query data through conversational English rather than complex SQL. The AI and language models must identify the appropriate data sources, generate effective SQL queries, and produce coherent responses with embedded results at scale.

Database 87

Database SQL AWS AI 87

Pickl AI

FEBRUARY 23, 2025

Apache Spark Apache Spark is a unified analytics engine for Big Data processing, with built-in modules for streaming, SQL, Machine Learning , and graph processing. Key Features : Speed : Spark processes data in-memory, making it up to 100 times faster than Hadoop MapReduce in certain applications.

Big Data 52

Big Data Big Data Apache Hadoop Apache Kafka 52