AWS Machine Learning Blog

SEPTEMBER 19, 2023

Implementing a multi-modal agent with AWS consolidates key insights from diverse structured and unstructured data on a large scale. All this is achieved using AWS services, thereby increasing the financial analyst’s efficiency to analyze multi-modal financial data (text, speech, and tabular data) holistically.

AWS 132

AWS AI AI ML 132

AWS Machine Learning Blog

MARCH 14, 2024

We formulated a text-to-SQL approach where by a user’s natural language query is converted to a SQL statement using an LLM. The SQL is run by Amazon Athena to return the relevant data. Our final solution is a combination of these text-to-SQL and text-RAG approaches. The following table contains some example responses.

SQL 130

SQL AWS AI AI 130

AWS Machine Learning Blog

MARCH 8, 2023

In this post, you will learn how Marubeni is optimizing market decisions by using the broad set of AWS analytics and ML services, to build a robust and cost-effective Power Bid Optimization solution. AWS Step Functions to orchestrate both the data and ML pipelines. One function to consolidate and prepare the data for training.

AWS 100

AWS Machine Learning Machine Learning Analytics 100

AWS Machine Learning Blog

JUNE 26, 2024

This post is a follow-up to Generative AI and multi-modal agents in AWS: The key to unlocking new value in financial markets. Analysts need to learn new tools and even some programming languages such as SQL (with different variations). Delete the S3 buckets created by AWS CloudFormation and then delete the CloudFormation stack.

AWS 135

AWS AI AI Database 135

IBM Journey to AI blog

JANUARY 10, 2023

This data will be analyzed using Netezza SQL and Python code to determine if the flight delays for the first half of 2022 have increased over flight delays compared to earlier periods of time within the current data (January 2019 – December 2021). Figure 7 – Initial query using the historical data (2003 – 2018).

Data Warehouse 52

Data Warehouse Data Analysis Data Analysis SQL 52

AWS Machine Learning Blog

NOVEMBER 26, 2024

Task 1: Query generation from natural language This task’s objective is to assess a model’s capacity to translate natural language questions into SQL queries, using contextual knowledge of the underlying data schema. Following these examples, the model is then prompted to generate the SQL query for a question of interest.

Machine Learning 101

Machine Learning Machine Learning SQL ML 101

Alation

SEPTEMBER 30, 2022

Our ability to catalog every data asset means that we can partner with other ISVs in data quality and observability, like BigEye and Soda ; privacy, like BigID and OneTrust; access governance, like Immuta and Privacera; not to mention the core platforms, like Snowflake , Databricks , AWS , GCP, and Azure. Subscribe to Alation's Blog.

Data Governance 92

Data Governance Azure SQL Data Quality 92