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Is web3 data storage ushering in a new era of privacy?

Dataconomy

Thankfully, a new era is beginning to dawn, carried on the winds of change that gusted after the Cambridge Analytica scandal came to light in 2018. Interestingly, storage on Space and Time’s decentralized network is completely free and data is encrypted in-database for second-to-none security.

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How SnapLogic built a text-to-pipeline application with Amazon Bedrock to translate business intent into action

Flipboard

This use case highlights how large language models (LLMs) are able to become a translator between human languages (English, Spanish, Arabic, and more) and machine interpretable languages (Python, Java, Scala, SQL, and so on) along with sophisticated internal reasoning.

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Generative AI and multi-modal agents in AWS: The key to unlocking new value in financial markets

AWS Machine Learning Blog

For structured data, the agent uses the SQL Connector and SQLAlchemy to analyze databases, which includes Amazon Athena. Session(region_name=region_name) athena_client = session.client('athena') database=database_name table=table_Name. It can query a stocks database to answer questions on stocks.

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The journey of PGA TOUR’s generative AI virtual assistant, from concept to development to prototype

AWS Machine Learning Blog

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.

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AI-powered assistants for investment research with multi-modal data: An application of Agents for Amazon Bedrock

AWS Machine Learning Blog

Analysts need to learn new tools and even some programming languages such as SQL (with different variations). Action groups – Action groups are interfaces that an agent uses to interact with the different underlying components such as APIs and databases.

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Analyzing the history of Tableau innovation

Tableau

Chris had earned an undergraduate computer science degree from Simon Fraser University and had worked as a database-oriented software engineer. In 2004, Tableau got both an initial series A of venture funding and Tableau’s first EOM contract with the database company Hyperion—that’s when I was hired. Release v1.0

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How to use Netezza Performance Server query data in Amazon Simple Storage Service (S3)

IBM Journey to AI blog

Netezza Performance Server (NPS) has recently added the ability to access Parquet files by defining a Parquet file as an external table in the database. All SQL and Python code is executed against the NPS database using Jupyter notebooks, which capture query output and graphing of results during the analysis phase of the demonstration.