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Data lakes vs. data warehouses: Decoding the data storage debate

Data Science Dojo

When it comes to data, there are two main types: data lakes and data warehouses. What is a data lake? An enormous amount of raw data is stored in its original format in a data lake until it is required for analytics applications. Which one is right for your business?

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How Twilio generated SQL using Looker Modeling Language data with Amazon Bedrock

AWS Machine Learning Blog

As one of the largest AWS customers, Twilio engages with data, artificial intelligence (AI), and machine learning (ML) services to run their daily workloads. Data is the foundational layer for all generative AI and ML applications.

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Imperva optimizes SQL generation from natural language using Amazon Bedrock

AWS Machine Learning Blog

Our goal was to improve the user experience of an existing application used to explore the counters and insights data. The data is stored in a data lake and retrieved by SQL using Amazon Athena. The following figure shows a search query that was translated to SQL and run. The challenge is to assure quality.

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Best 8 Data Version Control Tools for Machine Learning 2024

DagsHub

The following points illustrates some of the main reasons why data versioning is crucial to the success of any data science and machine learning project: Storage space One of the reasons of versioning data is to be able to keep track of multiple versions of the same data which obviously need to be stored as well.

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Build a robust text-to-SQL solution generating complex queries, self-correcting, and querying diverse data sources

AWS Machine Learning Blog

Structured Query Language (SQL) is a complex language that requires an understanding of databases and metadata. Today, generative AI can enable people without SQL knowledge. This generative AI task is called text-to-SQL, which generates SQL queries from natural language processing (NLP) and converts text into semantically correct SQL.

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Generate financial industry-specific insights using generative AI and in-context fine-tuning

AWS Machine Learning Blog

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.

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Sneak peek at Microsoft Fabric price and its promising features

Dataconomy

Unified data storage : Fabric’s centralized data lake, Microsoft OneLake, eliminates data silos and provides a unified storage system, simplifying data access and retrieval. OneLake is designed to store a single copy of data in a unified location, leveraging the open-source Apache Parquet format.

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