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Differentiating Between Data Lakes and Data Warehouses

Smart Data Collective

While there is a lot of discussion about the merits of data warehouses, not enough discussion centers around data lakes. We talked about enterprise data warehouses in the past, so let’s contrast them with data lakes. Both data warehouses and data lakes are used when storing big data.

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7 Key Benefits of Proper Data Lake Ingestion

Smart Data Collective

Perhaps one of the biggest perks is scalability, which simply means that with good data lake ingestion a small business can begin to handle bigger data numbers. The reality is businesses that are collecting data will likely be doing so on several levels. Data Analytics Simplified. Proper Scalability.

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Build a semantic search engine for tabular columns with Transformers and Amazon OpenSearch Service

AWS Big Data

Finding similar columns in a data lake has important applications in data cleaning and annotation, schema matching, data discovery, and analytics across multiple data sources. Transform CSV to Parquet Raw CSV files are converted to Parquet data format with AWS Glue.

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What’s cooking with Amazon Redshift at AWS re:Invent 2023

AWS Big Data

The analytics team is waiting to engage with our customers and partners at the analytics kiosk in the expo hall. For the latest and greatest with Amazon Redshift , our cloud data warehousing solution, I’ve curated a few must-attend sessions. Take a look, plan your week, and soak in the learning!

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Azure Data Sources for Data Science and Machine Learning

Jen Stirrup

It is more than just some giant USB stick in the sky that’s going to store all of the data. It has a lot of services that you can use, such as Big Data analytics. In this topic, we’re going to focus specifically on Big Data technologies, such as your HDInsight, Apache Spark and Databricks.

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Breaking barriers in geospatial: Amazon Redshift, CARTO, and H3

AWS Big Data

H3 indexing and related H3 spatial functions are now available for Amazon Redshift spatial analytics. For more information or to get started with Amazon Redshift spatial analytics, see the documentation for querying spatial data , spatial functions , and the spatial tutorial.

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Intelligenza artificiale e gen AI: i quattro elementi per passare al “next level”

CIO Business Intelligence

Altrettanto importante (e forse più trascurata) è la questione dei big data che servono per addestrare i modelli e il costo connesso. L’analisi dei dati attraverso l’apprendimento automatico (machine learning, deep learning, reti neurali) è la tecnologia maggiormente utilizzata dalle grandi imprese che utilizzano l’IA (51,9%).