Remove Data Lake Remove Structured Data Remove Testing Remove Unstructured Data
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Build a decentralized semantic search engine on heterogeneous data stores using autonomous agents

AWS Big Data

Large language models (LLMs) such as Anthropic Claude and Amazon Titan have the potential to drive automation across various business processes by processing both structured and unstructured data. Redshift Serverless is a fully functional data warehouse holding data tables maintained in real time.

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Navigating Data Entities, BYOD, and Data Lakes in Microsoft Dynamics

Jet Global

There is an established body of practice around creating, managing, and accessing OLAP data (known as “cubes”). Data Lakes. There has been a lot of talk over the past year or two in the D365F&SCM world about “data lakes.” There are virtually no rules about what such data looks like. It is unstructured.

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Rocket Mortgage lays foundation for generative AI success

CIO Business Intelligence

One of the most valuable aspects of AWS Bedrock, Woodring says, is that it establishes a standard data platform for Rocket, which will enable the mortgage lender to get its data “very quickly” to the right AI model. In other cases, Rocket will test out various AI models and “see their efficacy in different tasks,” Woodring says.

Data Lake 109
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Migrate data from Azure Blob Storage to Amazon S3 using AWS Glue

AWS Big Data

Today, we are pleased to announce new AWS Glue connectors for Azure Blob Storage and Azure Data Lake Storage that allow you to move data bi-directionally between Azure Blob Storage, Azure Data Lake Storage, and Amazon Simple Storage Service (Amazon S3). option("header","true").load("wasbs://yourblob@youraccountname.blob.core.windows.net/loadingtest-input/100mb")

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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Data science is an area of expertise that combines many disciplines such as mathematics, computer science, software engineering and statistics. It focuses on data collection and management of large-scale structured and unstructured data for various academic and business applications.

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Quantitative and Qualitative Data: A Vital Combination

Sisense

Most commonly, we think of data as numbers that show information such as sales figures, marketing data, payroll totals, financial statistics, and other data that can be counted and measured objectively. This is quantitative data. It’s “hard,” structured data that answers questions such as “how many?”

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Migrate data from Google Cloud Storage to Amazon S3 using AWS Glue

AWS Big Data

We’ve seen that there is a demand to design applications that enable data to be portable across cloud environments and give you the ability to derive insights from one or more data sources. With this connector, you can bring the data from Google Cloud Storage to Amazon S3.