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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.

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

Jet Global

For more sophisticated multidimensional reporting functions, however, a more advanced approach to staging data is required. The Data Warehouse Approach. Data warehouses gained momentum back in the early 1990s as companies dealing with growing volumes of data were seeking ways to make analytics faster and more accessible.

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

AWS Big Data

We’ve seen 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 these connectors, you can bring the data from Azure Blob Storage and Azure Data Lake Storage separately to Amazon S3. Learn more in README.

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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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Enterprise BI: Everything You Need to Know

FineReport

Enterprise BI typically functions by combining enterprise data warehouse and enterprise license to a BI platform or toolset that business users in various roles can use. Usually, enterprise BI incorporates relatively rigid, well-structured data models on data warehouses or data marts.