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Differentiating Between Data Lakes and Data Warehouses

Smart Data Collective

The market for data warehouses is booming. One study forecasts that the market will be worth $23.8 While there is a lot of discussion about the merits of data warehouses, not enough discussion centers around data lakes. Both data warehouses and data lakes are used when storing big data.

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Complexity Drives Costs: A Look Inside BYOD and Azure Data Lakes

Jet Global

The company’s market power is based largely on its ability to promote the “stack”—that is, to position the entire suite of Microsoft products as a holistic solution to customer problems. Option 3: Azure Data Lakes. This leads us to Microsoft’s apparent long-term strategy for D365 F&SCM reporting: Azure Data Lakes.

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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

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Understanding Structured and Unstructured Data

Sisense

Different types of information are more suited to being stored in a structured or unstructured format. Read on to explore more about structured vs unstructured data, why the difference between structured and unstructured data matters, and how cloud data warehouses deal with them both. Unstructured data.

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TDC Digital leverages IBM Cloud for transparent billing and improved customer satisfaction

IBM Big Data Hub

The rapid growth of global web-based ERP solution providers The global cloud ERP market is expected to grow at a CAGR of 15%, from USD 64.7 Small and midsize enterprises (SMEs) are the fastest-growing segment in the market due to reliability, scalability, integration, flexibility and improved productivity. billion in 2022 to USD 130.0

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A Look at Data Entities and BYOD for Accountants

Jet Global

Introducing Data Lakes. Microsoft’s next option is called Azure Data Lake Services (ADLS), and it seems to be the company’s favored long-term solution to its D365 F&SCM reporting challenge. Data lake” is a generic term that refers to a fairly new development in the world of big data analytics.

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Architectural patterns for real-time analytics using Amazon Kinesis Data Streams, part 1

AWS Big Data

This is the first post to a blog series that offers common architectural patterns in building real-time data streaming infrastructures using Kinesis Data Streams for a wide range of use cases. In this post, we will review the common architectural patterns of two use cases: Time Series Data Analysis and Event Driven Microservices.

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