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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.

Data Lake 135
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Top 5 Tools for Building an Interactive Analytics App

Smart Data Collective

The application presents a massive volume of unstructured data through a graphical or programming interface using the analytical abilities of business intelligence technology to provide instant insight. Interactive analytics applications present vast volumes of unstructured data at scale to provide instant insights.

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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.

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Big Data Sets New Standards In Stream Processing For Emerging Markets

Smart Data Collective

Data, for instance, has to be processed fast so that the companies can keep up to the changing business and market conditions in real time. This is where real-time stream processing enters the picture, and it may probably change everything you know about big data. What is Big Data? What is Big Data?

Big Data 104
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5 misconceptions about cloud data warehouses

IBM Big Data Hub

In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. The rise of cloud has allowed data warehouses to provide new capabilities such as cost-effective data storage at petabyte scale, highly scalable compute and storage, pay-as-you-go pricing and fully managed service delivery.

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The DataOps Vendor Landscape, 2021

DataKitchen

Companies that implement DataOps find that they are able to reduce cycle times from weeks (or months) to days, virtually eliminate data errors, increase collaboration, and dramatically improve productivity. As a result, vendors that market DataOps capabilities have grown in pace with the popularity of the practice.

Testing 304
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The rise of the data lakehouse: A new era of data value

CIO Business Intelligence

Traditionally, organizations have maintained two systems as part of their data strategies: a system of record on which to run their business and a system of insight such as a data warehouse from which to gather business intelligence (BI). You can intuitively query the data from the data lake.

Data Lake 140