Remove Dashboards Remove Metadata Remove Structured Data Remove Unstructured Data
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How to get powerful and actionable insights from any and all of your data, without delay

Cloudera

They were not able to quickly and easily query and analyze huge amounts of data as required. They also needed to combine text or other unstructured data with structured data and visualize the results in the same dashboards. You can link dashboards and have them depend on each other.

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The Future Is Hybrid Data, Embrace It

Cloudera

We live in a hybrid data world. In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB.

IT 111
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The Future Is Hybrid Data, Embrace It

CIO Business Intelligence

We live in a hybrid data world. In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB.

IT 97
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Data Lakes on Cloud & it’s Usage in Healthcare

BizAcuity

Data lakes are centralized repositories that can store all structured and unstructured data at any desired scale. The power of the data lake lies in the fact that it often is a cost-effective way to store data. In the future of healthcare, data lake is a prominent component, growing across the enterprise.

Data Lake 102
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Exploring real-time streaming for generative AI Applications

AWS Big Data

Streaming jobs constantly ingest new data to synchronize across systems and can perform enrichment, transformations, joins, and aggregations across windows of time more efficiently. For building such a data store, an unstructured data store would be best.

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Top 10 Key Features of BI Tools in 2020

FineReport

Overall, as users’ data sources become more extensive, their preferences for BI are changing. They prefer self-service development, interactive dashboards, and self-service data exploration. To put it bluntly, users increasingly want to do their own data analysis without having to find support from the IT department.

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The new challenges of scale: What it takes to go from PB to EB data scale

CIO Business Intelligence

Additionally, it is vital to be able to execute computing operations on the 1000+ PB within a multi-parallel processing distributed system, considering that the data remains dynamic, constantly undergoing updates, deletions, movements, and growth. We know the global volume of data will only grow larger and more difficult to navigate.