Remove 2022 Remove Interactive Remove Structured Data Remove Unstructured Data
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The Rise of Unstructured Data

Cloudera

Most of that data will be unstructured, and only about 10% will be stored. Seagate Technology forecasts that enterprise data will double from approximately 1 to 2 Petabytes (one Petabyte is 10^15 bytes) between 2020 and 2022. Here we mostly focus on structured vs unstructured data. Conclusions.

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Leading Trends of Fintech Development Services in 2022

Smart Data Collective

In this article, we will look at the main trends in the field of fintech development services for 2022. Now let’s consider the 5 most popular fintech development trends in the world in 2022. The direction associated with the development of KYC, AML, and BNPL systems is another fintech trend in 2022. Unstructured data.

Finance 116
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10 IT skills where expertise pays the most

CIO Business Intelligence

Each service is broken down and then categorized by its own specific set of functions into a standardized interface, enabling those services to interact with and access one another. Because of this, NoSQL databases allow for rapid scalability and are well-suited for large and unstructured data sets.

IT 129
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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 112
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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 73
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The rise of the data lakehouse: A new era of data value

CIO Business Intelligence

The data warehouse requires a time-consuming extract, transform, and load (ETL) process to move data from the system of record to the data warehouse, whereupon the data would be normalized, queried, and answers obtained. Under Guadagno, the Deerfield, Ill. That’s how we got here.

Data Lake 140