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SQL Streambuilder Data Transformations

Cloudera

As an essential part of ETL, as data is being consolidated, we will notice that data from different sources are structured in different formats. It might be required to enhance, sanitize, and prepare data so that data is fit for consumption by the SQL engine. What is a data transformation?

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DataOps Should Be Part of Everyone on the Data Team

DataKitchen

Data Transformers podcast hosts Peggy Tsai & Ramesh Dontha chat with DataKitchen CEO Chris Bergh about how DataOps should be 10% of every data team member's job. The post DataOps Should Be Part of Everyone on the Data Team first appeared on DataKitchen.

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CIOs are rethinking how they use public cloud services. Here’s why.

CIO Business Intelligence

Theres a renewed focus on on-premises, on-premises private cloud, or hosted private cloud versus public cloud, especially as data-heavy workloads such as generative AI have started to push cloud spend up astronomically, adds Woo. Id be cautious about going down the path of private cloud hosting or on premises, says Nag.

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Automating the Automators: Shift Change in the Robot Factory

O'Reilly on Data

Especially when you consider how Certain Big Cloud Providers treat autoML as an on-ramp to model hosting. Is autoML the bait for long-term model hosting? Related to the previous point, a company could go from “raw data” to “it’s serving predictions on live data” in a single work day.

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The Ultimate Guide to Modern Data Quality Management (DQM) For An Effective Data Quality Control Driven by The Right Metrics

datapine

This means there are no unintended data errors, and it corresponds to its appropriate designation (e.g., Here, it all comes down to the data transformation error rate. Data time-to-value: evaluates how long it takes you to gain insights from a data set. This is due to the technical nature of a data system itself.

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10 Examples of How Big Data in Logistics Can Transform The Supply Chain

datapine

In addition to driving operational efficiency and consistently meeting fulfillment targets, logistics providers use big data applications to provide real-time updates as well as a host of flexible pick-up, drop-off, or ordering options. Use our 14-days free trial today & transform your supply chain!

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Amazon Redshift data ingestion options

AWS Big Data

The currently available choices include: The Amazon Redshift COPY command can load data from Amazon Simple Storage Service (Amazon S3), Amazon EMR , Amazon DynamoDB , or remote hosts over SSH. This native feature of Amazon Redshift uses massive parallel processing (MPP) to load objects directly from data sources into Redshift tables.

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