Remove Data Processing Remove Data Transformation Remove Visualization
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10 Examples of How Big Data in Logistics Can Transform The Supply Chain

datapine

Financial efficiency: One of the key benefits of big data in supply chain and logistics management is the reduction of unnecessary costs. Using the right dashboard and data visualizations, it’s possible to hone in on any trends or patterns that uncover inefficiencies within your processes. Now’s the time to strike.

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Copy and mask PII between Amazon RDS databases using visual ETL jobs in AWS Glue Studio

AWS Big Data

You can use AWS Glue Studio to set up data replication and mask PII with no coding required. AWS Glue Studio visual editor provides a low-code graphic environment to build, run, and monitor extract, transform, and load (ETL) scripts. Data transformation – Adjusts and removes unnecessary fields.

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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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Amazon Q data integration adds DataFrame support and in-prompt context-aware job creation

AWS Big Data

This means you can refine your ETL jobs through natural follow-up questionsstarting with a basic data pipeline and progressively adding transformations, filters, and business logic through conversation. The DataFrame code generation now extends beyond AWS Glue DynamicFrame to support a broader range of data processing scenarios.

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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

He/she assists the organization by providing clarity and insight into advanced data technology solutions. As quality issues are often highlighted with the use of dashboard software , the change manager plays an important role in the visualization of data quality. Here, it all comes down to the data transformation error rate.

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Modernize your ETL platform with AWS Glue Studio: A case study from BMS

AWS Big Data

In addition to using native managed AWS services that BMS didn’t need to worry about upgrading, BMS was looking to offer an ETL service to non-technical business users that could visually compose data transformation workflows and seamlessly run them on the AWS Glue Apache Spark-based serverless data integration engine.

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Use AWS Glue to streamline SFTP data processing

AWS Big Data

AWS Glue is a serverless data integration service that helps analytics users to discover, prepare, move, and integrate data from multiple sources for analytics, machine learning (ML), and application development. For this example, you use AWS Glue Studio to develop a visual ETL pipeline. Select Visual ETL in the central pane.