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

datapine

Reporting being part of an effective DQM, we will also go through some data quality metrics examples you can use to assess your efforts in the matter. But first, let’s define what data quality actually is. What is the definition 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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End-to-end development lifecycle for data engineers to build a data integration pipeline using AWS Glue

AWS Big Data

The code includes the following: AWS resource definition Data integration logic When using AWS Glue, you can define the data integration logic in a job script, which can be written in Python or Scala. Solution overview Typically, you have multiple accounts to manage and provision resources for your data pipeline.

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Self-Service Data’s New Frontier: The Data Catalog

Alation

REFLECTIONS FROM THE GARTNER BI & ANALYTICS SUMMIT I hate to admit that the last time I attended the Gartner BI & Analytics Summit, Howard Dresner was still the host. Alation helps analysts find, understand and use their data. Everything you need to do to prepare for analysis before data transformation and visualization.

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Gain insights from historical location data using Amazon Location Service and AWS analytics services

AWS Big Data

You can also use the data transformation feature of Data Firehose to invoke a Lambda function to perform data transformation in batches. Data enrichment using Lambda Data enrichment in this pattern is facilitated through the invocation of a Lambda function.

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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.