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Choosing the Right ETL Platform: Benefits for Data Integration

Pickl AI

Summary: Selecting the right ETL platform is vital for efficient data integration. Introduction In today’s data-driven world, businesses rely heavily on ETL platforms to streamline data integration processes. What is ETL in Data Integration? Let’s explore some real-world applications of ETL in different sectors.

ETL 52
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Maximising Efficiency with ETL Data: Future Trends and Best Practices

Pickl AI

Summary: This article explores the significance of ETL Data in Data Management. It highlights key components of the ETL process, best practices for efficiency, and future trends like AI integration and real-time processing, ensuring organisations can leverage their data effectively for strategic decision-making.

ETL 52
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Harmonize data using AWS Glue and AWS Lake Formation FindMatches ML to build a customer 360 view

Flipboard

In this post, we look at how we can use AWS Glue and the AWS Lake Formation ML transform FindMatches to harmonize (deduplicate) customer data coming from different sources to get a complete customer profile to be able to provide better customer experience. Run the AWS Glue ML transform job.

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TigerEye (YC S22) Is Hiring a Full Stack Engineer

Hacker News

Here are a few of the things that you might do as an AI Engineer at TigerEye: - Design, develop, and validate statistical models to explain past behavior and to predict future behavior of our customers’ sales teams - Own training, integration, deployment, versioning, and monitoring of ML components - Improve TigerEye’s existing metrics collection and (..)

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Top ETL Tools: Unveiling the Best Solutions for Data Integration

Pickl AI

Summary: Choosing the right ETL tool is crucial for seamless data integration. Top contenders like Apache Airflow and AWS Glue offer unique features, empowering businesses with efficient workflows, high data quality, and informed decision-making capabilities. Choosing the right ETL tool is crucial for smooth data management.

ETL 40
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Integrating AWS Data Lake and RDS MS SQL: A Guide to Writing and Retrieving Data Securely

Dataversity

Writing data to an AWS data lake and retrieving it to populate an AWS RDS MS SQL database involves several AWS services and a sequence of steps for data transfer and transformation. This process leverages AWS S3 for the data lake storage, AWS Glue for ETL operations, and AWS Lambda for orchestration.

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Amazon Aurora MySQL zero-ETL integration with Amazon Redshift is now generally available

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“Data is at the center of every application, process, and business decision,” wrote Swami Sivasubramanian, VP of Database, Analytics, and Machine Learning at AWS, and I couldn’t agree more. A common pattern customers use today is to build data pipelines to move data from Amazon Aurora to Amazon Redshift.

ETL 181