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Use Apache Iceberg in your data lake with Amazon S3, AWS Glue, and Snowflake

AWS Big Data

Businesses are constantly evolving, and data leaders are challenged every day to meet new requirements. Customers are using AWS and Snowflake to develop purpose-built data architectures that provide the performance required for modern analytics and artificial intelligence (AI) use cases.

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Snowflake: Data Ingestion Using Snowpipe and AWS Glue

BizAcuity

In today’s world that is largely data-driven, organizations depend on data for their success and survival, and therefore need robust, scalable data architecture to handle their data needs. This typically requires a data warehouse for analytics needs that is able to ingest and handle real time data of huge volumes.

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How Knowledge Graphs Power Data Mesh and Data Fabric

Ontotext

The data ecosystem today is crowded with dazzling buzzwords, all fighting for investment dollars. A survey in 2021 found that a data company was being funded every 45 minutes. Data ecosystems have become jungles and in spite of all the technology, data teams are struggling to create a modern data experience.

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The New Data Integration Requirements

In(tegrate) the Clouds

This week SnapLogic posted a presentation of the 10 Modern Data Integration Platform Requirements on the company’s blog. They are: Application integration is done primarily through REST & SOAP services. Large-volume data integration is available to Hadoop-based data lakes or cloud-based data warehouses.

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With a zero-ETL approach, AWS is helping builders realize near-real-time analytics

AWS Big Data

Data is at the center of every application, process, and business decision. When data is used to improve customer experiences and drive innovation, it can lead to business growth. According to Forrester , advanced insights-driven businesses are 8.5 Firstly, it invariably requires data engineers to create custom code.

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Snowflake: Data Ingestion Using Snowpipe and AWS Glue

BizAcuity

Introduction In today’s world that is largely data-driven, organizations depend on data for their success and survival, and therefore need robust, scalable data architecture to handle their data needs. For this reason, Snowflake is often the cloud-native data warehouse of choice.

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Enhance monitoring and debugging for AWS Glue jobs using new job observability metrics

AWS Big Data

For any modern data-driven company, having smooth data integration pipelines is crucial. These pipelines pull data from various sources, transform it, and load it into destination systems for analytics and reporting. Undetected errors result in bad data and impact downstream analysis.

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