AWS Big Data

JULY 20, 2023

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. In this post, we describe Orca’s journey building a transactional data lake using Amazon Simple Storage Service (Amazon S3), Apache Iceberg, and AWS Analytics.

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Data Lake Analytics Snapshot Data Quality 98

AWS Big Data

DECEMBER 9, 2024

The importance of publishing only high-quality data cant be overstatedits the foundation for accurate analytics, reliable machine learning (ML) models, and sound decision-making. AWS Glue is a serverless data integration service that you can use to effectively monitor and manage data quality through AWS Glue Data Quality.

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AWS Big Data

NOVEMBER 22, 2023

Apache Hudi is an open table format that brings database and data warehouse capabilities to data lakes. Apache Hudi helps data engineers manage complex challenges, such as managing continuously evolving datasets with transactions while maintaining query performance. Under Administration , choose Data catalog settings.

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Data Lake Snapshot Metadata Optimization 115

AWS Big Data

MARCH 20, 2023

In the first post of this series , we described how AWS Glue for Apache Spark works with Apache Hudi, Linux Foundation Delta Lake, and Apache Iceberg datasets tables using the native support of those data lake formats. Even without prior experience using Hudi, Delta Lake or Iceberg, you can easily achieve typical use cases.

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AWS Big Data

JUNE 27, 2024

With built-in features such as automated snapshots and cross-Region replication, you can enhance your disaster resilience with Amazon Redshift. Amazon Redshift supports two kinds of snapshots: automatic and manual, which can be used to recover data. Snapshots are point-in-time backups of the Redshift data warehouse.

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AWS Big Data

NOVEMBER 10, 2023

The data sourcing problem To ensure the reliability of PySpark data pipelines, it’s essential to have consistent record-level data from both dimensional and fact tables stored in the Enterprise Data Warehouse (EDW). These tables are then joined with tables from the Enterprise Data Lake (EDL) at runtime.

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Data Processing Data Lake Data Warehouse Optimization 111

Cloudera

MARCH 5, 2024

With built-in features like time travel, schema evolution, and streamlined data discovery, Iceberg empowers data teams to enhance data lake management while upholding data integrity. Zero Downtime Upgrades Beyond improvements to Iceberg and Ozone, the platform now boasts Zero Downtime Upgrades (ZDU).

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Snapshot Data Lake Enterprise Data Governance 92

Cloudera

SEPTEMBER 12, 2022

A data fabric answers perhaps the biggest question of all: what data do we have to work with? Managing and making individual data sources available through traditional enterprise data integration, and when end users request them, simply does not scale — especially in light of a growing number of sources and volume.

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AWS Big Data

DECEMBER 20, 2024

Data migration The objective of this phase is to build a metadata-driven framework for migrating data from HDFS to Amazon S3 with Apache Iceberg storage format, which involves the least operational overhead, provides scalability capacity during peak hours, and guarantees data integrity and confidentiality.

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Metadata Data-driven Snapshot Data Lake 52

AWS Big Data

FEBRUARY 1, 2023

With data volumes exhibiting a double-digit percentage growth rate year on year and the COVID pandemic disrupting global logistics in 2021, it became more critical to scale and generate near-real-time data. You can visually create, run, and monitor extract, transform, and load (ETL) pipelines to load data into your data lakes.

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AWS Big Data

DECEMBER 13, 2023

Apache Kafka is an open-source distributed event streaming platform used by thousands of companies for high-performance data pipelines, streaming analytics, data integration, and mission-critical applications. We deploy Debezium MySQL source Kafka connector on Amazon MSK Connect.

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Data Warehouse Snapshot Data Processing Internet of Things 116

AWS Big Data

MARCH 3, 2023

Additionally, the scale is significant because the multi-tenant data sources provide a continuous stream of testing activity, and our users require quick data refreshes as well as historical context for up to a decade due to compliance and regulatory demands. Finally, data integrity is of paramount importance.

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Software Data Lake Testing Cost-Benefit 52

AWS Big Data

JULY 19, 2023

We show how to perform extract, transform, and load (ELT), an integration process focused on getting the raw data from a data lake into a staging layer to perform the modeling. Data can either be loaded when there is a new sale, or daily; this is where the inserted date or load date comes in handy.

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Modeling Sales Data Warehouse Snapshot 93

Cloudera

MARCH 23, 2022

Figure 1: Apache Iceberg fits the next generation data architecture by abstracting storage layer from analytics layer while introducing net new capabilities like time-travel and partition evolution. #1: Apache Iceberg enables seamless integration between different streaming and processing engines while maintaining data integrity between them.

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Metadata Data Architecture Machine Learning Cost-Benefit 97

AWS Big Data

JUNE 12, 2023

Acting as a bridge between producer and consumer apps, it enforces the schema, reduces the data footprint in transit, and safeguards against malformed data. AWS Glue is an ideal solution for running stream consumer applications, discovering, extracting, transforming, loading, and integrating data from multiple sources.

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AWS Big Data

MAY 30, 2023

Customers have been using data warehousing solutions to perform their traditional analytics tasks. Recently, data lakes have gained lot of traction to become the foundation for analytical solutions, because they come with benefits such as scalability, fault tolerance, and support for structured, semi-structured, and unstructured datasets.

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Data Lake Data Analytics Analytics Data Processing 98

AWS Big Data

MAY 19, 2023

Organizations across all industries have complex data processing requirements for their analytical use cases across different analytics systems, such as data lakes on AWS , data warehouses ( Amazon Redshift ), search ( Amazon OpenSearch Service ), NoSQL ( Amazon DynamoDB ), machine learning ( Amazon SageMaker ), and more.

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Machine Learning Metrics Big Data Management 113

AWS Big Data

NOVEMBER 29, 2023

We have seen a strong customer demand to expand its scope to cloud-based data lakes because data lakes are increasingly the enterprise solution for large-scale data initiatives due to their power and capabilities. Let’s say that this company is located in Europe and the data product must comply with the GDPR.

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Data Lake Management Metrics Data Warehouse 122