AWS Big Data

DECEMBER 21, 2023

To create and manage the data products, smava uses Amazon Redshift , a cloud data warehouse. In this post, we show how smava optimized their data platform by using Amazon Redshift Serverless and Amazon Redshift data sharing to overcome right-sizing challenges for unpredictable workloads and further improve price-performance.

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Data Lake Data Warehouse Data-driven B2B 115

Cloudera

DECEMBER 21, 2021

Since the release of Cloudera Data Engineering (CDE) more than a year ago , our number one goal was operationalizing Spark pipelines at scale with first class tooling designed to streamline automation and observability. This enabled new use-cases with customers that were using a mix of Spark and Hive to perform data transformations. .

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Snapshot Data-driven Optimization Management 118

Cloudera

OCTOBER 8, 2024

This service supports a range of optimized AI models, enabling seamless and scalable AI inference. In 2022, the release of ChatGPT attracted over 100 million users within just two months, demonstrating the technology’s accessibility and its impact across various user skill levels.

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Optimization Experimentation Metrics Enterprise 75

AWS Big Data

MAY 25, 2023

Data transformation plays a pivotal role in providing the necessary data insights for businesses in any organization, small and large. To gain these insights, customers often perform ETL (extract, transform, and load) jobs from their source systems and output an enriched dataset. 1X 1 4 16 64 G.2X 2X 2 8 32 128 G.4X

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Reporting Metrics Optimization Data Lake 97

AWS Big Data

NOVEMBER 29, 2023

dbt is an open source, SQL-first templating engine that allows you to write repeatable and extensible data transforms in Python and SQL. dbt is predominantly used by data warehouses (such as Amazon Redshift ) customers who are looking to keep their data transform logic separate from storage and engine.

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Data Lake Management Metrics Data Warehouse 121

AWS Big Data

MARCH 3, 2023

Data ingestion – Steps 1 and 2 use AWS DMS, which connects to the source database and moves full and incremental data (CDC) to Amazon S3 in Parquet format. Data transformation – Steps 3 and 4 represent an EMR Serverless Spark application (Amazon EMR 6.9 Let’s refer to this S3 bucket as the raw layer.

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Data Lake Dashboards Metrics Metadata 98

AWS Big Data

APRIL 5, 2023

The company also used the opportunity to reimagine its data pipeline and architecture. A key architectural decision that Showpad took during this time was to create a portable data layer by decoupling the data transformation from visualization, ML, or ad hoc querying tools and centralizing its business logic.

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Dashboards Reporting Cost-Benefit Visualization 52

CIO Business Intelligence

JANUARY 24, 2024

Shi , and “Swarm Robotics” (2022) by H. Agent Swarms offer a strategic solution: they can autonomously oversee repetitive, rules-based, high-volume tasks, optimizing back-office functions and ensuring regulatory compliance with precision. Recent research in this field underscores the growing importance and potential of Agent Swarms.

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IoT Machine Learning Internet of Things Optimization 118

AWS Big Data

NOVEMBER 14, 2024

We use the built-in features of Data Firehose, including AWS Lambda for necessary data transformation and Amazon Simple Notification Service (Amazon SNS) for near real-time alerts. To maintain up-to-date data, an AWS Glue crawler reads and updates the AWS Glue Data Catalog from transformed Parquet files.

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Data Lake Metadata Testing Data-driven 105