Remove 2012 Remove Big Data Remove Data Lake Remove Optimization
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Petabyte-scale log analytics with Amazon S3, Amazon OpenSearch Service, and Amazon OpenSearch Ingestion

AWS Big Data

At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. With this massive data growth, data proliferation across your data stores, data warehouse, and data lakes can become equally challenging.

Data Lake 112
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Run Spark SQL on Amazon Athena Spark

AWS Big Data

Modern applications store massive amounts of data on Amazon Simple Storage Service (Amazon S3) data lakes, providing cost-effective and highly durable storage, and allowing you to run analytics and machine learning (ML) from your data lake to generate insights on your data.

Data Lake 101
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Periscope Data Expands to Israel, Empowering Data Teams with Powerful Tools

Sisense

We hosted over 150 people from more than 100 companies, who gathered to learn why data can supercharge their companies and how harnessing the huge power of data can take business from startup to unicorn. Scott whisked us through the history of business intelligence from its first definition in 1958 to the current rise of Big Data.

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Measure performance of AWS Glue Data Quality for ETL pipelines

AWS Big Data

In recent years, data lakes have become a mainstream architecture, and data quality validation is a critical factor to improve the reusability and consistency of the data. He enjoys working on analytics and AI/ML challenges, with a passion for automation and optimization.

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How SumUp made digital analytics more accessible using AWS Glue

AWS Big Data

Founded in 2012, SumUp is the financial partner for more than 4 million small merchants in over 35 markets worldwide, helping them start, run and grow their business. AWS Glue gave us a cost-efficient option to migrate the data and we further optimized storage cost by pruning cold data.

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Simplify external object access in Amazon Redshift using automatic mounting of the AWS Glue Data Catalog

AWS Big Data

Amazon Redshift now makes it easier for you to run queries in AWS data lakes by automatically mounting the AWS Glue Data Catalog. You no longer have to create an external schema in Amazon Redshift to use the data lake tables cataloged in the Data Catalog. There are additional changes required in IAM policy.

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Simplify and speed up Apache Spark applications on Amazon Redshift data with Amazon Redshift integration for Apache Spark

AWS Big Data

For sales across multiple markets, the product sales data such as orders, transactions, and shipment data is available on Amazon S3 in the data lake. The data engineering team can use Apache Spark with Amazon EMR or AWS Glue to analyze this data in Amazon S3. enableHiveSupport().getOrCreate()