Remove 2022 Remove Dashboards Remove Data Architecture Remove Data Lake
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Build a transactional data lake using Apache Iceberg, AWS Glue, and cross-account data shares using AWS Lake Formation and Amazon Athena

AWS Big Data

Building a data lake on Amazon Simple Storage Service (Amazon S3) provides numerous benefits for an organization. However, many use cases, like performing change data capture (CDC) from an upstream relational database to an Amazon S3-based data lake, require handling data at a record level.

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Eight Top DataOps Trends for 2022

DataKitchen

Keep an eye on the eight top trends below that we believe will be significant in the year 2022. The data industry realizes that AI bias is simply a quality problem, and AI systems should be subject to this same level of process control as an automobile rolling off an assembly line. Data Gets Meshier. Data Gets Meshier.

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Get maximum value out of your cloud data warehouse with Amazon Redshift

AWS Big Data

Every day, customers are challenged with how to manage their growing data volumes and operational costs to unlock the value of data for timely insights and innovation, while maintaining consistent performance. As data workloads grow, costs to scale and manage data usage with the right governance typically increase as well.

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Supercharge Your Data Lakehouse with Apache Iceberg in Cloudera Data Platform

Cloudera

In February 2022, we introduced Apache Iceberg as a technical preview within CDP. Over the past decade, Cloudera has enabled multi-function analytics on data lakes through the introduction of the Hive table format and Hive ACID. We selected change data capture as our first use case on Iceberg.

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Build incremental data pipelines to load transactional data changes using AWS DMS, Delta 2.0, and Amazon EMR Serverless

AWS Big Data

Building data lakes from continuously changing transactional data of databases and keeping data lakes up to date is a complex task and can be an operational challenge. You can then apply transformations and store data in Delta format for managing inserts, updates, and deletes.

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Create an end-to-end data strategy for Customer 360 on AWS

AWS Big Data

This view is used to identify patterns and trends in customer behavior, which can inform data-driven decisions to improve business outcomes. In 2022, AWS commissioned a study conducted by the American Productivity and Quality Center (APQC) to quantify the Business Value of Customer 360.

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Exploring new ETL and ELT capabilities for Amazon Redshift from the AWS Glue Studio visual editor

AWS Big Data

In a modern data architecture, unified analytics enable you to access the data you need, whether it’s stored in a data lake or a data warehouse. AWS Glue provides an extensible architecture that enables users with different data processing use cases, and works well with Amazon Redshift.