AWS Big Data

SEPTEMBER 13, 2023

A modern data architecture is an evolutionary architecture pattern designed to integrate a data lake, data warehouse, and purpose-built stores with a unified governance model. The company wanted the ability to continue processing operational data in the secondary Region in the rare event of primary Region failure.

Data Lake 91

Data Lake Data Processing Metadata Snapshot 91

AWS Big Data

JUNE 9, 2023

A modern data architecture enables companies to ingest virtually any type of data through automated pipelines into a data lake, which provides highly durable and cost-effective object storage at petabyte or exabyte scale.

Data Lake 114

Data Lake Metadata Optimization Statistics 114

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.

Data Lake 88

Data Lake Analytics Snapshot Optimization 88

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.

Data Lake 93

Data Lake Snapshot Metadata Optimization 93

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.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

Cloudera

APRIL 3, 2023

In this blog, we will share with you in detail how Cloudera integrates core compute engines including Apache Hive and Apache Impala in Cloudera Data Warehouse with Iceberg. Every table change creates an Iceberg snapshot, this helps to resolve concurrency issues and allows readers to scan a stable table state every time.

Data Warehouse 82

Data Warehouse Snapshot Metadata Cost-Benefit 82

AWS Big Data

AUGUST 2, 2023

The data architecture diagram below shows an example of how you could use AWS services to calculate and visualize an organization’s estimated carbon footprint. Customers have the flexibility to choose the services in each stage of the data pipeline based on their use case.

Data Lake 72

Data Lake Measurement Visualization Data Architecture 72

O'Reilly on Data

OCTOBER 19, 2021

Much has been written about struggles of deploying machine learning projects to production. As with many burgeoning fields and disciplines, we don’t yet have a shared canonical infrastructure stack or best practices for developing and deploying data-intensive applications. However, the concept is quite abstract. Versioning.

IT 351

IT Testing Experimentation Software 351

Cloudera

DECEMBER 15, 2022

Improve performance and overall manageability of Iceberg tables using the new table maintenance capabilities such as expiring old snapshots and removing their metadata, and compaction to combine small files for more efficient data processing. Enhanced multi-function analytics. ORC open file format support.

Metadata 80

Metadata Data Warehouse Snapshot Data Quality 80

AWS Big Data

JUNE 10, 2024

This amalgamation empowers vendors with authority over a diverse range of workloads by virtue of owning the data. This authority extends across realms such as business intelligence, data engineering, and machine learning thus limiting the tools and capabilities that can be used. SparkActions.get().expireSnapshots(iceTable).expireOlderThan(TimeUnit.DAYS.toMillis(7)).execute()

Data Lake 93

Data Lake Metadata Snapshot Analytics 93

Cloudera

MARCH 23, 2022

Through Cloudera’s contributions, we have extended support for Hive and Impala, delivering on the vision of a data architecture for multi-function analytics from large scale data engineering (DE) workloads and stream processing (DF) to fast BI and querying (within DW) and machine learning (ML). . Financial regulation.

Metadata 92

Metadata Data Architecture Machine Learning Cost-Benefit 92

AWS Big Data

MARCH 20, 2023

Other use cases – Additional use cases relating to aggregations and machine learning (ML) inference use cases such as authorization to operate, listing spam detection, and avoiding account takeovers (ATOs), among others. The data from the S3 data lake is used for batch processing and analytics through Amazon EMR and Amazon Redshift.

Analytics 52

Analytics Slice and Dice Data Processing Data Lake 52

AWS Big Data

MARCH 18, 2024

Namespaces group together all of the resources you use in Redshift Serverless, such as schemas, tables, users, datashares, and snapshots. First, we need to give our Redshift namespace permission via AWS Identity and Access Management (IAM) to access subscriptions on AWS Data Exchange. Workgroup – A collection of compute resources.

Data Warehouse 81

Data Warehouse Visualization Snapshot Data-driven 81

Corinium

APRIL 25, 2019

Then when there is a breach, it comes as a shock, “wow, I didn’t even know that application had access to so much sensitive data”. Step One in any data security program should first be to discover and classify datasets that are sensitive, and know where that data is, and understand who really needs it to do their jobs.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

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.

Machine Learning 83

Machine Learning Metrics Big Data Management 83

AWS Big Data

JUNE 21, 2023

When setting out to build a data warehouse, it’s a common pattern to have a data lake as the source of the data warehouse. The data lake in this context serves a number of important functions: It acts as a central source for multiple applications, not just exclusively for data warehousing purposes.

Data Warehouse 80

Data Warehouse Data Lake OLAP Cost-Benefit 80