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. Create your S3 bucket if you do not have it.

Data Lake 95

Data Lake Snapshot Metadata Optimization 95

Cloudera

FEBRUARY 14, 2024

Introduction Apache Iceberg has recently grown in popularity because it adds data warehouse-like capabilities to your data lake making it easier to analyze all your data — structured and unstructured. Problem with too many snapshots Everytime a write operation occurs on an Iceberg table, a new snapshot is created.

Strategy 57

Strategy Optimization Snapshot Metadata 57

Cloudera

FEBRUARY 8, 2024

Overview This blog post describes support for materialized views for the Iceberg table format. It brings the reliability and simplicity of SQL tables to big data while enabling engines like Hive, Impala, Spark, Trino, Flink, and Presto to work with the same tables at the same time. These tables are created as Iceberg tables.

Snapshot 90

Snapshot Metadata Cost-Benefit Data Warehouse 90

AWS Big Data

JANUARY 17, 2024

With Amazon EMR 6.15, we launched AWS Lake Formation based fine-grained access controls (FGAC) on Open Table Formats (OTFs), including Apache Hudi, Apache Iceberg, and Delta lake. Many large enterprise companies seek to use their transactional data lake to gain insights and improve decision-making.

Data Lake 96

Data Lake Snapshot Big Data Data-driven 96

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. We will publish follow up blogs for other data services. Iceberg basics Iceberg is an open table format designed for large analytic workloads.

Data Warehouse 81

Data Warehouse Snapshot Metadata Cost-Benefit 81

IBM Big Data Hub

SEPTEMBER 25, 2023

But what most people don’t realize is that behind the scenes, Uber is not just a transportation service; it’s a data and analytics powerhouse. Every day, millions of riders use the Uber app, unwittingly contributing to a complex web of data-driven decisions. They ingest data in snapshots from operational systems.

OLAP 88

OLAP Data Lake Data-driven Snapshot 88

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. Learn more about the next generation of Cloudera Data Platform for Private Cloud.

Snapshot 87

Snapshot Data Lake Enterprise Data Governance 87

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.

Data Lake 105

Data Lake Management Metrics Data Warehouse 105

AWS Big Data

MARCH 23, 2023

For this blog our “primary” workgroup is using Athena engine version 3. Data producer setup In this section, we present the steps to set up the data producer. Register the S3 path storing the table using Lake Formation We register the S3 full path in Lake Formation: Navigate to the Lake Formation console.

Interactive 71

Interactive Snapshot Data Lake Software 71

AWS Big Data

AUGUST 2, 2023

In this blog, we will walk through how we can apply existing enterprise data to better understand and estimate Scope 1 carbon footprint using Amazon Simple Storage Service (S3) and Amazon Athena , a serverless interactive analytics service that makes it easy to analyze data using standard SQL.

Data Lake 74

Data Lake Measurement Visualization Data Architecture 74

Cloudera

SEPTEMBER 12, 2022

We have delivered the performance and reliability of the data warehouse with the flexibility and scale of a data lake with our data service engines and the Hive metastore. Applying the Iceberg table format to all the organization’s data in the data lake makes it more performant and usable at scale.

Unstructured Data 74

Unstructured Data Data Architecture Data Lake Snapshot 74

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. Maintaining performance and manageability with improved table maintenance .

Metadata 78

Metadata Data Warehouse Snapshot Data Quality 78

AWS Big Data

JANUARY 8, 2024

Therefore, it is critical for organizations to embrace a low-latency, scalable, and reliable data streaming infrastructure to deliver real-time business applications and better customer experiences. It can receive the events from an input Kinesis data stream and route the resulting stream to an output data stream.

Analytics 115

Analytics IoT Data-driven Snapshot 115

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. We discuss implementing dimensions and facts within Amazon Redshift. Solution overview The following diagram illustrates the solution architecture.

Modeling 71

Modeling Sales Data Warehouse Snapshot 71

AWS Big Data

MARCH 3, 2023

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. For Type , choose Spark.

Data Lake 86

Data Lake Dashboards Metrics Metadata 86

Cloudera

MARCH 23, 2022

Apache Iceberg snapshot and time-travel features can help analysts and auditors to easily look back in time and analyze the data with the simplicity of SQL. . The post 5 Reasons to Use Apache Iceberg on Cloudera Data Platform (CDP) appeared first on Cloudera Blog. Financial regulation. Reproducibility for ML Ops.

Metadata 90

Metadata Data Architecture Machine Learning Cost-Benefit 90

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 84

Machine Learning Metrics Big Data Management 84