AWS Big Data

MARCH 25, 2024

Furthermore, data events are filtered, enriched, and transformed to a consumable format using a stream processor. The result is made available to the application by querying the latest snapshot. For more details, refer to Create a low-latency source-to-data lake pipeline using Amazon MSK Connect, Apache Flink, and Apache Hudi.

Data Lake 94

Data Lake Unstructured Data Management Modeling 94

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 117

Data Lake Metadata Optimization Statistics 117

Cloudera

FEBRUARY 8, 2024

Subsequently, these snapshot IDs are used to determine the delta changes that should be applied to the materialized view rows. Incremental and full rebuild of materialized view We will insert rows into the base table and examine how the materialized view can be updated to reflect the new data.

Snapshot 90

Snapshot Metadata Cost-Benefit Data Warehouse 90

AWS Big Data

FEBRUARY 12, 2024

About Redshift and some relevant features for the use case Amazon Redshift is a fully managed, petabyte-scale, massively parallel data warehouse that offers simple operations and high performance. It makes it fast, simple, and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools.

Data Warehouse 104

Data Warehouse Analytics Snapshot Cost-Benefit 104

Cloudera

APRIL 3, 2023

Every table change creates an Iceberg snapshot, this helps to resolve concurrency issues and allows readers to scan a stable table state every time. During queries the query engines scan both the data files and delete files belonging to the same snapshot and merge them together (i.e.

Data Warehouse 81

Data Warehouse Snapshot Metadata Cost-Benefit 81

AWS Big Data

MAY 30, 2023

Customers have been using data warehousing solutions to perform their traditional analytics tasks. Recently, data lakes have gained lot of traction to become the foundation for analytical solutions, because they come with benefits such as scalability, fault tolerance, and support for structured, semi-structured, and unstructured datasets.

Data Lake 85

Data Lake Data Analytics Analytics Data Processing 85

Cloudera

MARCH 23, 2022

In fact, we recently announced the integration with our cloud ecosystem bringing the benefits of Iceberg to enterprises as they make their journey to the public cloud, and as they adopt more converged architectures like the Lakehouse. In CDP, this is already available as part of Impala MPP open source engine support for Z-Order.

Metadata 90

Metadata Data Architecture Machine Learning Cost-Benefit 90

Corinium

APRIL 25, 2019

Most enterprises in the 21st century regard data as an incredibly valuable asset – Insurance is no exception - to know your customers better, know your market better, operate more efficiently and other business benefits. In data-driven organizations, data is flowing. That’s the reward.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

AWS Big Data

MARCH 3, 2023

From detailed design to a beta release, Tricentis had customers expecting to consume data from a data lake specific to only their data, and all of the data that had been generated for over a decade. Data export As stated earlier, some customers want to get an export of their test data and create their data lake.

Software 52

Software Data Lake Testing Cost-Benefit 52

AWS Big Data

JUNE 21, 2023

In traditional databases, we would model such applications using a normalized data model (entity-relation diagram). A key pillar of AWS’s modern data strategy is the use of purpose-built data stores for specific use cases to achieve performance, cost, and scale. These types of queries are suited for a data warehouse.

Data Warehouse 84

Data Warehouse Data Lake OLAP Cost-Benefit 84

IBM Big Data Hub

SEPTEMBER 25, 2023

Presto is an open source distributed SQL query engine for data analytics and the data lakehouse, designed for running interactive analytic queries against datasets of all sizes, from gigabytes to petabytes. Because of its distributed nature, Presto scales for petabytes and exabytes of data.

OLAP 90

OLAP Data Lake Data-driven Snapshot 90

AWS Big Data

JULY 28, 2023

Today, tens of thousands of customers run business-critical workloads on Amazon Redshift to cost-effectively and quickly analyze their data using standard SQL and existing business intelligence (BI) tools. Amazon Redshift now makes it easier for you to run queries in AWS data lakes by automatically mounting the AWS Glue Data Catalog.

Data Lake 70

Data Lake Data Governance Data Warehouse Modeling 70