Cloudera

JULY 14, 2023

However, as there are already 25 million terabytes of data stored in the Hive table format, migrating existing tables in the Hive table format into the Iceberg table format is necessary for performance and cost. They also provide a “ snapshot” procedure that creates an Iceberg table with a different name with the same underlying data.

Snapshot 70

Snapshot Metadata Data Warehouse Testing 70

AWS Big Data

MARCH 10, 2023

These transactional data lakes combine features from both the data lake and the data warehouse. You can simplify your data strategy by running multiple workloads and applications on the same data in the same location. The Iceberg table is synced with the AWS Glue Data Catalog.

Data Lake 105

Data Lake Sales Data Warehouse Snapshot 105

IBM Big Data Hub

SEPTEMBER 25, 2023

With a few taps on a mobile device, riders request a ride; then, Uber’s algorithms work to match them with the nearest available driver and calculate the optimal price. Uber’s prowess as a transportation, logistics and analytics company hinges on their ability to leverage data effectively. But the simplicity ends there.

OLAP 88

OLAP Data Lake Data-driven Snapshot 88

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 115

Data Lake Metadata Optimization Statistics 115

CIO Business Intelligence

MAY 16, 2022

From the factory floor to online commerce sites and containers shuttling goods across the global supply chain, the proliferation of data collected at the edge is creating opportunities for real-time insights that elevate decision-making. The concept of the edge is not new, but its role in driving data-first business is just now emerging.

IoT 75

IoT Data Warehouse Internet of Things Machine Learning 75

AWS Big Data

MARCH 2, 2023

There is an increased need for data lakes to support database like features such as ACID transactions, record-level updates and deletes, time travel, and rollback. Apache Iceberg is designed to support these features on cost-effective petabyte-scale data lakes on Amazon S3. The snapshot points to the manifest list.

Data Lake 120

Data Lake Data Processing Metadata Snapshot 120

AWS Big Data

OCTOBER 18, 2023

Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse that provides the flexibility to use provisioned or serverless compute for your analytical workloads. The decoupled compute and storage architecture of Amazon Redshift enables you to build highly scalable, resilient, and cost-effective workloads.

Analytics 98

Analytics Data Warehouse Testing Dashboards 98

AWS Big Data

OCTOBER 24, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud, providing up to five times better price-performance than any other cloud data warehouse, with performance innovation out of the box at no additional cost to you. Note that all the time values are in microseconds.

Metrics 87

Metrics Statistics Data Warehouse Cost-Benefit 87

Cloudera

MAY 13, 2021

WM simplifies troubleshooting failed jobs and optimizing slow jobs. Suggesting workloads that should move to public cloud and understanding the public cloud costs. In this blog, we walk through the Impala workloads analysis in iEDH, Cloudera’s own Enterprise Data Warehouse (EDW) implementation on CDH clusters.

Management 71

Management Data Warehouse Interactive Reporting 71

AWS Big Data

MARCH 3, 2023

Any time new test cases or test results are created or modified, events trigger such that processing is immediate and new snapshot files are available via an API or data is pulled at the refresh frequency of the reporting or business intelligence (BI) tool. Fixed-size data files avoid further latency due to unbound file sizes.

Software 52

Software Data Lake Testing Cost-Benefit 52

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. Learn more about AWS data streaming services and get started building your own data streaming solution.

Data Lake 92

Data Lake Unstructured Data Management Modeling 92

AWS Big Data

JANUARY 17, 2024

Transaction data lake use case Amazon EMR customers often use Open Table Formats to support their ACID transaction and time travel needs in a data lake. Another popular transaction data lake use case is incremental query. The following are some highlighted steps: Run a snapshot query. %%sql

Data Lake 96

Data Lake Snapshot Big Data Data-driven 96

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. It definitely depends on the type of data, no one method is always better than the other. That’s the reward.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

FineReport

MAY 31, 2023

In today’s dynamic business environment, gaining comprehensive visibility into financial data is crucial for making informed decisions. In this article, we will explore the concept of a financial dashboard, highlight its numerous benefits, and provide various kinds of financial dashboard examples for you to employ and explore.

Dashboards 52

Dashboards Key Performance Indicator Metrics Visualization 52

AWS Big Data

JULY 28, 2023

Amazon Redshift is a petabyte-scale, enterprise-grade cloud data warehouse service delivering the best price-performance. 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.

Data Lake 69

Data Lake Data Governance Data Warehouse Modeling 69

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 83

Data Lake Data Analytics Analytics Data Processing 83