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 95

Data Lake Data Processing Metadata Snapshot 95

Domino Data Lab

JANUARY 11, 2021

Data Science works best with a high degree of data granularity when the data offers the closest possible representation of what happened during actual events – as in financial transactions, medical consultations or marketing campaign results. About Domino Data Lab. Integration Features.

Recreation/Entertainment 103

Recreation/Entertainment Data Science Data Warehouse Publishing 103

AWS Big Data

MARCH 28, 2023

In a data warehouse, a dimension is a structure that categorizes facts and measures in order to enable users to answer business questions. As organizations across the globe are modernizing their data platforms with data lakes on Amazon Simple Storage Service (Amazon S3), handling SCDs in data lakes can be challenging.

Data Lake 73

Data Lake Testing Snapshot Sales 73

AWS Big Data

APRIL 27, 2023

Amazon Athena supports the MERGE command on Apache Iceberg tables, which allows you to perform inserts, updates, and deletes in your data lake at scale using familiar SQL statements that are compliant with ACID (Atomic, Consistent, Isolated, Durable).

Data Lake 74

Data Lake Snapshot Optimization Data Transformation 74

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 118

Data Lake Metadata Optimization Statistics 118

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.

Analytics 106

Analytics Data Warehouse Snapshot Cost-Benefit 106

AWS Big Data

JUNE 27, 2024

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. You can start with just a few hundred gigabytes of data and scale to a petabyte or more. This enables you to use your data to acquire new insights for your business and customers. For additional details, refer to Automated snapshots.

Snapshot 74

Snapshot Data Warehouse Data Processing Strategy 74

AWS Big Data

JANUARY 24, 2023

This solution only replicates metadata in the Data Catalog, not the actual underlying data. To have a redundant data lake using Lake Formation and AWS Glue in an additional Region, we recommend replicating the Amazon S3-based storage using S3 replication , S3 sync, aws-s3-copy-sync-using-batch or S3 Batch replication process.

Data Architecture 67

Data Architecture Metadata Data Lake Snapshot 67

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

AWS Big Data

JULY 25, 2023

It automatically provisions and intelligently scales data warehouse compute capacity to deliver fast performance, and you pay only for what you use. Just load your data and start querying right away in the Amazon Redshift Query Editor or in your favorite business intelligence (BI) tool. Ashish Agrawal is a Sr.

Metrics 81

Metrics Data Warehouse Dashboards Snapshot 81

AWS Big Data

JULY 19, 2023

Amazon Redshift is a fully managed and petabyte-scale cloud data warehouse that is used by tens of thousands of customers to process exabytes of data every day to power their analytics workload. You can structure your data, measure business processes, and get valuable insights quickly can be done by using a dimensional model.

Modeling 70

Modeling Sales Data Warehouse Snapshot 70

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 81

Data Lake Data Analytics Analytics Data Processing 81

AWS Big Data

AUGUST 16, 2023

Iceberg manages large collections of files as tables, and it supports modern analytical data lake operations such as record-level insert, update, delete, and time travel queries. Iceberg also helps guarantee data correctness under concurrent write scenarios. On the Code tab, choose Test , then Configure test event.

Data Lake 72

Data Lake Metadata Testing Snapshot 72

Corinium

APRIL 25, 2019

Ahead of the Chief Data Analytics Officers & Influencers, Insurance event we caught up with Dominic Sartorio, Senior Vice President for Products & Development, Protegrity to discuss how the industry is evolving. In data-driven organizations, data is flowing. But I’ll give an example in favour of each.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

AWS Big Data

MARCH 3, 2023

Additionally, the scale is significant because the multi-tenant data sources provide a continuous stream of testing activity, and our users require quick data refreshes as well as historical context for up to a decade due to compliance and regulatory demands. Finally, data integrity is of paramount importance.

Software 52

Software Data Lake Testing Cost-Benefit 52

AWS Big Data

JUNE 10, 2024

Enterprises and organizations across the globe want to harness the power of data to make better decisions by putting data at the center of every decision-making process. However, throughout history, data services have held dominion over their customers’ data.

Data Lake 115

Data Lake Metadata Snapshot Analytics 115

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 88

Machine Learning Metrics Big Data Management 88

AWS Big Data

JUNE 21, 2023

These types of queries are suited for a data warehouse. The goal of a data warehouse is to enable businesses to analyze their data fast; this is important because it means they are able to gain valuable insights in a timely manner. Amazon Redshift is fully managed, scalable, cloud data warehouse.

Data Warehouse 83

Data Warehouse Data Lake OLAP Cost-Benefit 83