AWS Big Data

MARCH 16, 2023

Amazon Redshift is a fully managed data warehouse service that tens of thousands of customers use to manage analytics at scale. Together with price-performance , Amazon Redshift enables you to use your data to acquire new insights for your business and customers while keeping costs low.

Data Warehouse 52

Data Warehouse Testing Snapshot Modeling 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.

Metrics 83

Metrics Data Warehouse Dashboards Snapshot 83

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. You can get faster insights without spending valuable time managing your data warehouse. Fault tolerance is built in.

Analytics 100

Analytics Data Warehouse Testing Dashboards 100

Cloudera

JULY 14, 2023

While these instructions are carried out for Cloudera Data Platform (CDP), Cloudera Data Engineering, and Cloudera Data Warehouse, one can extrapolate them easily to other services and other use cases as well. You want to let your clients or jobs continue writing the data to the table.

Snapshot 69

Snapshot Metadata Data Warehouse Testing 69

AWS Big Data

NOVEMBER 29, 2023

dbt is an open source, SQL-first templating engine that allows you to write repeatable and extensible data transforms in Python and SQL. dbt is predominantly used by data warehouses (such as Amazon Redshift ) customers who are looking to keep their data transform logic separate from storage and engine.

Data Lake 108

Data Lake Management Metrics Data Warehouse 108

AWS Big Data

NOVEMBER 10, 2023

This integration expands the possibilities for AWS analytics and machine learning (ML) solutions, making the data warehouse accessible to a broader range of applications. Your applications can seamlessly read from and write to your Amazon Redshift data warehouse while maintaining optimal performance and transactional consistency.

Data Processing 97

Data Processing Data Lake Data Warehouse Optimization 97

AWS Big Data

DECEMBER 13, 2023

A CDC-based approach captures the data changes and makes them available in data warehouses for further analytics in real-time. usually a data warehouse) needs to reflect those changes in near real-time. This post showcases how to use streaming ingestion to bring data to Amazon Redshift.

Data Warehouse 102

Data Warehouse Snapshot Data Processing Management 102

AWS Big Data

MARCH 2, 2023

Whenever there is an update to the Iceberg table, a new snapshot of the table is created, and the metadata pointer points to the current table metadata file. At the top of the hierarchy is the metadata file, which stores information about the table’s schema, partition information, and snapshots. all_reviews ): data and metadata.

Data Lake 122

Data Lake Data Processing Metadata Snapshot 122

AWS Big Data

SEPTEMBER 13, 2023

The Analytics specialty practice of AWS Professional Services (AWS ProServe) helps customers across the globe with modern data architecture implementations on the AWS Cloud. We begin with a Data lake reference architecture followed by an overview of operational data processing framework.

Data Lake 95

Data Lake Data Processing Metadata Snapshot 95

AWS Big Data

APRIL 27, 2023

It supports modern analytical data lake operations such as create table as select (CTAS), upsert and merge, and time travel queries. Athena also supports the ability to create views and perform VACUUM (snapshot expiration) on Apache Iceberg tables to optimize storage and performance.

Data Lake 76

Data Lake Snapshot Optimization Data Transformation 76

AWS Big Data

OCTOBER 20, 2023

The connectors were only able to reference hostnames in the connector configuration or plugin that are publicly resolvable and couldn’t resolve private hostnames defined in either a private hosted zone or use DNS servers in another customer network. For instructions, refer to create key-pair here. For instructions, refer to here.

Data Processing 91

Data Processing Snapshot Data Warehouse Management 91

Cloudera

JULY 13, 2023

A range of Iceberg table analysis such as listing table’s data file, selecting table snapshot, partition filtering, and predicate filtering can be delegated through Iceberg Java API instead, obviating the need for each query engine to implement it themself. The data files and metadata files in Iceberg format are immutable.

Metadata 69

Metadata Snapshot Data Warehouse Statistics 69

AWS Big Data

AUGUST 16, 2023

Most businesses store their critical data in a data lake, where you can bring data from various sources to a centralized storage. Change Data Capture (CDC) in the context of a data lake refers to the process of capturing and propagating changes made to source data.

Data Lake 74

Data Lake Metadata Testing Snapshot 74

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. Test SCD Type 2 implementation With the infrastructure in place, you’re ready to test out the overall solution design and query historical records from the employee dataset.

Data Lake 74

Data Lake Testing Snapshot Sales 74

AWS Big Data

FEBRUARY 1, 2023

Architecturally, we chose a serverless model, and the data lake architecture action line refers to all the architectural gaps and challenging features we determined were part of the improvements. To query data from REST APIs and other data sources, we used PySpark and JDBC modules.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

AWS Big Data

MAY 30, 2023

Data lakes are not transactional by default; however, there are multiple open-source frameworks that enhance data lakes with ACID properties, providing a best of both worlds solution between transactional and non-transactional storage mechanisms. The reference data is continuously replicated from MySQL to DynamoDB through AWS DMS.

Data Lake 83

Data Lake Data Analytics Analytics Data Processing 83

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. This post is not intended to provide detailed technical guidance (e.g.

Data Lake 118

Data Lake Metadata Optimization Statistics 118

IBM Big Data Hub

APRIL 8, 2024

Can Amazon RDS for Db2 be used for running data warehousing workloads? Answer : Yes, Amazon RDS for Db2 can support analytics workloads, but it is not a data warehouse. Amazon RDS Refer to the Amazon RDS for Db2 pricing page for instances supported.   Scalability 5.

Snapshot 76

Snapshot Data Warehouse Data Processing Management 76

O'Reilly on Data

OCTOBER 19, 2021

We need robust versioning for data, models, code, and preferably even the internal state of applications—think Git on steroids to answer inevitable questions: What changed? The applications must be integrated to the surrounding business systems so ideas can be tested and validated in the real world in a controlled manner. Versioning.

IT 346

IT Testing Experimentation Software 346