AWS Big Data

FEBRUARY 16, 2023

Amazon Redshift is the most widely used data warehouse in the cloud, best suited for analyzing exabytes of data and running complex analytical queries. Amazon QuickSight is a fast business analytics service to build visualizations, perform ad hoc analysis, and quickly get business insights from your data.

Data Warehouse 83

Data Warehouse Sales Visualization Data Processing 83

AWS Big Data

NOVEMBER 17, 2023

dbt (DataBuildTool) offers this mechanism by introducing a well-structured framework for data analysis, transformation and orchestration. It also applies general software engineering principles like integrating with git repositories, setting up DRYer code, adding functional test cases, and including external libraries.

Snapshot 93

Snapshot Data Processing Testing Data Warehouse 93

AWS Big Data

NOVEMBER 29, 2023

As part of the Talent Intelligence Platform Eightfold also exposes a data hub where each customer can access their Amazon Redshift-based data warehouse and perform ad hoc queries as well as schedule queries for reporting and data export. Many customers have implemented Amazon Redshift to support multi-tenant applications.

Metadata 104

Metadata Data Warehouse Analytics Data Analytics 104

AWS Big Data

MARCH 27, 2024

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. Complete the implementation tasks such as data ingestion and performance testing.

Testing 101

Testing Data Warehouse Metrics Cost-Benefit 101

DataKitchen

AUGUST 19, 2021

Each data source is updated on its own schedule, for example, daily, weekly or monthly. The DataKitchen Platform ingests data into a data lake and runs Recipes to create a data warehouse leveraged by users and self-service data analysts. The third set of domains are cached data sets (e.g.,

Data Warehouse 246

Data Warehouse Data Lake Manufacturing Testing 246

CIO Business Intelligence

OCTOBER 13, 2023

Data architect Armando Vázquez identifies eight common types of data architects: Enterprise data architect: These data architects oversee an organization’s overall data architecture, defining data architecture strategy and designing and implementing architectures.

Data Architecture 122

Data Architecture Data Warehouse Statistics Visualization 122

AWS Big Data

OCTOBER 26, 2023

times better price-performance than other cloud data warehouses on real-world workloads using advanced techniques like concurrency scaling to support hundreds of concurrent users, enhanced string encoding for faster query performance, and Amazon Redshift Serverless performance enhancements. Amazon Redshift delivers up to 4.9

Data Warehouse 98

Data Warehouse Cost-Benefit Dashboards Optimization 98

DataKitchen

SEPTEMBER 21, 2023

What is Data in Place? Data in Place refers to the organized structuring and storage of data within a specific storage medium, be it a database, bucket store, files, or other storage platforms. This focus on evaluation and testing should be relentless and critical in the ‘last mile’ of the Data Journey.

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

AWS Big Data

APRIL 3, 2023

Tens of thousands of customers run business-critical workloads on Amazon Redshift , AWS’s fast, petabyte-scale cloud data warehouse delivering the best price-performance. With Amazon Redshift, you can query data across your data warehouse, operational data stores, and data lake using standard SQL.

Data Warehouse 99

Data Warehouse Testing Data Lake Data-driven 99

AWS Big Data

MAY 28, 2024

The details of each step are as follows: Populate the Amazon Redshift Serverless data warehouse with company stock information stored in Amazon Simple Storage Service (Amazon S3). Redshift Serverless is a fully functional data warehouse holding data tables maintained in real time. This is testing for hallucination.

Unstructured Data 88

Unstructured Data Structured Data Data Warehouse Testing 88

AWS Big Data

MARCH 18, 2024

Load generic address data to Amazon Redshift Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Redshift Serverless makes it straightforward to run analytics workloads of any size without having to manage data warehouse infrastructure.

Data Warehouse 83

Data Warehouse Visualization Snapshot Data-driven 83

AWS Big Data

MAY 9, 2024

Your analytic solution architecture should be able to handle large data volumes at high concurrency and without compromising speed, thereby delivering a scalable high-performance analytics environment. Amazon Redshift Serverless provides a fully managed, petabyte-scale, auto scaling cloud data warehouse to support high-concurrency analytics.

Testing 81

Testing Cost-Benefit Optimization Reporting 81

AWS Big Data

FEBRUARY 13, 2023

We live in a data-producing world, and as companies want to become data driven, there is the need to analyze more and more data. These analyses are often done using data warehouses. Status quo before migration Here at OLX Group, Amazon Redshift has been our choice for data warehouse for over 5 years.

Snapshot 69

Snapshot Data Warehouse Testing Analytics 69

DataKitchen

NOVEMBER 20, 2021

Many organizations take weeks to procure and prep data sets. A DataOps Engineer can make test data available on demand. If we can provide shortcuts to members of the data team, we can help improve their productivity. . We have data profiling tools that we run to compare versions of datasets.

Testing 246

Testing Machine Learning Data Warehouse Reporting 246

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

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 87

Enterprise Data Warehouse Data Lake Optimization 87

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.

IT 342

IT Testing Experimentation Software 342

AWS Big Data

MARCH 27, 2024

These services enable you to collect and analyze data in near real time and put a comprehensive data governance framework in place that uses granular access control to secure sensitive data from unauthorized users. This will be your online transaction processing (OLTP) data store for transactional data.

Data Analytics 93

Data Analytics Analytics Data Warehouse Data Lake 93

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 98

Analytics Data Warehouse Testing Dashboards 98

AWS Big Data

FEBRUARY 16, 2024

Many customers are extending their data warehouse capabilities to their data lake with Amazon Redshift. They are looking to further enhance their security posture where they can enforce access policies on their data lakes based on Amazon Simple Storage Service (Amazon S3).

Data Lake 100

Data Lake Data Warehouse Testing Business Objectives 100

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 70

Snapshot Data Warehouse Data Processing Management 70

AWS Big Data

NOVEMBER 1, 2023

You can use Redshift ML to automate data preparation, preprocessing, and selection of your problem type (for more information, refer to Create, train, and deploy machine learning models in Amazon Redshift using SQL with Amazon Redshift ML ). Please refer to this GitHub repository for sample scripts to automate model versioning.

Modeling 100

Modeling Data Warehouse Machine Learning Recreation/Entertainment 100

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 105

Data Lake Management Metrics Data Warehouse 105

AWS Big Data

NOVEMBER 29, 2023

In 2013, Amazon Web Services revolutionized the data warehousing industry by launching Amazon Redshift , the first fully-managed, petabyte-scale, enterprise-grade cloud data warehouse. Amazon Redshift made it simple and cost-effective to efficiently analyze large volumes of data using existing business intelligence tools.

Data Warehouse 103

Data Warehouse Data Lake Analytics Machine Learning 103

AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 86

Enterprise Data Warehouse Snapshot Cost-Benefit 86

AWS Big Data

NOVEMBER 13, 2023

Amazon Redshift is a fully managed data warehousing service that offers both provisioned and serverless options, making it more efficient to run and scale analytics without having to manage your data warehouse. These upstream data sources constitute the data producer components.

Data Warehouse 94

Data Warehouse Data Lake Analytics Data Science 94

Cloudera

DECEMBER 12, 2018

After having rebuilt their data warehouse, I decided to take a little bit more of a pointed role, and I joined Oracle as a database performance engineer. I spent eight years in the real-world performance group where I specialized in high visibility and high impact data warehousing competes and benchmarks.

Data Warehouse 42

Data Warehouse Marketing Big Data Data Lake 42

AWS Big Data

APRIL 25, 2024

Amazon Managed Workflows for Apache Airflow (Amazon MWAA) is a managed orchestration service for Apache Airflow that you can use to set up and operate data pipelines in the cloud at scale. Apache Airflow is an open source tool used to programmatically author, schedule, and monitor sequences of processes and tasks, referred to as workflows.

Metadata 106

Metadata Data Processing Management Testing 106

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

NOVEMBER 27, 2023

Amazon Redshift , the most widely used cloud data warehouse, has evolved significantly to meet the performance requirements of the most demanding workloads. This post covers one such new feature—the multidimensional data layout sort key. Refer to Working with automatic table optimization for more details on ATO.

Cost-Benefit 101

Cost-Benefit Data Warehouse Optimization Testing 101

Cloudera

AUGUST 31, 2021

Cloudera and Accenture demonstrate strength in their relationship with an accelerator called the Smart Data Transition Toolkit for migration of legacy data warehouses into Cloudera Data Platform. Accenture’s Smart Data Transition Toolkit . Are you looking for your data warehouse to support the hybrid multi-cloud?

Data Warehouse 82

Data Warehouse Cost-Benefit Metadata Data-driven 82

Smart Data Collective

OCTOBER 17, 2022

A point of data entry in a given pipeline. Examples of an origin include storage systems like data lakes, data warehouses and data sources that include IoT devices, transaction processing applications, APIs or social media. The final point to which the data has to be eventually transferred is a destination.

Data Warehouse 131

Data Warehouse Data Lake Visualization Big Data 131

AWS Big Data

MAY 18, 2023

You can discover and connect to over 70 diverse data sources, manage your data in a centralized data catalog, and create, run, and monitor data integration pipelines to load data into your data lakes and your data warehouses. For more details, refer to Spark Release 3.3.0 runtime ( 3.5

Testing 79

Testing Data Lake Cost-Benefit Data Integration 79

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 95

Data Processing Data Lake Data Warehouse Optimization 95

AWS Big Data

JUNE 2, 2023

Amazon Redshift is a widely used, fully managed, petabyte-scale cloud data warehouse. Tens of thousands of customers use Amazon Redshift to process exabytes of data every day to power their analytic workloads. For more information, refer to Migrate Google BigQuery to Amazon Redshift using AWS Schema Conversion tool (SCT).

Metadata 113

Metadata Data Warehouse Big Data Testing 113

Smart Data Collective

JUNE 6, 2021

Before diving into whether or not Google BigQuery is the future of big data analytics, it’s vital to firstly understand what “big data analytics” actually means. If your company revolves around the manufacturing of goods or services, for example, big data can aid you in the development of your products. References.

Big Data 132

Big Data Data Analytics Analytics Cost-Benefit 132

Cloudera

FEBRUARY 12, 2024

In this blog, we’ll take you through our tried and tested best practices for setting up your DNS for use with Cloudera on Azure. Please refer to the Microsoft documentation for detail. ” For Liftie-based data services: the entitlement “LIFTIE_AKS_DISABLE_PRIVATE_DNS_ZONE” must be set.

Data Warehouse 52

Data Warehouse Machine Learning Data Lake Management 52