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 74

Data Lake Testing Snapshot Sales 74

AWS Big Data

OCTOBER 17, 2023

With Amazon Redshift, you can use standard SQL to query data across your data warehouse, operational data stores, and data lake. Migrating a data warehouse can be complex. You have to migrate terabytes or petabytes of data from your legacy system while not disrupting your production workload.

Data Warehouse 90

Data Warehouse Data Processing Data Lake Management 90

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 76

Data Lake Snapshot Optimization Data Transformation 76

DataKitchen

AUGUST 19, 2021

Figure 3 shows an example processing architecture with data flowing in from internal and external sources. Each data source is updated on its own schedule, for example, daily, weekly or monthly. The data scientists and analysts have what they need to build analytics for the user. The new Recipes run, and BOOM!

Data Warehouse 246

Data Warehouse Data Lake Manufacturing Testing 246

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 102

Data Lake Data Warehouse Testing Business Objectives 102

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

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 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 105

Data Warehouse Data Lake Analytics Machine Learning 105

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 96

Data Analytics Analytics Data Warehouse Data Lake 96

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 89

Enterprise Data Warehouse Data Lake Optimization 89

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 131

Data Architecture Data Warehouse Statistics Visualization 131

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

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 96

Data Warehouse Data Lake Analytics Data Science 96

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 103

Testing Data Warehouse Metrics Cost-Benefit 103

AWS Big Data

OCTOBER 20, 2023

Today, we are pleased to announce new AWS Glue connectors for Azure Blob Storage and Azure Data Lake Storage that allow you to move data bi-directionally between Azure Blob Storage, Azure Data Lake Storage, and Amazon Simple Storage Service (Amazon S3). option("header","true").load("wasbs://yourblob@youraccountname.blob.core.windows.net/loadingtest-input/100mb")

Data Lake 88

Data Lake Big Data Consulting Data Warehouse 88

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 100

Data Warehouse Testing Data Lake Data-driven 100

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 85

Data Warehouse Visualization Snapshot Data-driven 85

AWS Big Data

MAY 7, 2024

It also makes it easier for engineers, data scientists, product managers, analysts, and business users to access data throughout an organization to discover, use, and collaborate to derive data-driven insights. Note that a managed data asset is an asset for which Amazon DataZone can manage permissions.

Metadata 78

Metadata Data Lake Data Processing Data-driven 78

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 88

Enterprise Data Warehouse Snapshot Cost-Benefit 88

AWS Big Data

FEBRUARY 15, 2024

You might be modernizing your data architecture using Amazon Redshift to enable access to your data lake and data in your data warehouse, and are looking for a centralized and scalable way to define and manage the data access based on IdP identities. For Permission mode , select Lake Formation.

Management 94

Management Data Lake Sales Data Warehouse 94

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

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

Testing 80

Testing Data Lake Cost-Benefit Data Integration 80

AWS Big Data

JUNE 28, 2023

Another example of AWS’s investment in zero-ETL is providing the ability to query a variety of data sources without having to worry about data movement. Data analysts and data engineers can use familiar SQL commands to join data across several data sources for quick analysis, and store the results in Amazon S3 for subsequent use.

Analytics 71

Analytics Data Warehouse Data Lake Data-driven 71

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 74

Data Lake Metadata Testing Snapshot 74

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

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

AWS Big Data

JULY 20, 2023

Apache Hive is a SQL-based data warehouse system for processing highly distributed datasets on the Apache Hadoop platform. The Hive metastore is a repository of metadata about the SQL tables, such as database names, table names, schema, serialization and deserialization information, data location, and partition details of each table.

Data Lake 83

Data Lake Metadata Data Processing Big Data 83

AWS Big Data

JULY 12, 2023

Introduction to Amazon Redshift Amazon Redshift is a fast, fully-managed, self-learning, self-tuning, petabyte-scale, ANSI-SQL compatible, and secure cloud data warehouse. Thousands of customers use Amazon Redshift to analyze exabytes of data and run complex analytical queries. This is often a laborious and error-prone process.

Data Warehouse 52

Data Warehouse Modeling Dashboards Data Lake 52

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

APRIL 19, 2023

Many customers run big data workloads such as extract, transform, and load (ETL) on Apache Hive to create a data warehouse on Hadoop. To configure AWS CLI interaction with AWS, refer to Quick setup. json ) to DynamoDB (for more information, refer to Write data to a table using the console or AWS CLI ): { "name": "step1.q",

Metadata 82

Metadata Testing Data Lake Consulting 82

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

JUNE 6, 2023

These are six main steps in the data pipeline: Amazon EventBridge triggers an AWS Lambda function when the event pattern for AWS Glue Data Quality matches the defined rule. For more information, refer to Working with Query Results, Output Files, and Query History. For S3 path , enter the S3 path to your data source. (

Data Quality 74

Data Quality Metrics Visualization Dashboards 74

AWS Big Data

FEBRUARY 8, 2023

Test the connection with SAP using the wheel file. For more information, refer to Download and Installation of NW RFC SDK. For instructions, refer to Configuration basics. For instructions, refer to Configuration basics. Deenbandhu Prasad is a Senior Analytics Specialist at AWS, specializing in big data services.

Testing 76

Testing Data Integration Data Lake Enterprise 76

AWS Big Data

FEBRUARY 8, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Amazon Redshift enables you to run complex SQL analytics at scale and performance on terabytes to petabytes of structured and unstructured data, and make the insights widely available through popular business intelligence (BI) and analytics tools.

Data Quality 79

Data Quality Testing Data Warehouse Unstructured Data 79

IBM Big Data Hub

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Prescriptive analytics: Prescriptive analytics predicts likely outcomes and makes decision recommendations.

Data Science 84

Data Science Data Analytics Prescriptive Analytics Analytics 84

AWS Big Data

SEPTEMBER 21, 2023

Satori integrates natively with both Amazon Redshift provisioned clusters and Amazon Redshift Serverless for easy setup of your Amazon Redshift data warehouse in the secure Satori portal. In part 2, we will explore how to set up self-service data access with Satori to data stored in Amazon Redshift.

Data Warehouse 89

Data Warehouse Interactive Data Architecture Data Lake 89

Jet Global

JANUARY 15, 2021

In this respect, we often hear references to “switching costs” and “stickiness.” Virtually every ERP implementation or upgrade requires substantial effort to design, build, or modify, and then to test reports. A non-developer can build a custom data warehouse with Jet Analytics in as little as 30 minutes.

Cost-Benefit 72

Cost-Benefit Data Lake Reporting OLAP 72