AWS Big Data

AUGUST 31, 2023

Amazon Redshift is a fast, fully managed petabyte-scale cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools. Amazon Redshift also supports querying nested data with complex data types such as struct, array, and map.

Data Lake 109

Data Lake Data Warehouse Metadata Data Architecture 109

AWS Big Data

DECEMBER 4, 2024

SageMaker still includes all the existing ML and AI capabilities you’ve come to know and love for data wrangling, human-in-the-loop data labeling with Amazon SageMaker Ground Truth , experiments, MLOps, Amazon SageMaker HyperPod managed distributed training, and more. The tools to transform your business are here.

Data Analytics 87

Data Analytics Analytics Data Lake Data Quality 87

AWS Big Data

NOVEMBER 7, 2024

Amazon Redshift is a fully managed, AI-powered cloud data warehouse that delivers the best price-performance for your analytics workloads at any scale. Refer to Easy analytics and cost-optimization with Amazon Redshift Serverless to get started. For this post, we use Redshift Serverless. Choose Run all on each notebook tab.

Metadata 98

Metadata Sales Data Warehouse Optimization 98

AWS Big Data

OCTOBER 30, 2024

Amazon Redshift is a fast, scalable, secure, and fully managed cloud data warehouse that makes it simple and cost-effective to analyze your data using standard SQL and your existing business intelligence (BI) tools. Data ingestion is the process of getting data to Amazon Redshift.

Data Warehouse 91

Data Warehouse Sales Data Lake Recreation/Entertainment 91

AWS Big Data

OCTOBER 1, 2024

Amazon Redshift enables you to efficiently query and retrieve structured and semi-structured data from open format files in Amazon S3 data lake without having to load the data into Amazon Redshift tables. Amazon Redshift extends SQL capabilities to your data lake, enabling you to run analytical queries.

Data Lake 107

Data Lake Statistics Broadcasting Optimization 107

Jet Global

NOVEMBER 5, 2020

That stands for “bring your own database,” and it refers to a model in which core ERP data are replicated to a separate standalone database used exclusively for reporting. OLAP reporting has traditionally relied on a data warehouse. Option 3: Azure Data Lakes. Data lakes are not a mature technology.

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Data Lake OLAP Data Warehouse Unstructured Data 98

AWS Big Data

DECEMBER 9, 2024

Today, many customers build data quality validation pipelines using its Data Quality Definition Language (DQDL) because with static rules, dynamic rules , and anomaly detection capability , its fairly straightforward. One of its key features is the ability to manage data using branches.

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Data Quality Publishing Snapshot Data Lake 111

AWS Big Data

NOVEMBER 14, 2024

This post explores how to start using Delta Lake UniForm on Amazon Web Services (AWS). You can learn how to query Delta Lake native tables through UniForm from different data warehouses or engines such as Amazon Redshift as an example of expanding data access to more engines. in Delta Lake public document.

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Metadata Data Warehouse Big Data Data Lake 112

AWS Big Data

MAY 30, 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. Solution overview Amazon Redshift is an industry-leading cloud data warehouse.

Data Warehouse 101

Data Warehouse Data Lake Cost-Benefit Structured Data 101

AWS Big Data

MARCH 2, 2023

Iceberg has become very popular for its support for ACID transactions in data lakes and features like schema and partition evolution, time travel, and rollback. and later supports the Apache Iceberg framework for data lakes. AWS Glue 3.0 The following diagram illustrates the solution architecture.

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Data Lake Data Processing Metadata Snapshot 129

Jet Global

SEPTEMBER 4, 2020

Its solution was to replicate data from the production database, using data entities, into a traditional relational database. Microsoft referred to this approach as “bring your own database” (BYOD). For more sophisticated multidimensional reporting functions, however, a more advanced approach to staging data is required.

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

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. Of those tables, some are larger (such as in terms of record volume) than others, and some are updated more frequently than others.

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Data Lake Data Processing Metadata Snapshot 105

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 126

Data Lake Metadata Statistics Optimization 126

AWS Big Data

JANUARY 6, 2025

Amazon AppFlow automatically encrypts data in motion, and allows you to restrict data from flowing over the public internet for SaaS applications that are integrated with AWS PrivateLink , reducing exposure to security threats. Refer to the Amazon Redshift Database Developer Guide for more details.

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Analytics Data Warehouse Big Data Metrics 95

AWS Big Data

JULY 31, 2024

In the current industry landscape, data lakes have become a cornerstone of modern data architecture, serving as repositories for vast amounts of structured and unstructured data. Maintaining data consistency and integrity across distributed data lakes is crucial for decision-making and analytics.

Data Lake 113

Data Lake Marketing Data Processing Management 113

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.

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Data Warehouse Data Lake OLAP Cost-Benefit 93

AWS Big Data

APRIL 3, 2024

licensed, 100% open-source data table format that helps simplify data processing on large datasets stored in data lakes. Data engineers use Apache Iceberg because it’s fast, efficient, and reliable at any scale and keeps records of how datasets change over time.

Data Lake 107

Data Lake Snapshot Metadata Data Architecture 107

AWS Big Data

JUNE 10, 2024

One of the key challenges in modern big data management is facilitating efficient data sharing and access control across multiple EMR clusters. Organizations have multiple Hive data warehouses across EMR clusters, where the metadata gets generated. Test access using SageMaker Studio in the consumer account.

Data Lake 98

Data Lake Metadata Data Warehouse Data Processing 98

AWS Big Data

DECEMBER 12, 2024

One-time and complex queries are two common scenarios in enterprise data analytics. Complex queries, on the other hand, refer to large-scale data processing and in-depth analysis based on petabyte-level data warehouses in massive data scenarios. Here, data modeling uses dbt on Amazon Redshift.

Snapshot 81

Snapshot Recreation/Entertainment Experimentation Data Lake 81

AWS Big Data

AUGUST 22, 2024

In this post, we discuss how the Kaplan data engineering team implemented data integration from the Salesforce application to Amazon Redshift. Solution overview The high-level data flow starts with the source data stored in Amazon S3 and then integrated into Amazon Redshift using various AWS services.

Data Warehouse 114

Data Warehouse Data Lake Data Integration Management 114

AWS Big Data

MARCH 27, 2023

Amazon Redshift Serverless makes it simple to run and scale analytics without having to manage your data warehouse infrastructure. For more details on tagging, refer to Tagging resources overview. For more tagging best practices, refer to Tagging AWS resources. Choose Save changes. About the Authors Sandeep Bajwa is a Sr.

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Data Warehouse Management Snapshot Data Lake 93

AWS Big Data

DECEMBER 4, 2024

With this new functionality, customers can create up-to-date replicas of their data from applications such as Salesforce, ServiceNow, and Zendesk in an Amazon SageMaker Lakehouse and Amazon Redshift. SageMaker Lakehouse gives you the flexibility to access and query your data in-place with all Apache Iceberg compatible tools and engines.

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Data Integration Data Lake Statistics Data-driven 99

AWS Big Data

JULY 21, 2023

This leads to having data across many instances of data warehouses and data lakes using a modern data architecture in separate AWS accounts. We recently announced the integration of Amazon Redshift data sharing with AWS Lake Formation.

Data Lake 94

Data Lake Data Warehouse Marketing Management 94

AWS Big Data

OCTOBER 14, 2024

Enterprise data is brought into data lakes and data warehouses to carry out analytical, reporting, and data science use cases using AWS analytical services like Amazon Athena , Amazon Redshift , Amazon EMR , and so on.

Metadata 91

Metadata Data Lake Modeling Data Warehouse 91

AWS Big Data

FEBRUARY 24, 2023

Data lakes are a popular choice for today’s organizations to store their data around their business activities. As a best practice of a data lake design, data should be immutable once stored. A data lake built on AWS uses Amazon Simple Storage Service (Amazon S3) as its primary storage environment.

Data Lake 92

Data Lake Metadata Testing Data Warehouse 92

AWS Big Data

MAY 24, 2023

When you build your transactional data lake using Apache Iceberg to solve your functional use cases, you need to focus on operational use cases for your S3 data lake to optimize the production environment. For more information, refer to Retry Amazon S3 requests with EMRFS. availability.

Data Lake 93

Data Lake Snapshot Metadata Optimization 93

AWS Big Data

MAY 20, 2024

Whether you are new to Apache Iceberg on AWS or already running production workloads on AWS, this comprehensive technical guide offers detailed guidance on foundational concepts to advanced optimizations to build your transactional data lake with Apache Iceberg on AWS. He can be reached via LinkedIn. He can be reached via LinkedIn.

Data Lake 110

Data Lake Big Data Cost-Benefit Data Warehouse 110

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 100

Data Warehouse Data Processing Data Lake Management 100

AWS Big Data

DECEMBER 20, 2024

You can now generate data integration jobs for various data sources and destinations, including Amazon Simple Storage Service (Amazon S3) data lakes with popular file formats like CSV, JSON, and Parquet, as well as modern table formats such as Apache Hudi , Delta , and Apache Iceberg.

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Data Integration Visualization Data Processing Data Lake 96

AWS Big Data

AUGUST 1, 2023

Although Jira Cloud provides reporting capability, loading this data into a data lake will facilitate enrichment with other business data, as well as support the use of business intelligence (BI) tools and artificial intelligence (AI) and machine learning (ML) applications. Search for the Jira Cloud connector.

Data Lake 93

Data Lake Data Transformation Data-driven Cost-Benefit 93

O'Reilly on Data

OCTOBER 19, 2021

but to reference concrete tooling used today in order to ground what could otherwise be a somewhat abstract exercise. Adapted from the book Effective Data Science Infrastructure. ML use cases rarely dictate the master data management solution, so the ML stack needs to integrate with existing data warehouses.

IT 364

IT Testing Experimentation Software 364

CIO Business Intelligence

APRIL 25, 2024

Currently, a handful of startups offer “reverse” extract, transform, and load (ETL), in which they copy data from a customer’s data warehouse or data platform back into systems of engagement where business users do their work. Sharing Customer 360 insights back without data replication.

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Data Integration Data Lake Data Warehouse Metadata 119

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).

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Data Lake Snapshot Optimization Data Transformation 83

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.

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Data Warehouse Data Lake Visualization Big Data 145

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.

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Data Lake Testing Snapshot Big Data 82

CIO Business Intelligence

JUNE 29, 2022

Azure Data Factory. Data Explorer is a big data analytics platform that you can use, as the name suggests, for exploring data using KQL, also known as the Kusto Query Language, from the codename for the project which may or may not be a reference to exploring your ocean of data as if you were Jacques Cousteau.

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Data Lake Analytics Data Warehouse Machine Learning 116

AWS Big Data

JUNE 25, 2024

This post is co-authored by Vijay Gopalakrishnan, Director of Product, Salesforce Data Cloud. In today’s data-driven business landscape, organizations collect a wealth of data across various touch points and unify it in a central data warehouse or a data lake to deliver business insights.

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Data Lake Cost-Benefit Data-driven Data Warehouse 113