Alation

AUGUST 4, 2022

It’s been one decade since the “ Big Data Era ” began (and to much acclaim!). Analysts asked, What if we could manage massive volumes and varieties of data? Yet the question remains: How much value have organizations derived from big data? Big Data as an Enabler of Digital Transformation.

Big Data 95

Big Data Digital Transformation Data Lake Data-driven 95

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 86

Data Lake Metadata Testing Data Warehouse 86

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. availability. Note the configuration parameters s3.write.tags.write-tag-name write.tags.write-tag-name and s3.delete.tags.delete-tag-name

Data Lake 87

Data Lake Snapshot Metadata Optimization 87

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

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 88

Data Warehouse Data Processing Data Lake Management 88

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

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

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

DECEMBER 21, 2023

To speed up the self-service analytics and foster innovation based on data, a solution was needed to provide ways to allow any team to create data products on their own in a decentralized manner. To create and manage the data products, smava uses Amazon Redshift , a cloud data warehouse.

Data Lake 91

Data Lake Data Warehouse Data-driven B2B 91

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

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 127

Data Architecture Data Warehouse Statistics Visualization 127

AWS Big Data

NOVEMBER 8, 2023

Because Gilead is expanding into biologics and large molecule therapies, and has an ambitious goal of launching 10 innovative therapies by 2030, there is heavy emphasis on using data with AI and machine learning (ML) to accelerate the drug discovery pipeline. Loading data is a key process for any analytical system, including Amazon Redshift.

Data Lake 78

Data Lake Data Warehouse Cost-Benefit Optimization 78

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

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 86

Data Lake Big Data Consulting Data Warehouse 86

Smart Data Collective

OCTOBER 17, 2022

Big data is shaping our world in countless ways. Data powers everything we do. Exactly why, the systems have to ensure adequate, accurate and most importantly, consistent data flow between different systems. A point of data entry in a given pipeline. The destination is decided by the use case of the data pipeline.

Data Warehouse 131

Data Warehouse Data Lake Visualization Big Data 131

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

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

DataKitchen

JULY 27, 2023

Let’s go through the ten Azure data pipeline tools Azure Data Factory : This cloud-based data integration service allows you to create data-driven workflows for orchestrating and automating data movement and transformation. You can use it for big data analytics and machine learning workloads.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

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

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 77

Metadata Data Lake Data Processing Data-driven 77

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

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

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. Select the data share and choose Authorize.

Management 91

Management Data Lake Sales Data Warehouse 91

AWS Big Data

MARCH 27, 2024

You can send data from your streaming source to this resource for ingesting the data into a Redshift data warehouse. This will be your online transaction processing (OLTP) data store for transactional data. With continuous innovations added to Amazon Redshift, it is now more than just a data warehouse.

Data Analytics 93

Data Analytics Analytics Data Warehouse Data Lake 93

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

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 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

FEBRUARY 13, 2024

Choose Add new data source. Choose Save & test. Now the CloudWatch data source has been registered. Copy the data source ID from the URL [link].amazonaws.com/datasources/edit/ About the Authors Noritaka Sekiyama is a Principal Big Data Architect on the AWS Glue team. Choose Administration.

Metrics 100

Metrics Dashboards Visualization Key Performance Indicator 100

IBM Big Data Hub

JANUARY 18, 2023

In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. It required a different data platform solution. Hence, Data Lake emerged, which handles unstructured and structured data with huge volume. Data lakehouse was created to solve these problems.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

AWS Big Data

MARCH 3, 2023

Tricentis is the global leader in continuous testing for DevOps, cloud, and enterprise applications. Speed changes everything, and continuous testing across the entire CI/CD lifecycle is the key. Tricentis instills that confidence by providing software tools that enable Agile Continuous Testing (ACT) at scale.

Software 52

Software Data Lake Testing Cost-Benefit 52

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. Interesting times.

Data Warehouse 42

Data Warehouse Marketing Big Data Data Lake 42

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

NOVEMBER 9, 2023

A modern data platform entails maintaining data across multiple layers, targeting diverse platform capabilities like high performance, ease of development, cost-effectiveness, and DataOps features such as CI/CD, lineage, and unit testing. AWS Glue – AWS Glue is used to load files into Amazon Redshift through the S3 data lake.

Data Warehouse 107

Data Warehouse Testing Data Quality Reporting 107

Cloudera

NOVEMBER 29, 2021

Managing data and its flow, from the edge to the cloud, is one of the most important tasks in the process of gaining data intelligence. . The category Data Lifecycle Connection highlights organizations that work with multiple parts of the data lifecycle to collect, enrich, report, serve, and predict. .

Data Lake 77

Data Lake Data Warehouse Data Architecture Reporting 77

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

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. Refer to Develop and test AWS Glue version 3.0

Testing 79

Testing Data Lake Cost-Benefit Data Integration 79

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