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.

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Data Warehouse Testing Data Lake Data-driven 95

Smart Data Collective

AUGUST 9, 2019

However, more mainstream games use big data as well. Fortnite is one of the games that uses big data to offer great service to its customers. Even Forbes Tech Council has written about the benefits of data lakes in Fortnite. As it turns out, Epic uses a data lake for this massive undertaking.

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Big Data Data Lake Data Architecture Machine Learning 78

AWS Big Data

JULY 28, 2023

However, Athena also allows you to query data stored in 30 different data sources—in addition to Amazon S3—including relational, non-relational, and object stores running on premises or in other cloud environments. In Athena, we refer to queries on non-Amazon S3 data sources as federated queries. Pathik Shah is a Sr.

Big Data 76

Big Data Data Architecture Data Lake Interactive 76

AWS Big Data

MAY 18, 2023

It’s even harder when your organization is dealing with silos that impede data access across different data stores. Seamless data integration is a key requirement in a modern data architecture to break down data silos. For more details, refer to Spark Release 3.3.0 AWS Glue Data Catalog client 3.6.0

Testing 73

Testing Data Lake Cost-Benefit Data Integration 73

AWS Big Data

FEBRUARY 6, 2023

Use case overview Migrating Hadoop workloads to Amazon EMR accelerates big data analytics modernization, increases productivity, and reduces operational cost. Refactoring coupled compute and storage to a decoupling architecture is a modern data solution. George Zhao is a Senior Data Architect at AWS ProServe.

Cost-Benefit 52

Cost-Benefit Data Lake Dashboards Big Data 52

AWS Big Data

MARCH 28, 2023

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 68

Data Lake Testing Snapshot Sales 68

Cloudera

DECEMBER 19, 2018

Data analytics priorities have shifted this year. Don’t blink or you might miss what leading organizations are doing to modernize their analytic and data warehousing environments. Natural language analytics and streaming data analytics are emerging technologies that will impact the market.

Data Warehouse 54

Data Warehouse Analytics Big Data Data Architecture 54

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.

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Data Lake Metadata Optimization Statistics 109

AWS Big Data

JANUARY 24, 2023

This solution only replicates metadata in the Data Catalog, not the actual underlying data. To have a redundant data lake using Lake Formation and AWS Glue in an additional Region, we recommend replicating the Amazon S3-based storage using S3 replication , S3 sync, aws-s3-copy-sync-using-batch or S3 Batch replication process.

Data Architecture 64

Data Architecture Metadata Data Lake Snapshot 64

AWS Big Data

FEBRUARY 14, 2023

Organizations have chosen to build data lakes on top of Amazon Simple Storage Service (Amazon S3) for many years. A data lake is the most popular choice for organizations to store all their organizational data generated by different teams, across business domains, from all different formats, and even over history.

Data Lake 77

Data Lake Statistics Data Architecture Finance 77

BizAcuity

APRIL 14, 2022

The comprehensive system which collectively includes generating data, storing the data, aggregating and analyzing the data, the tools, platforms and other softwares involved is referred to as Big Data Ecosystem. Competitive Advantages to using Big Data Analytics. Unscalable data architecture.

Big Data 52

Big Data Data Analytics Management Unstructured Data 52

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.

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Data Warehouse Data Lake Analytics Data Science 88

AWS Big Data

AUGUST 2, 2023

Using existing analytics tools such as Amazon Athena and Amazon QuickSight an organization can gain insight into its estimated carbon footprint. The data architecture diagram below shows an example of how you could use AWS services to calculate and visualize an organization’s estimated carbon footprint.

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Data Lake Measurement Visualization Data Architecture 68

AWS Big Data

JANUARY 22, 2024

Cost and resource efficiency – This is an area where Acast observed a reduction in data duplication, and therefore cost reduction (in some accounts, removing the copy of data 100%), by reading data across accounts while enabling scaling. In this approach, teams responsible for generating data are referred to as producers.

Data-driven 82

Data-driven Advertising Metadata Data Architecture 82

AWS Big Data

JUNE 7, 2023

Cargotec captures terabytes of IoT telemetry data from their machinery operated by numerous customers across the globe. This data needs to be ingested into a data lake, transformed, and made available for analytics, machine learning (ML), and visualization. mode('overwrite').save(output_path mode('overwrite').save(output_path

Metadata 55

Metadata Data Lake Machine Learning Big Data 55

AWS Big Data

MARCH 3, 2023

Building data lakes from continuously changing transactional data of databases and keeping data lakes up to date is a complex task and can be an operational challenge. You can then apply transformations and store data in Delta format for managing inserts, updates, and deletes. with Apache Spark version 3.3.0)

Data Lake 79

Data Lake Dashboards Metrics Metadata 79

AWS Big Data

MARCH 26, 2024

It is prudent to consolidate this data into a single customer view, serving as a primary reference for downstream applications, ranging from ecommerce platforms to CRM systems. This consolidated view acts as a liaison between the data platform and customer-centric applications.

Data Strategy 66

Data Strategy Strategy Data Warehouse Prescriptive Analytics 66

DataKitchen

OCTOBER 11, 2021

First, you must understand the existing challenges of the data team, including the data architecture and end-to-end toolchain. The biggest challenge is broken data pipelines due to highly manual processes. Figure 1 shows a manually executed data analytics pipeline.

Testing 157

Testing Metadata Dashboards Statistics 157

AWS Big Data

OCTOBER 25, 2023

Therefore, there is a need to being able to analyze and extract value from the data economically and flexibly. Solution overview Data and metadata discovery is one of the primary requirements in data analytics, where data consumers explore what data is available and in what format, and then consume or query it for analysis.

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Unstructured Data Metadata Management Analytics 115

Ontotext

FEBRUARY 26, 2024

Firstly, on the data maturity spectrum, the vast majority of organizations I’ve spoken with are stuck in the information stage. They have massive amounts of data they’re collecting and storing in their relational databases, document stores, data lakes, and data warehouses. RDF vs LPG?

Technology 52

Technology Cost-Benefit Data-driven Metadata 52

AWS Big Data

DECEMBER 18, 2023

Amazon Redshift powers data-driven decisions for tens of thousands of customers every day with a fully managed, AI-powered cloud data warehouse, delivering the best price-performance for your analytics workloads. What’s new with Amazon Redshift Want to learn more about the most recent features launched in Amazon Redshift?

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Data Warehouse Machine Learning Data-driven Data Lake 95

IBM Big Data Hub

AUGUST 4, 2023

In turn, they both must also have the data literacy skills to be able to verify the data’s accuracy, ensure its security, and provide or follow guidance on when and how it should be used. Data democratization uses a fit-for-purpose data architecture that is designed for the way today’s businesses operate, in real-time.

Data Architecture 64

Data Architecture Data Lake Machine Learning Data Governance 64