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

MARCH 25, 2024

Furthermore, data events are filtered, enriched, and transformed to a consumable format using a stream processor. The result is made available to the application by querying the latest snapshot. For more information, refer to Notions of Time: Event Time and Processing Time. For more information, refer to Dynamic Tables.

Data Lake 93

Data Lake Unstructured Data Management Modeling 93

AWS Big Data

JANUARY 8, 2024

For security, Kinesis Data Streams provide server-side encryption so you can meet strict data management requirements by encrypting your data at rest and Amazon Virtual Private Cloud (VPC) interface endpoints to keep traffic between your Amazon VPC and Kinesis Data Streams private.

Analytics 115

Analytics IoT Data-driven Snapshot 115

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. Moreover, the framework should consume compute resources as optimally as possible per the size of the operational tables.

Data Lake 94

Data Lake Data Processing Metadata Snapshot 94

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. This property is set to true by default. availability.

Data Lake 86

Data Lake Snapshot Metadata Optimization 86

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 116

Data Lake Metadata Optimization Statistics 116

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 75

Data Lake Snapshot Optimization Data Transformation 75

AWS Big Data

JULY 3, 2023

This helps traders determine the potential profitability of a strategy and identify any risks associated with it, enabling them to optimize it for better performance. Amazon Simple Storage Service (Amazon S3) is a popular cloud-based object storage service that can be used as the foundation for building a data lake.

Snapshot 86

Snapshot Data Lake Testing Strategy 86

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. This introduces the need for both polling and pushing the data to access and analyze in near-real time.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

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 82

Data Lake Data Analytics Analytics Data Processing 82

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 68

Data Architecture Metadata Data Lake Snapshot 68

AWS Big Data

JUNE 12, 2023

This schema serves as a single source of truth for producer and consumer and you can leverage the schema evolution feature of AWS Glue Schema Registry to keep it consistent as the data changes over time. Refer appendix section for more information on this feature. Refer to the first stack’s output.

Management 81

Management Metadata Testing Internet of Things 81

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. We use a sample JSON file as input to Amazon DynamoDB.

Data Lake 73

Data Lake Metadata Testing Snapshot 73

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. Versioning.

IT 346

IT Testing Experimentation Software 346

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 85

Data Lake Dashboards Metrics Metadata 85

Cloudera

MARCH 23, 2022

Being multi-function also means integrated end-to-end data pipelines that break siloes, piecing together analytics as a coherent life-cycle where business value can be extracted at each and every stage. Users should be able to choose their tool of choice and take advantage of its workload specific optimizations. 4: Enterprise grade.

Metadata 88

Metadata Data Architecture Machine Learning Cost-Benefit 88

AWS Big Data

MARCH 20, 2023

Top line revenue refers to the total value of sales of an organization’s services or products. The AWS Data Lab offers accelerated, joint engineering engagements between customers and AWS technical resources to create tangible deliverables that accelerate data and analytics modernization initiatives.

Analytics 52

Analytics Slice and Dice Data Processing Data Lake 52

AWS Big Data

MAY 19, 2023

Organizations across all industries have complex data processing requirements for their analytical use cases across different analytics systems, such as data lakes on AWS , data warehouses ( Amazon Redshift ), search ( Amazon OpenSearch Service ), NoSQL ( Amazon DynamoDB ), machine learning ( Amazon SageMaker ), and more.

Machine Learning 85

Machine Learning Metrics Management Big Data 85

AWS Big Data

NOVEMBER 29, 2023

We have seen a strong customer demand to expand its scope to cloud-based data lakes because data lakes are increasingly the enterprise solution for large-scale data initiatives due to their power and capabilities. The team uses dbt-glue to build a transformed gold model optimized for business intelligence (BI).

Data Lake 106

Data Lake Management Metrics Data Warehouse 106

AWS Big Data

JUNE 21, 2023

Built on highly curated structured data, it provides the flexibility and speed to run aggregations across an entire dataset to derive insights. To house our data, we need to define a data model. An optimal design choice is to use a dimensional model. This is achieved by partitioning the data.

Data Warehouse 82

Data Warehouse Data Lake OLAP Cost-Benefit 82

AWS Big Data

JULY 28, 2023

Amazon Redshift now makes it easier for you to run queries in AWS data lakes by automatically mounting the AWS Glue Data Catalog. You no longer have to create an external schema in Amazon Redshift to use the data lake tables cataloged in the Data Catalog.

Data Lake 68

Data Lake Data Governance Data Warehouse Modeling 68