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 74

Data Lake Snapshot Optimization Data Transformation 74

AWS Big Data

MARCH 10, 2023

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.

Data Lake 103

Data Lake Sales Data Warehouse Snapshot 103

AWS Big Data

SEPTEMBER 13, 2023

The Analytics specialty practice of AWS Professional Services (AWS ProServe) helps customers across the globe with modern data architecture implementations on the AWS Cloud. Of those tables, some are larger (such as in terms of record volume) than others, and some are updated more frequently than others.

Data Lake 91

Data Lake Data Processing Metadata Snapshot 91

AWS Big Data

MARCH 4, 2024

As enterprises collect increasing amounts of data from various sources, the structure and organization of that data often need to change over time to meet evolving analytical needs. This is critical for fast-moving enterprises to augment data structures to support new use cases. This hampers agility and time to insight.

Snapshot 112

Snapshot Data Lake Metadata Recreation/Entertainment 112

AWS Big Data

MARCH 28, 2023

A slowly changing dimension (SCD) is a data warehousing concept that contains relatively static data that can change slowly over a period of time. There are three major types of SCDs maintained in data warehousing: Type 1 (no history), Type 2 (full history), and Type 3 (limited history).

Data Lake 71

Data Lake Testing Snapshot Sales 71

AWS Big Data

JANUARY 24, 2024

AWS-powered data lakes, supported by the unmatched availability of Amazon Simple Storage Service (Amazon S3), can handle the scale, agility, and flexibility required to combine different data and analytics approaches. It will pre-populate the properties as shown in the following screenshot.

Snapshot 101

Snapshot Data Lake Metadata Optimization 101

AWS Big Data

FEBRUARY 12, 2024

Objective Gupshup wanted to build a messaging analytics platform that provided: Build a platform to get detailed insights, data, and reports about WhatsApp/SMS campaigns and track the success of every text message sent by the end customers. Additionally, extract, load, and transform (ELT) data processing is sped up and made easier.

Data Warehouse 101

Data Warehouse Analytics Snapshot Cost-Benefit 101

AWS Big Data

NOVEMBER 22, 2023

Apache Hudi is an open table format that brings database and data warehouse capabilities to data lakes. Apache Hudi helps data engineers manage complex challenges, such as managing continuously evolving datasets with transactions while maintaining query performance.

Data Lake 93

Data Lake Snapshot Metadata Optimization 93

AWS Big Data

JUNE 27, 2024

With built-in features such as automated snapshots and cross-Region replication, you can enhance your disaster resilience with Amazon Redshift. Disaster recovery strategies Amazon Redshift is a cloud-based data warehouse that supports many recovery capabilities out of the box to address unforeseen outages and minimize downtime.

Snapshot 48

Snapshot Data Warehouse Data Processing Strategy 48

AWS Big Data

OCTOBER 3, 2023

In our previous post Improve operational efficiencies of Apache Iceberg tables built on Amazon S3 data lakes , we discussed how you can implement solutions to improve operational efficiencies of your Amazon Simple Storage Service (Amazon S3) data lake that is using the Apache Iceberg open table format and running on the Amazon EMR big data platform.

Optimization 110

Optimization Snapshot Data Lake Metadata 110

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. The response times for these data sources are critical to our key stakeholders.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

AWS Big Data

JANUARY 27, 2023

To build a data-driven business, it is important to democratize enterprise data assets in a data catalog. With a unified data catalog, you can quickly search datasets and figure out data schema, data format, and location. Verify all table metadata is stored in the AWS Glue Data Catalog.

Data Lake 62

Data Lake Metadata Business Analysis Data-driven 62

AWS Big Data

JANUARY 8, 2024

The volume of time-sensitive data produced is increasing rapidly, with different formats of data being introduced across new businesses and customer use cases. It aims to provide a framework to create low-latency streaming applications on the AWS Cloud using Amazon Kinesis Data Streams and AWS purpose-built data analytics services.

Analytics 113

Analytics IoT Data-driven Snapshot 113

AWS Big Data

JANUARY 17, 2024

With Amazon EMR 6.15, we launched AWS Lake Formation based fine-grained access controls (FGAC) on Open Table Formats (OTFs), including Apache Hudi, Apache Iceberg, and Delta lake. Many large enterprise companies seek to use their transactional data lake to gain insights and improve decision-making.

Data Lake 94

Data Lake Snapshot Big Data Data-driven 94

AWS Big Data

MAY 15, 2024

Athena is an interactive query service that simplifies data analysis in Amazon Simple Storage Service (Amazon S3) using standard SQL. By extracting detailed information from CloudTrail and querying it using Athena, this solution streamlines the process of data collection, analysis, and reporting of EIP usage within an AWS account.

Snapshot 89

Snapshot Optimization Data Lake Reporting 89

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 Filter by resource type , you can filter by Workgroup , Namespace , Snapshot , and Recovery Point. For more details on tagging, refer to Tagging resources overview.

Data Warehouse 86

Data Warehouse Management Snapshot Data Lake 86

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 84

Enterprise Data Warehouse Snapshot Cost-Benefit 84

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 103

Data Lake Management Metrics Data Warehouse 103

AWS Big Data

JANUARY 24, 2023

AWS Lake Formation helps with enterprise data governance and is important for a data mesh architecture. It works with the AWS Glue Data Catalog to enforce data access and governance. This solution only replicates metadata in the Data Catalog, not the actual underlying data. Migrate Amazon S3 data.

Data Architecture 67

Data Architecture Metadata Data Lake Snapshot 67

AWS Big Data

AUGUST 16, 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. AWS Glue crawlers will extract schema information and update the location of Iceberg metadata and schema updates in the Data Catalog.

Data Lake 79

Data Lake Metadata Snapshot Management 79

AWS Big Data

MARCH 25, 2024

This data usually comes from third parties, and developers need to find a way to ingest this data and process the data changes as they happen. However, the value of such important data diminishes significantly over time. The result is made available to the application by querying the latest snapshot.

Data Lake 90

Data Lake Unstructured Data Management Modeling 90

AWS Big Data

MAY 30, 2023

Customers have been using data warehousing solutions to perform their traditional analytics tasks. Traditional batch ingestion and processing pipelines that involve operations such as data cleaning and joining with reference data are straightforward to create and cost-efficient to maintain. options(**additional_options).mode("append").save(s3_output_folder)

Data Lake 81

Data Lake Data Analytics Analytics Data Processing 81

Cloudera

MARCH 5, 2024

AI, and any analytics for that matter, are only as good as the data upon which they are based. Struggling to access and collect, oftentimes disparate and siloed, data across environments that are required to power AI, many organizations are unable to achieve the business insight and value they had hoped for.

Snapshot 85

Snapshot Data Lake Enterprise Data Governance 85

AWS Big Data

NOVEMBER 10, 2023

Apache Spark is a widely-used open source distributed processing system renowned for handling large-scale data workloads. Amazon Redshift offers seamless integration with Apache Spark, allowing you to easily access your Redshift data on both Amazon Redshift provisioned clusters and Amazon Redshift Serverless. options(**read_config).option("query",

Data Processing 93

Data Processing Data Lake Data Warehouse Optimization 93

AWS Big Data

MARCH 20, 2023

In this post, we share how Poshmark improved CX and accelerated revenue growth by using a real-time analytics solution. High-level challenge: The need for real-time analytics Previous efforts at Poshmark for improving CX through analytics were based on batch processing of analytics data and using it on a daily basis to improve CX.

Analytics 52

Analytics Slice and Dice Data Processing Data Lake 52

AWS Big Data

AUGUST 16, 2023

Apache Iceberg is an open table format for very large analytic datasets. 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. We use a sample JSON file as input to Amazon DynamoDB.

Data Lake 72

Data Lake Metadata Testing Snapshot 72

AWS Big Data

MARCH 23, 2023

Large organizations often have lines of businesses (LoBs) that operate with autonomy in managing their business data. It makes sharing data across LoBs non-trivial. These organizations have adopted a federated model, with each LoB having the autonomy to make decisions on their data. Use time travel to find the table snapshot.

Interactive 69

Interactive Snapshot Data Lake Software 69

AWS Big Data

JUNE 21, 2023

This approach comes with a heavy computational cost in terms of processing and distributing the data across multiple tables while ensuring the system is ACID-compliant at all times, which can negatively impact performance and scalability. These types of queries are suited for a data warehouse. This is called index overloading.

Data Warehouse 80

Data Warehouse Data Lake OLAP Cost-Benefit 80

AWS Big Data

JULY 28, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. It is designed for analyzing large volumes of data and performing complex queries on structured and semi-structured data. It requires careful analysis to identify data dependencies and mitigate any potential risks or disruptions.

Snapshot 84

Snapshot Metadata Measurement Data Warehouse 84

AWS Big Data

AUGUST 2, 2023

In this blog, we will walk through how we can apply existing enterprise data to better understand and estimate Scope 1 carbon footprint using Amazon Simple Storage Service (S3) and Amazon Athena , a serverless interactive analytics service that makes it easy to analyze data using standard SQL.

Data Lake 72

Data Lake Measurement Visualization Data Architecture 72

AWS Big Data

JULY 28, 2023

Today, tens of thousands of customers run business-critical workloads on Amazon Redshift to cost-effectively and quickly analyze their data using standard SQL and existing business intelligence (BI) tools. Amazon Redshift now makes it easier for you to run queries in AWS data lakes by automatically mounting the AWS Glue Data Catalog.

Data Lake 67

Data Lake Data Governance Data Warehouse Modeling 67

AWS Big Data

MARCH 3, 2023

In this post, we share how the AWS Data Lab helped Tricentis to improve their software as a service (SaaS) Tricentis Analytics platform with insights powered by Amazon Redshift. Although Tricentis has amassed such data over a decade, the data remains untapped for valuable insights.

Software 52

Software Data Lake Testing Cost-Benefit 52

AWS Big Data

DECEMBER 13, 2023

Traditionally, customers used batch-based approaches for data movement from operational systems to analytical systems. A batch-based approach can introduce latency in data movement and reduce the value of data for analytics. usually a data warehouse) needs to reflect those changes in near real-time.

Data Warehouse 98

Data Warehouse Snapshot Data Processing Management 98

AWS Big Data

JULY 25, 2023

Amazon Redshift Serverless makes it simple to run and scale analytics in seconds. It automatically provisions and intelligently scales data warehouse compute capacity to deliver fast performance, and you pay only for what you use. The following screenshot shows the metrics available at the snapshot storage level.

Metrics 81

Metrics Data Warehouse Dashboards Snapshot 81

AWS Big Data

MARCH 18, 2024

It always pays to know more about your customers, and AWS Data Exchange makes it straightforward to use publicly available census data to enrich your customer dataset. The United States Census Bureau conducts the US census every 10 years and gathers household survey data. Workgroup – A collection of compute resources.

Data Warehouse 81

Data Warehouse Visualization Snapshot Data-driven 81

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.

Data Lake 84

Data Lake Dashboards Metrics Metadata 84

AWS Big Data

JULY 19, 2023

Amazon Redshift is a fully managed and petabyte-scale cloud data warehouse that is used by tens of thousands of customers to process exabytes of data every day to power their analytics workload. You can structure your data, measure business processes, and get valuable insights quickly can be done by using a dimensional model.

Modeling 69

Modeling Sales Data Warehouse Snapshot 69