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.

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Data Lake Snapshot Big Data Data-driven 90

AWS Big Data

JANUARY 8, 2024

This is the first post to a blog series that offers common architectural patterns in building real-time data streaming infrastructures using Kinesis Data Streams for a wide range of use cases. In this post, we will review the common architectural patterns of two use cases: Time Series Data Analysis and Event Driven Microservices.

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Analytics IoT Data-driven Snapshot 109

AWS Big Data

MAY 15, 2024

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. Additionally, you can analyze activity logs with AWS CloudTrail Lake and Amazon Athena.

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Snapshot Optimization Data Lake Reporting 52

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.

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Data Warehouse Management Snapshot Data Lake 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.

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Snapshot Data Lake Enterprise Data Governance 89

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

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Enterprise Data Warehouse Snapshot Cost-Benefit 81

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.

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Data Lake Metadata Snapshot Management 74

AWS Big Data

NOVEMBER 10, 2023

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. These tables are then joined with tables from the Enterprise Data Lake (EDL) at runtime. options(**read_config).option("query",

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Data Processing Data Lake Data Warehouse Optimization 89

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. OpenSearch Service provides support for native ingestion from Kinesis data streams or MSK topics.

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Data Lake Unstructured Data Management Modeling 87

AWS Big Data

MARCH 23, 2023

Register the S3 path storing the table using Lake Formation We register the S3 full path in Lake Formation: Navigate to the Lake Formation console. In the navigation pane, under Register and ingest , choose Data lake locations. The Iceberg table keeps track of the snapshots.

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Interactive Snapshot Data Lake Software 66

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.

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Data Lake Data Processing Metadata Snapshot 88

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.

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Data Warehouse Snapshot Data Processing Management 95

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.

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Data Lake Testing Snapshot Sales 68

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. parquet") df.sortWithinPartitions("review_date").writeTo("dev.db.amazon_reviews_iceberg").append()

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Data Lake Snapshot Metadata Optimization 80

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 70

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 110

AWS Big Data

JULY 20, 2023

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. In this post, we describe Orca’s journey building a transactional data lake using Amazon Simple Storage Service (Amazon S3), Apache Iceberg, and AWS Analytics.

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Data Lake Analytics Snapshot Optimization 83

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.

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Data Lake Snapshot Metadata Optimization 89

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.

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Data Warehouse Analytics Snapshot Cost-Benefit 97

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. You can use it for analytics, ML, and application development. Then we chose Amazon Athena as our query service.

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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. 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)

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Data Lake Data Analytics Analytics Data Processing 76

Cloudera

FEBRUARY 8, 2024

Apache Iceberg is a high-performance open table format for petabyte-scale analytic datasets. It brings the reliability and simplicity of SQL tables to big data while enabling engines like Hive, Impala, Spark, Trino, Flink, and Presto to work with the same tables at the same time. In such situations, Hive falls back to the full rebuild.

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Snapshot Metadata Cost-Benefit Data Warehouse 92

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.

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Data Architecture Metadata Data Lake Snapshot 64

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.

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Analytics Slice and Dice Data Processing Data Lake 52

Cloudera

APRIL 3, 2023

Cloudera Contributors: Ayush Saxena, Tamas Mate, Simhadri Govindappa Since we announced the general availability of Apache Iceberg in Cloudera Data Platform (CDP), we are excited to see customers testing their analytic workloads on Iceberg. We will publish follow up blogs for other data services. ID, TBL_ICEBERG_PART_2.NAME,

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Data Warehouse Snapshot Metadata Cost-Benefit 83

AWS Big Data

JULY 28, 2023

It is designed for analyzing large volumes of data and performing complex queries on structured and semi-structured data. Many customers are looking for best practices to keep their Amazon Redshift analytics environment compliant and have an ability to respond to GDPR right to forgotten requests.

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Snapshot Metadata Measurement Data Warehouse 79

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.

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Data Lake Measurement Visualization Data Architecture 68

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.

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Metrics Data Warehouse Dashboards Snapshot 76

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 68

Data Lake Metadata Testing Snapshot 68

Cloudera

DECEMBER 15, 2022

Since we announced the general availability of Apache Iceberg in Cloudera Data Platform (CDP), Cloudera customers, such as Teranet , have built open lakehouses to future-proof their data platforms for all their analytical workloads. Enhanced multi-function analytics. Accelerate analytics with materialized view support.

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Metadata Data Warehouse Snapshot Data Quality 80

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.

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Modeling Sales Data Warehouse Snapshot 66

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. Workgroup – A collection of compute resources.

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Data Warehouse Visualization Snapshot Data-driven 79

Cloudera

SEPTEMBER 12, 2022

Once you have the access to all the data you need at the right time, the next step is to be able to use the data efficiently, opening the door for new analytic use cases. This is where the data lakehouse comes in. These answers must be reliable and delivered quickly. Better together.

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Unstructured Data Data Architecture Data Lake Snapshot 75

Corinium

APRIL 25, 2019

Ahead of the Chief Data Analytics Officers & Influencers, Insurance event we caught up with Dominic Sartorio, Senior Vice President for Products & Development, Protegrity to discuss how the industry is evolving. Why should Chief Data & Analytics Officers care about data security?

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Insurance Risk IoT Cost-Benefit 150

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. While aggregating, summarizing, and aligning to a common information model, all transformations must not affect the integrity of data from its source.

Software 52

Software Data Lake Testing Cost-Benefit 52

Cloudera

MARCH 23, 2022

Let’s highlight some of those benefits, and why choosing CDP and Iceberg can future proof your next generation data architecture. . Figure 1: Apache Iceberg fits the next generation data architecture by abstracting storage layer from analytics layer while introducing net new capabilities like time-travel and partition evolution. #1:

Metadata 92

Metadata Data Architecture Machine Learning Cost-Benefit 92

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.

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Data Lake Dashboards Metrics Metadata 79