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 130

Data Lake Metadata Statistics Optimization 130

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 122

Data Lake Sales Data Warehouse Snapshot 122

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. You still need to set appropriate EMRFS retries to provide additional resiliency.

Data Lake 98

Data Lake Snapshot Metadata Optimization 98

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. The company wanted the ability to continue processing operational data in the secondary Region in the rare event of primary Region failure.

Data Lake 111

Data Lake Data Processing Metadata Snapshot 111

AWS Big Data

JULY 29, 2024

In the era of big data, data lakes have emerged as a cornerstone for storing vast amounts of raw data in its native format. They support structured, semi-structured, and unstructured data, offering a flexible and scalable environment for data ingestion from multiple sources.

Metadata 126

Metadata Snapshot Data Lake Metrics 126

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.

Data Lake 98

Data Lake Analytics Snapshot Data Quality 98

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. Schema evolution enables adding, deleting, renaming, or modifying columns without needing to rewrite existing data.

Snapshot 132

Snapshot Data Lake Metadata Recreation/Entertainment 132

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 96

Data Lake Testing Snapshot Big Data 96

AWS Big Data

JULY 3, 2023

Backtesting is a process used in quantitative finance to evaluate trading strategies using historical data. 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.

Snapshot 105

Snapshot Data Lake Testing Strategy 105

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.

Snapshot 125

Snapshot Data Lake Metadata Optimization 125

Cloudera

FEBRUARY 14, 2024

Introduction Apache Iceberg has recently grown in popularity because it adds data warehouse-like capabilities to your data lake making it easier to analyze all your data — structured and unstructured. You can take advantage of a combination of the strategies provided and adapt them to your particular use cases.

Optimization 59

Optimization Strategy Snapshot Metadata 59

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. To develop your disaster recovery plan, you should complete the following tasks: Define your recovery objectives for downtime and data loss (RTO and RPO) for data and metadata.

Snapshot 91

Snapshot Data Warehouse Data Processing Strategy 91

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 115

Data Lake Snapshot Big Data Data-driven 115

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.

Snapshot 114

Snapshot Data Lake Optimization Reporting 114

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 88

Data Architecture Metadata Data Lake Snapshot 88

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. We’d love to hear your feedback!

Interactive 91

Interactive Snapshot Data Lake Software 91

AWS Big Data

JUNE 21, 2023

A typical ask for this data may be to identify sales trends as well as sales growth on a yearly, monthly, or even daily basis. A key pillar of AWS’s modern data strategy is the use of purpose-built data stores for specific use cases to achieve performance, cost, and scale. This is achieved by partitioning the data.

Data Warehouse 103

Data Warehouse Data Lake OLAP Cost-Benefit 103

AWS Big Data

JULY 28, 2023

To successfully respond to a data subject’s requests, organizations should have a clear strategy to determine how data is forgotten, flagged, anonymized, or deleted, and they should have clear guidelines in place for data audits. Note that putting a comprehensive data strategy in place is not in scope for this post.

Snapshot 98

Snapshot Metadata Measurement Data Warehouse 98

Corinium

APRIL 25, 2019

Most of my days focus on understanding what’s happening in the market, defining overall product strategy and direction, and translating into execution across the various teams. Then when there is a breach, it comes as a shock, “wow, I didn’t even know that application had access to so much sensitive data”. And then there is the Cloud.

Insurance 150

Insurance Risk IoT Data-driven 150

AWS Big Data

AUGUST 1, 2024

Effective planning, thorough risk assessment, and a well-designed migration strategy are crucial to mitigating these challenges and implementing a successful transition to the new data warehouse environment on Amazon Redshift. Organic strategy – This strategy uses a lift and shift data schema using migration tools.

Data Warehouse 113

Data Warehouse KPI Optimization Cost-Benefit 113

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

AUGUST 2, 2023

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. Customers have the flexibility to choose the services in each stage of the data pipeline based on their use case.

Data Lake 94

Data Lake Measurement Visualization Data Architecture 94

AWS Big Data

JANUARY 8, 2024

It can receive the events from an input Kinesis data stream and route the resulting stream to an output data stream. State snapshot in Amazon S3 – You can store the state snapshot in Amazon S3 for tracking. You can create a stateful functions cluster with Apache Flink based on your application business logic.

Analytics 133

Analytics IoT Data-driven Snapshot 133

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 98

Data Lake Dashboards Metrics Metadata 98

AWS Big Data

JULY 19, 2023

We show how to perform extract, transform, and load (ELT), an integration process focused on getting the raw data from a data lake into a staging layer to perform the modeling. He is passionate about using data to drive insights, while aligning with business requirements and objectives.

Modeling 91

Modeling Sales Data Warehouse Snapshot 91

AWS Big Data

MARCH 18, 2024

Namespaces group together all of the resources you use in Redshift Serverless, such as schemas, tables, users, datashares, and snapshots. First, we need to give our Redshift namespace permission via AWS Identity and Access Management (IAM) to access subscriptions on AWS Data Exchange. Workgroup – A collection of compute resources.

Data Warehouse 110

Data Warehouse Visualization Snapshot Data-driven 110

AWS Big Data

MARCH 3, 2023

From detailed design to a beta release, Tricentis had customers expecting to consume data from a data lake specific to only their data, and all of the data that had been generated for over a decade. Data export As stated earlier, some customers want to get an export of their test data and create their data lake.

Software 52

Software Data Lake Testing Dashboards 52

AWS Big Data

MARCH 20, 2023

The data from the Kinesis data stream is consumed by two applications: A Spark streaming application on Amazon EMR is used to write data from the Kinesis data stream to a data lake hosted on Amazon Simple Storage Service (Amazon S3) in a partitioned way.

Analytics 52

Analytics Slice and Dice Data Processing Data Lake 52

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 93

Data Lake Metadata Testing Snapshot 93

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 112

Machine Learning Metrics Big Data Management 112

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. Let’s say that this company is located in Europe and the data product must comply with the GDPR.

Data Lake 122

Data Lake Management Metrics Data Warehouse 122

IBM Big Data Hub

SEPTEMBER 25, 2023

Uber understood that digital superiority required the capture of all their transactional data, not just a sampling. They stood up a file-based data lake alongside their analytical database. Because much of the work done on their data lake is exploratory in nature, many users want to execute untested queries on petabytes of data.

OLAP 86

OLAP Data Lake Data-driven Online Analytical Processing 86

AWS Big Data

DECEMBER 20, 2024

After the tables are created, the second task transfers HDFS data to a landing bucket in Amazon S3 using AWS DataSync to sync customer data. This process brings data from all the different layers of the data lake. Its highly recommended to regularly expire snapshots that are no longer needed.

Metadata 119

Metadata Data-driven Snapshot Data Lake 119

AWS Big Data

FEBRUARY 18, 2025

To optimize their security operations, organizations are adopting modern approaches that combine real-time monitoring with scalable data analytics. They are using data lake architectures and Apache Iceberg to efficiently process large volumes of security data while minimizing operational overhead.

Snapshot 78

Snapshot Optimization Data Lake Metadata 78

AWS Big Data

NOVEMBER 6, 2024

Second, because traditional data warehousing approaches are unable to keep up with the volume, velocity, and variety of data, engineering teams are building data lakes and adopting open data formats such as Parquet and Apache Iceberg to store their data.

Metadata 115

Metadata Data Lake Management Internet of Things 115