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. Additionally, you’ll benefit from performance improvements through pushdown optimizations, further enhancing the efficiency of your operations.

Data Processing 95

Data Processing Data Lake Data Warehouse Optimization 95

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

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 88

Snapshot Data Lake Enterprise Data Governance 88

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.

Data Lake 92

Data Lake Unstructured Data Management Modeling 92

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 93

Data Lake Data Processing Metadata Snapshot 93

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

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

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

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 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 89

Data Lake Analytics Snapshot Optimization 89

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 95

Data Lake Snapshot Metadata Optimization 95

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.

Snapshot 92

Snapshot Metadata Cost-Benefit Data Warehouse 92

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 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

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

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.

Data Warehouse 83

Data Warehouse Snapshot Metadata Cost-Benefit 83

AWS Big Data

JUNE 10, 2024

Cloudinary is a cloud-based media management platform that provides a comprehensive set of tools and services for managing, optimizing, and delivering images, videos, and other media assets on websites and mobile applications. Cloudinary data retention for the specific analytical data discussed in this post was defined as 30 days.

Data Lake 94

Data Lake Metadata Snapshot Analytics 94

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 73

Data Lake Metadata Testing Snapshot 73

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 93

Metadata Data Architecture Machine Learning Cost-Benefit 93

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. A data fabric combined with a data lakehouse is the ideal foundation for most organizations.

Unstructured Data 76

Unstructured Data Data Architecture Data Lake Snapshot 76

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?

Insurance 150

Insurance Risk IoT Cost-Benefit 150

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 85

Data Lake Dashboards Metrics Metadata 85

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

AWS Big Data

JUNE 12, 2023

Organizations across the world are increasingly relying on streaming data, and there is a growing need for real-time data analytics, considering the growing velocity and volume of data being collected. Step 6} $ REGISTRY_NAME={VAL_OF_GlueSchemaRegistryName - Ref. Step 6} $ SCHEMA_NAME={VAL_OF_SchemaName– Ref.

Management 81

Management Metadata Testing Internet of Things 81

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 Big Data Management 85

AWS Big Data

NOVEMBER 29, 2023

It enables data engineers, data scientists, and analytics engineers to define the business logic with SQL select statements and eliminates the need to write boilerplate data manipulation language (DML) and data definition language (DDL) expressions.

Data Lake 105

Data Lake Management Metrics Data Warehouse 105

AWS Big Data

JUNE 21, 2023

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. Deriving business insights by identifying year-on-year sales growth is an example of an online analytical processing (OLAP) query. To house our data, we need to define a data model.

Data Warehouse 82

Data Warehouse Data Lake OLAP Cost-Benefit 82

IBM Big Data Hub

SEPTEMBER 25, 2023

But what most people don’t realize is that behind the scenes, Uber is not just a transportation service; it’s a data and analytics powerhouse. Every day, millions of riders use the Uber app, unwittingly contributing to a complex web of data-driven decisions. But the simplicity ends there. What is Presto?

OLAP 87

OLAP Data Lake Data-driven Snapshot 87

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