AWS Big Data

OCTOBER 19, 2023

Data lakes and data warehouses are two of the most important data storage and management technologies in a modern data architecture. Data lakes store all of an organization’s data, regardless of its format or structure.

Data Lake 118

Data Lake Data Warehouse Visualization Snapshot 118

AWS Big Data

AUGUST 31, 2023

Amazon Redshift enables you to directly access data stored in Amazon Simple Storage Service (Amazon S3) using SQL queries and join data across your data warehouse and data lake. With Amazon Redshift, you can query the data in your S3 data lake using a central AWS Glue metastore from your Redshift data warehouse.

Data Lake 104

Data Lake Data Warehouse Metadata Data Architecture 104

AWS Big Data

JUNE 10, 2024

Apache Iceberg brings the reliability and simplicity of SQL tables to big data, while making it possible for processing engines such as Apache Spark, Trino, Apache Flink, Presto, Apache Hive, and Impala to safely work with the same tables at the same time. The following table shows the cost and time for each query and product.

Data Lake 119

Data Lake Metadata Snapshot Analytics 119

AWS Big Data

JUNE 10, 2024

In this post, we delve into the key aspects of using Amazon EMR for modern data management, covering topics such as data governance, data mesh deployment, and streamlined data discovery. Organizations have multiple Hive data warehouses across EMR clusters, where the metadata gets generated.

Data Lake 93

Data Lake Metadata Data Warehouse Data Processing 93

Data Virtualization

NOVEMBER 3, 2022

Reading Time: 4 minutes The amount of expanding volume and variety of data originating from various sources are a massive challenge for businesses. In attempts to overcome their big data challenges, organizations are exploring data lakes as repositories where huge volumes and varieties of.

Data Lake 52

Data Lake Big Data Data Integration Management 52

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 91

Data Lake Analytics Snapshot Data Quality 91

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 116

Metadata Snapshot Data Lake Metrics 116

AWS Big Data

AUGUST 3, 2023

Data analytics on operational data at near-real time is becoming a common need. Due to the exponential growth of data volume, it has become common practice to replace read replicas with data lakes to have better scalability and performance. Apache Hudi connector for AWS Glue For this post, we use AWS Glue 4.0,

Data Lake 84

Data Lake Visualization Dashboards Insurance 84

Data Virtualization

OCTOBER 5, 2022

For this reason, organizations must periodically revisit their data architectures, to ensure that they are aligned with current business goals.

Data Lake 52

Data Lake Data Architecture Data Integration Management 52

AWS Big Data

FEBRUARY 22, 2023

In this post, we show how Ruparupa implemented an incrementally updated data lake to get insights into their business using Amazon Simple Storage Service (Amazon S3), AWS Glue , Apache Hudi , and Amazon QuickSight. An AWS Glue ETL job, using the Apache Hudi connector, updates the S3 data lake hourly with incremental data.

Data Lake 52

Data Lake Dashboards Cost-Benefit Data Warehouse 52

David Menninger's Analyst Perspectives

NOVEMBER 16, 2021

Talend is a data integration and management software company that offers applications for cloud computing, big data integration, application integration, data quality and master data management.

Management 324

Management Data Warehouse Data Quality Data Integration 324

IBM Big Data Hub

JUNE 26, 2020

Like oil, data is valuable but it must be refined in order to provide value. Organizations need to collect, organize, and analyze their data across multi-cloud, hybrid cloud, and data lakes. Yet traditional ETL tools support only a limited number of delivery styles and involve a significant amount of hand-coding.

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Data Integration Data Lake Machine Learning Enterprise 107

AWS Big Data

JANUARY 26, 2023

AWS Glue is a serverless, scalable data integration service that makes it easier to discover, prepare, move, and integrate data from multiple sources. AWS Glue provides an extensible architecture that enables users with different data processing use cases.

Data Lake 117

Data Lake Big Data Software Interactive 117

AWS Big Data

OCTOBER 20, 2023

Today, we are pleased to announce new AWS Glue connectors for Azure Blob Storage and Azure Data Lake Storage that allow you to move data bi-directionally between Azure Blob Storage, Azure Data Lake Storage, and Amazon Simple Storage Service (Amazon S3). option("header","true").load("wasbs://yourblob@youraccountname.blob.core.windows.net/loadingtest-input/100mb")

Data Lake 94

Data Lake Big Data Consulting Data Warehouse 94

AWS Big Data

DECEMBER 15, 2023

Even after identification, it’s cumbersome to implement redaction, masking, or encryption of sensitive data at scale. In this post, we provide an automated solution to detect PII data in Amazon Redshift using AWS Glue. For our solution, we use Amazon Redshift to store the data.

Data Lake 113

Data Lake Data Warehouse Big Data Structured Data 113

AWS Big Data

AUGUST 22, 2024

The infrastructure provides an analytics experience to hundreds of in-house analysts, data scientists, and student-facing frontend specialists. The data engineering team is on a mission to modernize its data integration platform to be agile, adaptive, and straightforward to use.

Data Warehouse 107

Data Warehouse Data Lake Data Integration Management 107

AWS Big Data

AUGUST 19, 2024

As organizations increasingly rely on data stored across various platforms, such as Snowflake , Amazon Simple Storage Service (Amazon S3), and various software as a service (SaaS) applications, the challenge of bringing these disparate data sources together has never been more pressing. For more information on AWS Glue, visit AWS Glue.

Analytics 104

Analytics Data-driven Data Integration Data Lake 104

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. Under Administration , choose Data catalog settings.

Data Lake 103

Data Lake Snapshot Metadata Optimization 103

AWS Big Data

JUNE 25, 2024

This post is co-authored by Vijay Gopalakrishnan, Director of Product, Salesforce Data Cloud. In today’s data-driven business landscape, organizations collect a wealth of data across various touch points and unify it in a central data warehouse or a data lake to deliver business insights.

Data Lake 108

Data Lake Cost-Benefit Data-driven Data Warehouse 108

AWS Big Data

MARCH 20, 2023

In the first post of this series , we described how AWS Glue for Apache Spark works with Apache Hudi, Linux Foundation Delta Lake, and Apache Iceberg datasets tables using the native support of those data lake formats. Even without prior experience using Hudi, Delta Lake or Iceberg, you can easily achieve typical use cases.

Visualization 84

Visualization Data Lake Snapshot Big Data 84

In(tegrate) the Clouds

JUNE 23, 2016

This week SnapLogic posted a presentation of the 10 Modern Data Integration Platform Requirements on the company’s blog. They are: Application integration is done primarily through REST & SOAP services. Large-volume data integration is available to Hadoop-based data lakes or cloud-based data warehouses.

Data Integration 49

Data Integration Data Lake Data Warehouse Data-driven 49

AWS Big Data

FEBRUARY 13, 2024

Monitoring data pipelines in real time is critical for catching issues early and minimizing disruptions. AWS Glue has made this more straightforward with the launch of AWS Glue job observability metrics , which provide valuable insights into your data integration pipelines built on AWS Glue.

Metrics 108

Metrics Dashboards Visualization Key Performance Indicator 108

AWS Big Data

JANUARY 12, 2024

Ingestion: Data lake batch, micro-batch, and streaming Many organizations land their source data into their data lake in various ways, including batch, micro-batch, and streaming jobs. Amazon AppFlow can be used to transfer data from different SaaS applications to a data lake.

Data Lake 105

Data Lake Cost-Benefit Visualization Structured Data 105

AWS Big Data

MAY 3, 2023

In today’s data-driven business environment, organizations face the challenge of efficiently preparing and transforming large amounts of data for analytics and data science purposes. Businesses need to build data warehouses and data lakes based on operational data.

Data Lake 89

Data Lake Data Warehouse Data-driven Optimization 89

AWS Big Data

AUGUST 13, 2024

In today’s data-driven world, seamless integration and transformation of data across diverse sources into actionable insights is paramount. With AWS Glue, you can discover and connect to hundreds of diverse data sources and manage your data in a centralized data catalog. Kamen Sharlandjiev is a Sr.

Data Processing 95

Data Processing Visualization Data Lake Data Processing 95

Smart Data Collective

OCTOBER 17, 2022

Big data is shaping our world in countless ways. Data powers everything we do. Exactly why, the systems have to ensure adequate, accurate and most importantly, consistent data flow between different systems. A point of data entry in a given pipeline. Data Pipeline: Use Cases. Destination.

Data Warehouse 130

Data Warehouse Data Lake Visualization Big Data 130

AWS Big Data

FEBRUARY 7, 2023

This post focuses on such schema changes in file-based tables and shows how to automatically replicate the schema evolution of structured data from table formats in databases to the tables stored as files in cost-effective way. Apache Hudi supports ACID transactions and CRUD operations on a data lake. and save it.

Data Lake 77

Data Lake Testing Big Data Structured Data 77

AWS Big Data

NOVEMBER 13, 2023

Amazon Redshift is a fully managed data warehousing service that offers both provisioned and serverless options, making it more efficient to run and scale analytics without having to manage your data warehouse. Additionally, data is extracted from vendor APIs that includes data related to product, marketing, and customer experience.

Data Warehouse 101

Data Warehouse Analytics Data Lake Data Science 101

Jet Global

MAY 27, 2022

Synapse services are powerful tools for bringing data together for analytics, machine learning, reporting needs, and more. How Synapse works with Data Lakes and Warehouses. Synapse services, data lakes, and data warehouses are often discussed together. Streamline Data with Atlas.

Data Lake 52

Data Lake IT Recreation/Entertainment Data Warehouse 52

Juice Analytics

MAY 11, 2020

Among all the hot analytics initiatives to choose from (big data, IoT, NLP, data storytelling, cognitive BI, GDPR), plain old reporting is what is considered the most important strategic initiative. But seriously, reporting?

Reporting 134

Reporting Analytics IT Data Lake 134

AWS Big Data

NOVEMBER 20, 2023

For any modern data-driven company, having smooth data integration pipelines is crucial. These pipelines pull data from various sources, transform it, and load it into destination systems for analytics and reporting. About the Authors Noritaka Sekiyama is a Principal Big Data Architect on the AWS Glue team.

Metrics 105

Metrics Data Lake Cost-Benefit Dashboards 105

AWS Big Data

NOVEMBER 29, 2023

Zero-ETL integration also enables you to load and analyze data from multiple operational database clusters in a new or existing Amazon Redshift instance to derive holistic insights across many applications. Learn more about the zero-ETL integrations, data lake performance enhancements, and other announcements below.

Data Warehouse 109

Data Warehouse Data Lake Analytics Machine Learning 109

AWS Big Data

DECEMBER 13, 2023

In addition to using native managed AWS services that BMS didn’t need to worry about upgrading, BMS was looking to offer an ETL service to non-technical business users that could visually compose data transformation workflows and seamlessly run them on the AWS Glue Apache Spark-based serverless data integration engine.

Metadata 98

Metadata Data Lake Visualization Data Transformation 98

AWS Big Data

MARCH 3, 2023

Additionally, the scale is significant because the multi-tenant data sources provide a continuous stream of testing activity, and our users require quick data refreshes as well as historical context for up to a decade due to compliance and regulatory demands. Finally, data integrity is of paramount importance.

Software 52

Software Data Lake Testing Cost-Benefit 52

DataKitchen

JULY 27, 2023

Let’s go through the ten Azure data pipeline tools Azure Data Factory : This cloud-based data integration service allows you to create data-driven workflows for orchestrating and automating data movement and transformation. You can use it for big data analytics and machine learning workloads.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

AWS Big Data

OCTOBER 27, 2023

Data integration is the foundation of robust data analytics. It encompasses the discovery, preparation, and composition of data from diverse sources. In the modern data landscape, accessing, integrating, and transforming data from diverse sources is a vital process for data-driven decision-making.

Analytics 107

Analytics Visualization Data Integration Cost-Benefit 107

AWS Big Data

NOVEMBER 10, 2023

The data sourcing problem To ensure the reliability of PySpark data pipelines, it’s essential to have consistent record-level data from both dimensional and fact tables stored in the Enterprise Data Warehouse (EDW). These tables are then joined with tables from the Enterprise Data Lake (EDL) at runtime.

Data Processing 102

Data Processing Data Lake Data Warehouse Optimization 102