AWS Big Data

OCTOBER 9, 2023

Data lakes have been gaining popularity for storing vast amounts of data from diverse sources in a scalable and cost-effective way. As the number of data consumers grows, data lake administrators often need to implement fine-grained access controls for different user profiles.

Data Lake 129

Data Lake Testing Big Data Management 129

AWS Big Data

JULY 18, 2024

Over the years, organizations have invested in creating purpose-built, cloud-based data lakes that are siloed from one another. A major challenge is enabling cross-organization discovery and access to data across these multiple data lakes, each built on different technology stacks.

Data Lake 122

Data Lake Publishing Metadata Data-driven 122

AWS Big Data

JULY 31, 2024

In the current industry landscape, data lakes have become a cornerstone of modern data architecture, serving as repositories for vast amounts of structured and unstructured data. Maintaining data consistency and integrity across distributed data lakes is crucial for decision-making and analytics.

Data Lake 112

Data Lake Marketing Data Processing Management 112

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 108

Data Lake Data Warehouse Metadata Data Architecture 108

AWS Big Data

JUNE 10, 2024

In this blog post, we dive into different data aspects and how Cloudinary breaks the two concerns of vendor locking and cost efficient data analytics by using Apache Iceberg, Amazon Simple Storage Service (Amazon S3 ), Amazon Athena , Amazon EMR , and AWS Glue. 5 seconds $0.08 8 seconds $0.07 8 seconds $0.02 107 seconds $0.25

Data Lake 122

Data Lake Metadata Snapshot Analytics 122

DataKitchen

DECEMBER 9, 2022

Observability in DataOps refers to the ability to monitor and understand the performance and behavior of data-related systems and processes, and to use that information to improve the quality and speed of data-driven decision making. Query> An AI, Chat GPT wrote this blog post, why should I read it? .

Machine Learning 130

Machine Learning Data-driven Optimization Data Analytics 130

AWS Big Data

OCTOBER 30, 2024

Amazon DataZone now launched authentication supports through the Amazon Athena JDBC driver, allowing data users to seamlessly query their subscribed data lake assets via popular business intelligence (BI) and analytics tools like Tableau, Power BI, Excel, SQL Workbench, DBeaver, and more.

Visualization 116

Visualization Data Lake Testing Data Governance 116

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 104

Data Lake Data Processing Metadata Snapshot 104

AWS Big Data

OCTOBER 29, 2024

This led to inefficiencies in data governance and access control. AWS Lake Formation is a service that streamlines and centralizes the data lake creation and management process. The Solution: How BMW CDH solved data duplication The CDH is a company-wide data lake built on Amazon Simple Storage Service (Amazon S3).

Data Lake 89

Data Lake Sales Metadata Machine Learning 89

AWS Big Data

DECEMBER 4, 2024

With this new functionality, customers can create up-to-date replicas of their data from applications such as Salesforce, ServiceNow, and Zendesk in an Amazon SageMaker Lakehouse and Amazon Redshift. SageMaker Lakehouse gives you the flexibility to access and query your data in-place with all Apache Iceberg compatible tools and engines.

Data Integration 98

Data Integration Data Lake Statistics Data-driven 98

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. Note the configuration parameters s3.write.tags.write-tag-name write.tags.write-tag-name and s3.delete.tags.delete-tag-name

Data Lake 92

Data Lake Snapshot Metadata Optimization 92

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 94

Data Lake Analytics Snapshot Data Quality 94

AWS Big Data

DECEMBER 4, 2024

Amazon SageMaker Lakehouse , now generally available, unifies all your data across Amazon Simple Storage Service (Amazon S3) data lakes and Amazon Redshift data warehouses, helping you build powerful analytics and AI/ML applications on a single copy of data. The tools to transform your business are here.

Data Analytics 86

Data Analytics Analytics Data Lake Data Quality 86

DataKitchen

NOVEMBER 4, 2021

Cloud computing has made it much easier to integrate data sets, but that’s only the beginning. Creating a data lake has become much easier, but that’s only ten percent of the job of delivering analytics to users. It often takes months to progress from a data lake to the final delivery of insights.

Data Processing 246

Data Processing Data Lake Cost-Benefit Testing 246

AWS Big Data

OCTOBER 30, 2024

With this integration, you can now seamlessly query your governed data lake assets in Amazon DataZone using popular business intelligence (BI) and analytics tools, including partner solutions like Tableau. Refer to the detailed blog post on how you can use this to connect through various other tools.

Analytics 104

Analytics Visualization Data Governance Data-driven 104

DataKitchen

AUGUST 3, 2021

First-generation – expensive, proprietary enterprise data warehouse and business intelligence platforms maintained by a specialized team drowning in technical debt. Second-generation – gigantic, complex data lake maintained by a specialized team drowning in technical debt. The post What is a Data Mesh?

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

AWS Big Data

JULY 21, 2023

Data-driven organizations treat data as an asset and use it across different lines of business (LOBs) to drive timely insights and better business decisions. This leads to having data across many instances of data warehouses and data lakes using a modern data architecture in separate AWS accounts.

Data Lake 93

Data Lake Data Warehouse Marketing Management 93

AWS Big Data

AUGUST 1, 2023

Although Jira Cloud provides reporting capability, loading this data into a data lake will facilitate enrichment with other business data, as well as support the use of business intelligence (BI) tools and artificial intelligence (AI) and machine learning (ML) applications. For InitialRunFlag , choose Setup.

Data Lake 92

Data Lake Data Transformation Data-driven Cost-Benefit 92

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 81

Data Lake Testing Snapshot Sales 81

DataKitchen

DECEMBER 7, 2021

This book is not available until January 2022, but considering all the hype around the data mesh, we expect it to be a best seller. In the book, author Zhamak Dehghani reveals that, despite the time, money, and effort poured into them, data warehouses and data lakes fail when applied at the scale and speed of today’s organizations.

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Data-driven Data Governance Big Data Data Science 246

AWS Big Data

APRIL 24, 2023

Building a data lake on Amazon Simple Storage Service (Amazon S3) provides numerous benefits for an organization. However, many use cases, like performing change data capture (CDC) from an upstream relational database to an Amazon S3-based data lake, require handling data at a record level.

Data Lake 88

Data Lake Data Governance Machine Learning Cost-Benefit 88

DataKitchen

AUGUST 19, 2021

Figure 3 shows an example processing architecture with data flowing in from internal and external sources. Each data source is updated on its own schedule, for example, daily, weekly or monthly. The data scientists and analysts have what they need to build analytics for the user. The new Recipes run, and BOOM! Conclusion.

Data Warehouse 246

Data Warehouse Data Lake Manufacturing Testing 246

AWS Big Data

JUNE 15, 2023

In today’s world, customers manage vast amounts of data in their Amazon Simple Storage Service (Amazon S3) data lakes, which requires convoluted data pipelines to continuously understand the changes in the data layout and make them available to consuming systems. Review and update the crawler settings.

Data Lake 98

Data Lake Metadata Cost-Benefit Management 98

AWS Big Data

JUNE 23, 2023

This blog post is co-written with Ori Nakar from Imperva. Events and many other security data types are stored in Imperva’s Threat Research Multi-Region data lake. Imperva harnesses data to improve their business outcomes. Imperva’s data lake has a few dozen different datasets, in the scale of petabytes.

Data Lake 76

Data Lake Dashboards Cost-Benefit Data Warehouse 76

DataKitchen

NOVEMBER 29, 2021

The rise of distributed data architectures like Data Mesh will combine with DataOps automation to give rise to Hub-Spoke architectures that deftly blend the benefits of centralization and decentralization. For example, a Hub-Spoke architecture could integrate data from a multitude of sources into a data lake.

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Testing Data Lake Data Architecture Manufacturing 245

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. For more information, see Changing the default settings for your data lake.

Data Lake 88

Data Lake Visualization Dashboards Insurance 88

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 119

Metadata Snapshot Data Lake Metrics 119

DataKitchen

AUGUST 9, 2021

Instead of having a giant, unwieldy data lake , the data mesh breaks up the data and workflow assets into controllable and composable domains with inherent interdependencies. Domains are built from raw data and/or the output of other domains.

Testing 246

Testing Data Lake Metadata Publishing 246

TDAN

JUNE 5, 2024

In the ever-evolving landscape of data management, two key concepts have emerged as essential components for organizations seeking to harness the power of their data: data marts and data lakes. Understanding the distinctions […]

Data Lake 52

Data Lake Management Data Architecture Big Data 52

AWS Big Data

MAY 29, 2024

Grant access to User1 in Lake Formation Sign in to the Lake Formation console, choose Data lake permissions in the navigation pane, and grant access to the user group on the database oktank_tipblog_temp and table customer. csv("s3://tip-blog-s3-s3ag/input/*").show() csv("s3://tip-blog-s3-s3ag/input/*").write.mode("overwrite").parquet("s3://tip-blog-s3-s3ag/input/")

Data Lake 94

Data Lake Enterprise Management Business Intelligence 94

AWS Big Data

APRIL 18, 2024

This is a guest blog post co-authored with Atul Khare and Bhupender Panwar from Salesforce. The Normalized Parquet Logs are stored in an Amazon Simple Storage Service (Amazon S3) data lake and cataloged into Hive Metastore (HMS) on an Amazon Relational Database Service (Amazon RDS) instance based on S3 event notifications.

Optimization 101

Optimization Data Lake Management Key Performance Indicator 101

AWS Big Data

OCTOBER 30, 2024

However, you can use the same file name as long as it’s from different auto-copy jobs: job_customerA_sales – s3://redshift-blogs/sales/customerA/2022-10-15-sales.csv job_customerB_sales – s3://redshift-blogs/sales/customerB/2022-10-15-sales.csv Do not update file contents. Do not overwrite existing files.

Data Warehouse 89

Data Warehouse Sales Data Lake Recreation/Entertainment 89

DataKitchen

AUGUST 27, 2021

DataOps automation replaces the non-value-add work performed by the data team and the outside dollars spent on consultants with an automated framework that executes efficiently and at a high level of quality. Focusing on the processes that operate on data enables the team to automate workflows and build a factory that produces insights.

Analytics 246

Analytics Sales Testing Cost-Benefit 246

AWS Big Data

DECEMBER 4, 2024

Open table formats are emerging in the rapidly evolving domain of big data management, fundamentally altering the landscape of data storage and analysis. By providing a standardized framework for data representation, open table formats break down data silos, enhance data quality, and accelerate analytics at scale.

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Snapshot Metadata Data Lake Optimization 84

Cloudera

OCTOBER 23, 2024

One of the most important innovations in data management is open table formats, specifically Apache Iceberg , which fundamentally transforms the way data teams manage operational metadata in the data lake. Try Cloudera’s open data lakehouse on AWS for 5 days for free here , or try Snowflake for free for 30 days here.

Metadata 84

Metadata Data Lake Dashboards Interactive 84

AWS Big Data

OCTOBER 14, 2024

Enterprise data is brought into data lakes and data warehouses to carry out analytical, reporting, and data science use cases using AWS analytical services like Amazon Athena , Amazon Redshift , Amazon EMR , and so on. Run the following Shell script commands in the console to copy the Jupyter Notebooks.

Metadata 89

Metadata Data Lake Modeling Data Warehouse 89

Data Virtualization

AUGUST 19, 2021

“Data mesh” is a new data analytics paradigm proposed by Zhamak Dehghani, one that is designed to move organizations from monolithic architectures such as the data warehouse and the data lake to more decentralized architectures. As long-time supporters of logical.

Data Lake 98

Data Lake Data Warehouse Data Analytics Analytics 98