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. Overall, DataOps observability is an essential component of modern data-driven organizations.

Machine Learning 130

Machine Learning Data-driven Optimization Data Analytics 130

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 114

Data Integration Data Lake Statistics Data-driven 114

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. Use case Amazon DataZone addresses your data sharing challenges and optimizes data availability.

Analytics 119

Analytics Visualization Data Governance Data-driven 119

AWS Big Data

OCTOBER 3, 2023

In our previous post Improve operational efficiencies of Apache Iceberg tables built on Amazon S3 data lakes , we discussed how you can implement solutions to improve operational efficiencies of your Amazon Simple Storage Service (Amazon S3) data lake that is using the Apache Iceberg open table format and running on the Amazon EMR big data platform.

Optimization 126

Optimization Snapshot Data Lake Metadata 126

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 116

Data Lake Marketing Data Processing Management 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 98

Data Lake Snapshot Metadata Optimization 98

AWS Big Data

APRIL 18, 2024

This is a guest blog post co-authored with Atul Khare and Bhupender Panwar from Salesforce. In this post, we discuss how the Salesforce TIP team optimized their architecture using Amazon Web Services (AWS) managed services to achieve better scalability, cost, and operational efficiency. Headquartered in San Francisco, Salesforce, Inc.

Optimization 111

Optimization Data Lake Management Key Performance Indicator 111

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

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. Moreover, the framework should consume compute resources as optimally as possible per the size of the operational tables.

Data Lake 111

Data Lake Data Processing Metadata Snapshot 111

Sisense

DECEMBER 23, 2019

Artificial Intelligence and machine learning are the future of every industry, especially data and analytics. AI and ML are the only ways to derive value from massive data lakes, cloud-native data warehouses, and other huge stores of information. Use AI to tackle huge datasets.

Data Lake 86

Data Lake Machine Learning Data Warehouse Digital Transformation 86

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.

Snapshot 84

Snapshot Metadata Data Lake Optimization 84

DataKitchen

NOVEMBER 4, 2021

It expands beyond tools and data architecture and views the data organization from the perspective of its processes and workflows. The DataKitchen Platform is a “ process hub” that masters and optimizes those processes. Cloud computing has made it much easier to integrate data sets, but that’s only the beginning.

Data Processing 246

Data Processing Data Lake Cost-Benefit Testing 246

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 98

Data Lake Data Transformation Data-driven Cost-Benefit 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 95

Data Lake Dashboards Cost-Benefit Data Warehouse 95

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

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

CDW Research Hub

JULY 18, 2022

One modern data platform solution that provides simplicity and flexibility to grow is Snowflake’s data cloud and platform. These Snowflake accelerators reduce the time to analytics for your users at all levels so you can make data-driven decisions faster. Security Data Lake. Optimizing Snowflake functionality.

Optimization 87

Optimization Data Lake Data Warehouse Manufacturing 87

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. You can add more such query optimization rules to the instructions.

Metadata 105

Metadata Data Lake Modeling Data Warehouse 105

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 105

Data Lake Metadata Cost-Benefit Management 105

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 98

Data Lake Data Governance Machine Learning Cost-Benefit 98

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 110

Data Warehouse Sales Data Lake Recreation/Entertainment 110

AWS Big Data

NOVEMBER 22, 2024

Important considerations for preview As you begin using automated Spark upgrades during the preview period, there are several important aspects to consider for optimal usage of the service: Service scope and limitations – The preview release focuses on PySpark code upgrades from AWS Glue versions 2.0 option("recursiveFileLookup", "true").option("path",

Cost-Benefit 105

Cost-Benefit Data-driven Software Testing 105

IBM Big Data Hub

JULY 5, 2023

Data Lakes have been around for well over a decade now, supporting the analytic operations of some of the largest world corporations. Such data volumes are not easy to move, migrate or modernize. The challenges of a monolithic data lake architecture Data lakes are, at a high level, single repositories of data at scale.

Data Lake 60

Data Lake Metadata Cost-Benefit Data Warehouse 60

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. For CoW tables, queries see the latest data committed.

Data Lake 116

Data Lake Snapshot Metadata Optimization 116

Sisense

APRIL 9, 2021

The amount of data being generated and stored every day has exploded. Companies of all kinds are sitting on stockpiles of data that could someday prove valuable. Until then though, they don’t necessarily want to spend the time and resources necessary to create a schema to house this data in a traditional data warehouse.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Structured Data 52

Data Virtualization

NOVEMBER 25, 2021

The market for data lakes has recently seen an impressive wave of new-generation engines that provide highly efficient processing of very large data volumes stored in distributed file systems, like S3, ADLS and others. With low cost of storage in.

Data Lake 52

Data Lake Strategy Marketing Optimization 52

Data Virtualization

NOVEMBER 25, 2021

The market for data lakes has recently seen an impressive wave of new-generation engines that provide highly efficient processing of very large data volumes stored in distributed file systems, like S3, ADLS and others. With low cost of storage in.

Data Lake 52

Data Lake Strategy Marketing Optimization 52

AWS Big Data

NOVEMBER 22, 2023

Today, we’re making available a new capability of AWS Glue Data Catalog that allows generating column-level statistics for AWS Glue tables. These statistics are now integrated with the cost-based optimizers (CBO) of Amazon Athena and Amazon Redshift Spectrum , resulting in improved query performance and potential cost savings.

Statistics 130

Statistics Data Lake Optimization Data-driven 130

AWS Big Data

NOVEMBER 29, 2024

Customers often want to augment and enrich SAP source data with other non-SAP source data. Such analytic use cases can be enabled by building a data warehouse or data lake. Customers can now use the AWS Glue SAP OData connector to extract data from SAP.

Visualization 105

Visualization Data Processing Data-driven Cost-Benefit 105

Smart Data Collective

FEBRUARY 20, 2022

Your SaaS company can store and protect any amount of data using Amazon Simple Storage Service (S3), which is ideal for data lakes, cloud-native applications, and mobile apps. Management of data. This blog post has demonstrated how AWS can greatly benefit your SaaS company, on multiple levels. Conclusions.

Cost-Benefit 138

Cost-Benefit Data Lake Software Machine Learning 138

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 116

Data Lake Snapshot Big Data Data-driven 116

Alation

FEBRUARY 20, 2020

For many enterprises, a hybrid cloud data lake is no longer a trend, but becoming reality. Not only can resources be quickly provisioned and optimized for different workloads and processing needs, but it can be done cost effectively. The Problem with Hybrid Cloud Environments. How to Catalog AWS S3 with Alation.

Data Lake 52

Data Lake ROI Metadata Cost-Benefit 52

AWS Big Data

OCTOBER 21, 2024

However, enterprises often encounter challenges with data silos, insufficient access controls, poor governance, and quality issues. Embracing data as a product is the key to address these challenges and foster a data-driven culture. In this context, Amazon DataZone is the optimal choice for managing the enterprise data platform.

Sales 115

Sales Data-driven Data Processing Key Performance Indicator 115

CIO Business Intelligence

MAY 21, 2024

The Concert offering focuses on dependency mapping across an increasingly broad set of data sources (or entities) to enable developers, site reliability engineers (SREs) , and operations to better understand potential problems at the application layer, according to IDC Research Vice President Stephen Elliot. “As

Enterprise 110

Enterprise Management Data Lake Risk 110

CIO Business Intelligence

APRIL 25, 2022

Now generally available, the M&E data lakehouse comes with industry use-case specific features that the company calls accelerators, including real-time personalization, said Steve Sobel, the company’s global head of communications, in a blog post. Features focus on media and entertainment firms.

Recreation/Entertainment 119

Recreation/Entertainment Data Lake Data Warehouse Unstructured Data 119

Cloudera

JUNE 2, 2022

CDF-PC is a cloud native universal data distribution service powered by Apache NiFi on Kubernetes, ??allowing allowing developers to connect to any data source anywhere with any structure, process it, and deliver to any destination. This blog aims to answer two questions: What is a universal data distribution service?

Enterprise 104

Enterprise Data Lake Data Collection Data-driven 104

AWS Big Data

AUGUST 19, 2024

In this post, we explore how AWS Glue can serve as the data integration service to bring the data from Snowflake for your data integration strategy, enabling you to harness the power of your data ecosystem and drive meaningful outcomes across various use cases. Store the extracted and transformed data in Amazon S3.

Analytics 119

Analytics Data-driven Data Integration Data Lake 119