DataKitchen

AUGUST 3, 2021

The data mesh design pattern breaks giant, monolithic enterprise data architectures into subsystems or domains, each managed by a dedicated team. First-generation – expensive, proprietary enterprise data warehouse and business intelligence platforms maintained by a specialized team drowning in technical debt.

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

AWS Big Data

APRIL 3, 2024

They understand that a one-size-fits-all approach no longer works, and recognize the value in adopting scalable, flexible tools and open data formats to support interoperability in a modern data architecture to accelerate the delivery of new solutions.

Data Lake 112

Data Lake Snapshot Metadata Data Architecture 112

DataKitchen

NOVEMBER 29, 2021

Data Gets Meshier. 2022 will bring further momentum behind modular enterprise architectures like data mesh. The data mesh addresses the problems characteristic of large, complex, monolithic data architectures by dividing the system into discrete domains managed by smaller, cross-functional teams.

Testing 245

Testing Data Lake Data Architecture Manufacturing 245

Cloudera

MAY 28, 2024

It’s not enough for businesses to implement and maintain a data architecture. The unpredictability of market shifts and the evolving use of new technologies means businesses need more data they can trust than ever to stay agile and make the right decisions.

Data Architecture 88

Data Architecture Data Lake Data Warehouse Cost-Benefit 88

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 129

Data Lake Data Warehouse Visualization Snapshot 129

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. and Delta Lake 2.3.0. Apache Iceberg 1.2.0,

Data Lake 128

Data Lake Metadata Statistics Optimization 128

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 120

Data Lake Sales Data Warehouse Snapshot 120

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 127

Data Lake Publishing Metadata Data-driven 127

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. However, efficiently managing and synchronizing data within these lakes presents a significant challenge.

Data Lake 115

Data Lake Marketing Data Processing Management 115

AWS Big Data

DECEMBER 4, 2024

While traditional extract, transform, and load (ETL) processes have long been a staple of data integration due to its flexibility, for common use cases such as replication and ingestion, they often prove time-consuming, complex, and less adaptable to the fast-changing demands of modern data architectures. What is zero-ETL?

Data Integration 105

Data Integration Data Lake Statistics Data-driven 105

AWS Big Data

AUGUST 31, 2023

Amazon Redshift is a fast, fully managed petabyte-scale cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools. Amazon Redshift also supports querying nested data with complex data types such as struct, array, and map.

Data Lake 113

Data Lake Data Warehouse Metadata Data Architecture 113

AWS Big Data

OCTOBER 1, 2024

Amazon Redshift enables you to efficiently query and retrieve structured and semi-structured data from open format files in Amazon S3 data lake without having to load the data into Amazon Redshift tables. Amazon Redshift extends SQL capabilities to your data lake, enabling you to run analytical queries.

Data Lake 111

Data Lake Statistics Broadcasting Optimization 111

David Menninger's Analyst Perspectives

JANUARY 15, 2021

Traditional on-premises data processing solutions have led to a hugely complex and expensive set of data silos where IT spends more time managing the infrastructure than extracting value from the data.

IT 306

IT Data Architecture Big Data Data Processing 306

AWS Big Data

JUNE 10, 2024

The open table format accelerates companies’ adoption of a modern data strategy because it allows them to use various tools on top of a single copy of the data. A solution based on Apache Iceberg encompasses complete data management, featuring simple built-in table optimization capabilities within an existing storage solution.

Data Lake 125

Data Lake Metadata Snapshot Analytics 125

AWS Big Data

DECEMBER 4, 2024

Ask questions in plain English to find the right datasets, automatically generate SQL queries, or create data pipelines without writing code. This innovation drives an important change: you’ll no longer have to copy or move data between data lake and data warehouses.

Data Analytics 92

Data Analytics Analytics Data Lake Data Quality 92

DataKitchen

NOVEMBER 4, 2021

Data organizations often have a mix of centralized and decentralized activity. DataOps concerns itself with the complex flow of data across teams, data centers and organizational boundaries. It expands beyond tools and data architecture and views the data organization from the perspective of its processes and workflows.

Data Processing 246

Data Processing Data Lake Cost-Benefit Testing 246

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 108

Data Lake Data Processing Metadata Snapshot 108

Cloudera

MARCH 28, 2024

But, even with the backdrop of an AI-dominated future, many organizations still find themselves struggling with everything from managing data volumes and complexity to security concerns to rapidly proliferating data silos and governance challenges. Let’s explore some of the most important findings that the survey uncovered.

Data Architecture 94

Data Architecture Strategy Data Lake Data-driven 94

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 103

Data Lake Metadata Data Warehouse Data Processing 103

AWS Big Data

FEBRUARY 26, 2025

This recognition, we feel, reflects our ongoing commitment to innovation and excellence in data integration, demonstrating our continued progress in providing comprehensive data management solutions. This graphic was published by Gartner, Inc. The Gartner document is available upon request from here.

Data Integration 87

Data Integration Data Lake Data Warehouse Unstructured Data 87

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 97

Data Lake Analytics Snapshot Data Quality 97

Cloudera

SEPTEMBER 6, 2022

There remain challenges in workforce management, particularly in call centers, and order backlogs for fiber broadband and other physical infrastructure are being worked through. Previously, there were three types of data structures in telco: . Entity data sets — i.e. marketing data lakes . The challenges.

Data Architecture 84

Data Architecture Cost-Benefit Digital Transformation Business Driver 84

AWS Big Data

JANUARY 15, 2025

Their terminal operations rely heavily on seamless data flows and the management of vast volumes of data. With the addition of these technologies alongside existing systems like terminal operating systems (TOS) and SAP, the number of data producers has grown substantially. datazone_env_twinsimsilverdata"."cycle_end";')

IoT 106

IoT Machine Learning Metadata Data-driven 106

Data Virtualization

OCTOBER 5, 2022

Reading Time: 3 minutes At the heart of every organization lies a data architecture, determining how data is accessed, organized, and used. 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

CIO Business Intelligence

NOVEMBER 28, 2023

To avoid the inevitable, CIOs must get serious about data management. Data, of course, has been all the rage the past decade, having been declared the “new oil” of the digital economy. Still, to truly create lasting value with data, organizations must develop data management mastery.

Management 131

Management Data Architecture Data Lake Data Strategy 131

AWS Big Data

FEBRUARY 14, 2023

Organizations have chosen to build data lakes on top of Amazon Simple Storage Service (Amazon S3) for many years. A data lake is the most popular choice for organizations to store all their organizational data generated by different teams, across business domains, from all different formats, and even over history.

Data Lake 94

Data Lake Statistics Data Architecture Finance 94

Cloudera

AUGUST 30, 2022

That should be easy, but when agencies don’t share data or applications, they don’t have a unified view of people. As such, managers at different agencies need to sort through multiple systems to make sure these documents are delivered correctly—even though they all apply to the same individuals.”. Modern data architectures.

Data Architecture 79

Data Architecture Data Lake Data Warehouse Metadata 79

AWS Big Data

JULY 21, 2023

This leads to having data across many instances of data warehouses and data lakes using a modern data architecture in separate AWS accounts. Customers want to be able to manage their permissions in a central place across all of their assets.

Data Lake 97

Data Lake Data Warehouse Marketing Management 97

CIO Business Intelligence

NOVEMBER 25, 2022

As part of that transformation, Agusti has plans to integrate a data lake into the company’s data architecture and expects two AI proofs of concept (POCs) to be ready to move into production within the quarter. It’s a different beast to manage workloads in the cloud versus workloads on premise.

Data Lake 128

Data Lake Data Warehouse Unstructured Data Data Architecture 128

Cloudera

OCTOBER 23, 2024

In August, we wrote about how in a future where distributed data architectures are inevitable, unifying and managing operational and business metadata is critical to successfully maximizing the value of data, analytics, and AI.

Metadata 84

Metadata Data Lake Dashboards Interactive 84

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 87

Data Lake Testing Snapshot Sales 87

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 94

Data Lake Data Governance Machine Learning Cost-Benefit 94

DataKitchen

JANUARY 3, 2022

Business analysts must rapidly deliver value and simultaneously manage fragile and error-prone analytics production pipelines. Data tables from IT and other data sources require a large amount of repetitive, manual work to be used in analytics. IT-created infrastructure such as a data lake/warehouse).

Business Analytics 245

Business Analytics Analytics Testing Dashboards 245

AWS Big Data

FEBRUARY 15, 2024

Many organizations use identity providers (IdPs) to authenticate users, manage their attributes, and group memberships for secure, efficient, and centralized identity management. AWS Lake Formation makes it straightforward to centrally govern, secure, and globally share data for analytics and machine learning (ML).

Management 109

Management Data Lake Sales Data Warehouse 109

CIO Business Intelligence

MARCH 9, 2022

They’re comparatively expensive and can’t handle big data analytics. However, they do contain effective data management, organization, and integrity capabilities. As a result, users can easily find what they need, and organizations avoid the operational and cost burdens of storing unneeded or duplicate data copies.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Big Data 119