AWS Big Data

JUNE 10, 2024

This amalgamation empowers vendors with authority over a diverse range of workloads by virtue of owning the data. This authority extends across realms such as business intelligence, data engineering, and machine learning thus limiting the tools and capabilities that can be used.

Data Lake 121

Data Lake Metadata Snapshot Analytics 121

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

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 105

Data Lake Statistics Broadcasting Optimization 105

AWS Big Data

AUGUST 9, 2023

The combination of a data lake in a serverless paradigm brings significant cost and performance benefits. By monitoring application logs, you can gain insights into job execution, troubleshoot issues promptly to ensure the overall health and reliability of data pipelines.

Data Lake 93

Data Lake Metrics Testing Cost-Benefit 93

Corinium

JUNE 6, 2019

Some of the work is very foundational, such as building an enterprise data lake and migrating it to the cloud, which enables other more direct value-added activities such as self-service. There is usually a steep learning curve in terms of “doing AI right”, which is invaluable.

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

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 125

Data Lake Metadata Statistics Optimization 125

AWS Big Data

DECEMBER 17, 2024

Today, Amazon Redshift is used by customers across all industries for a variety of use cases, including data warehouse migration and modernization, near real-time analytics, self-service analytics, data lake analytics, machine learning (ML), and data monetization.

Data Lake 81

Data Lake Data Warehouse Data-driven Optimization 81

Jet Global

SEPTEMBER 4, 2020

There is an established body of practice around creating, managing, and accessing OLAP data (known as “cubes”). Data Lakes. There has been a lot of talk over the past year or two in the D365F&SCM world about “data lakes.” Traditional databases and data warehouses do not lend themselves to that task.

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

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 103

Data Lake Data Processing Metadata Snapshot 103

AWS Big Data

JANUARY 9, 2025

These features allow efficient data corrections, gap-filling in time series, and historical data updates without disrupting ongoing analyses or compromising data integrity. Unlike direct Amazon S3 access, Iceberg supports these operations on petabyte-scale data lakes without requiring complex custom code.

Metadata 106

Metadata Snapshot Cost-Benefit Optimization 106

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.

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

AWS Big Data

JUNE 10, 2024

Use cases for Hive metastore federation for Amazon EMR Hive metastore federation for Amazon EMR is applicable to the following use cases: Governance of Amazon EMR-based data lakes – Producers generate data within their AWS accounts using an Amazon EMR-based data lake supported by EMRFS on Amazon Simple Storage Service (Amazon S3)and HBase.

Data Lake 95

Data Lake Metadata Data Warehouse Data Processing 95

DataKitchen

SEPTEMBER 18, 2024

These leaders are expected to influence organizational behavior without direct authority, leading to what DataKitchen CEO Christopher Bergh described as “data nags”—individuals who know what’s wrong but struggle to get others to act. Who should make the change (data engineers, system owners, or data quality professionals).

Scorecard 177

Scorecard Data Quality Measurement Testing 177

Cloudera

FEBRUARY 16, 2022

In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin. We will learn what it is, why it is important and how Cloudera Machine Learning (CML) is helping organisations tackle this challenge as part of the broader objective of achieving Ethical AI.

Machine Learning 85

Machine Learning Modeling Metadata Recreation/Entertainment 85

CIO Business Intelligence

AUGUST 9, 2024

At Atlanta’s Hartsfield-Jackson International Airport, an IT pilot has led to a wholesale data journey destined to transform operations at the world’s busiest airport, fueled by machine learning and generative AI. Data integrity presented a major challenge for the team, as there were many instances of duplicate data.

Data Transformation 126

Data Transformation Machine Learning Data Lake Dashboards 126

CIO Business Intelligence

OCTOBER 11, 2022

The goal, she explained, is to knock down data silos between those groups, using multiple data lakes supported by strong security and governance, to drive positive impact across the supply chain, manufacturing, and the clinical trials of new drugs. . Four ways to improve data-driven business transformation . “You

Machine Learning 145

Machine Learning Data Science Data-driven Testing 145

CIO Business Intelligence

NOVEMBER 4, 2022

Rigid requirements to ensure the accuracy of data and veracity of scientific formulas as well as machine learning algorithms and data tools are common in modern laboratories. When Bob McCowan was promoted to CIO at Regeneron Pharmaceuticals in 2018, he had previously run the data center infrastructure for the $81.5

Data Lake 124

Data Lake IT Experimentation Data-driven 124

CIO Business Intelligence

APRIL 8, 2025

Comparison of modern data architectures : Architecture Definition Strengths Weaknesses Best used when Data warehouse Centralized, structured and curated data repository. Inflexible schema, poor for unstructured or real-time data. Data lake Raw storage for all types of structured and unstructured data.

Data Quality 102

Data Quality Data-driven Key Performance Indicator Metadata 102

AWS Big Data

NOVEMBER 22, 2024

Organizations run millions of Apache Spark applications each month on AWS, moving, processing, and preparing data for analytics and machine learning. Data practitioners need to upgrade to the latest Spark releases to benefit from performance improvements, new features, bug fixes, and security enhancements. Python 3.7)

Cost-Benefit 95

Cost-Benefit Data-driven Software Testing 95

CIO Business Intelligence

MARCH 29, 2024

That’s why Rocket Mortgage has been a vigorous implementor of machine learning and AI technologies — and why CIO Brian Woodring emphasizes a “human in the loop” AI strategy that will not be pinned down to any one generative AI model. Today, 60% to 70% of Rocket’s workloads run on the cloud, with more than 95% of those workloads in AWS.

Data Lake 134

Data Lake Machine Learning Data Warehouse Unstructured Data 134

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. Today, we backflush our data lake through our data warehouse.

Data Lake 128

Data Lake Data Warehouse Unstructured Data Data Architecture 128

DataKitchen

JULY 27, 2023

You can use it for big data analytics and machine learning workloads. Azure Databricks Delta Live Table s: These provide a more straightforward way to build and manage Data Pipelines for the latest, high-quality data in Delta Lake. Azure Blob Storage serves as the data lake to store raw data.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

Smart Data Collective

FEBRUARY 20, 2022

Data storage databases. 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. AWS also offers developers the technology to develop smart apps using machine learning and complex algorithms.

Cost-Benefit 138

Cost-Benefit Data Lake Software Machine Learning 138

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. A question arises on what level of details we need to include in the table metadata.

Metadata 88

Metadata Data Lake Modeling Data Warehouse 88

AWS Big Data

DECEMBER 16, 2024

For each service, you need to learn the supported authorization and authentication methods, data access APIs, and framework to onboard and test data sources. To solve for these challenges, we launched Amazon SageMaker Lakehouse unified data connectivity. To learn more, refer to Amazon SageMaker Unified Studio.

Visualization 71

Visualization Data Processing Testing Publishing 71

Cloudera

AUGUST 28, 2020

In order for edge analytics to be successful, you still need the cloud or a centralized data hub, when you can land petabytes of live or test data in the cloud, or a centralized data cluster and then use it to, train, test, and iterate on machine learning models using all that data.

IoT 110

IoT Machine Learning B2B Testing 110

AWS Big Data

MARCH 4, 2024

As enterprises collect increasing amounts of data from various sources, the structure and organization of that data often need to change over time to meet evolving analytical needs. Schema evolution enables adding, deleting, renaming, or modifying columns without needing to rewrite existing data.

Snapshot 123

Snapshot Data Lake Metadata Recreation/Entertainment 123

Smart Data Collective

OCTOBER 17, 2022

A point of data entry in a given pipeline. Examples of an origin include storage systems like data lakes, data warehouses and data sources that include IoT devices, transaction processing applications, APIs or social media. The final point to which the data has to be eventually transferred is a destination.

Data Warehouse 145

Data Warehouse Data Lake Visualization Big Data 145

AWS Big Data

NOVEMBER 29, 2023

This cloud service was a significant leap from the traditional data warehousing solutions, which were expensive, not elastic, and required significant expertise to tune and operate. Amazon Redshift Serverless, generally available since 2021, allows you to run and scale analytics without having to provision and manage the data warehouse.

Data Warehouse 112

Data Warehouse Analytics Data Lake Machine Learning 112

CIO Business Intelligence

APRIL 26, 2024

billion acquisition of data and analytics company Neustar in 2021, TransUnion has expanded into other services such as marketing, fraud detection and prevention, and robust analytical services. The platform approach to AI TransUnion has been developing, deploying, and continuously modifying machine learning models for some time.

Modeling 114

Modeling IT Machine Learning Data Governance 114

AWS Big Data

FEBRUARY 26, 2025

Analytics remained one of the key focus areas this year, with significant updates and innovations aimed at helping businesses harness their data more efficiently and accelerate insights. From enhancing data lakes to empowering AI-driven analytics, AWS unveiled new tools and services that are set to shape the future of data and analytics.

Analytics 59

Analytics Data Lake Metadata Data Warehouse 59

CIO Business Intelligence

MAY 26, 2022

When companies first start deploying artificial intelligence and building machine learning projects, the focus tends to be on theory. But the tools that data scientists use to create these proofs of concept often don’t translate well into production systems. You need traceability of your code, data, and models.”.

Machine Learning 145

Machine Learning Data-driven Modeling Dashboards 145

CIO Business Intelligence

MAY 28, 2022

When companies first start deploying artificial intelligence and building machine learning projects, the focus tends to be on theory. But the tools that data scientists use to create these proofs of concept often don’t translate well into production systems. You need traceability of your code, data, and models.”.

Machine Learning 143

Machine Learning Data-driven Modeling Dashboards 143

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. These tables are then joined with tables from the Enterprise Data Lake (EDL) at runtime. options(**read_config).option("query",

Data Processing 104

Data Processing Data Lake Data Warehouse Optimization 104

AWS Big Data

JUNE 25, 2024

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. Connection to Amazon Redshift is established by deploying a data stream in Salesforce Data Cloud.

Data Lake 111

Data Lake Cost-Benefit Data-driven Data Warehouse 111

Cloudera

JUNE 30, 2022

Today’s general availability announcement covers Iceberg running within key data services in the Cloudera Data Platform (CDP) — including Cloudera Data Warehousing ( CDW ), Cloudera Data Engineering ( CDE ), and Cloudera Machine Learning ( CML ).

Data Lake 88

Data Lake Data Warehouse Data Architecture Metadata 88

Cloudera

OCTOBER 13, 2020

In the beginning, CDP ran only on AWS with a set of services that supported a handful of use cases and workload types: CDP Data Warehouse: a kubernetes-based service that allows business analysts to deploy data warehouses with secure, self-service access to enterprise data. Learn More, Keep in Touch. This is Now.

Data Warehouse 97

Data Warehouse Machine Learning Visualization Data Lake 97