CIO Business Intelligence

DECEMBER 20, 2024

Beyond breaking down silos, modern data architectures need to provide interfaces that make it easy for users to consume data using tools fit for their jobs. Data must be able to freely move to and from data warehouses, data lakes, and data marts, and interfaces must make it easy for users to consume that data.

Data Architecture 122

Data Architecture Management Consulting Internet of Things 122

IBM Big Data Hub

JUNE 26, 2020

Organizations need to collect, organize, and analyze their data across multi-cloud, hybrid cloud, and data lakes. In turn, enterprises are increasingly looking for machine-learning-powered integration tools to synchronize data for analytics, improve employee productivity, and prepare data for analytics.

Data Integration 107

Data Integration Data Lake Machine Learning Enterprise 107

AWS Big Data

SEPTEMBER 10, 2024

We often see requests from customers who have started their data journey by building data lakes on Microsoft Azure, to extend access to the data to AWS services. In such scenarios, data engineers face challenges in connecting and extracting data from storage containers on Microsoft Azure.

Data Lake 110

Data Lake Metadata Management Software 110

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. 5 seconds $0.08 8 seconds $0.07

Data Lake 126

Data Lake Metadata Snapshot Analytics 126

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 117

Data Lake Metadata Data Warehouse Data Processing 117

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

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

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

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

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 110

Metadata Snapshot Cost-Benefit Optimization 110

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. Use one click to access your data lake tables using auto-mounted AWS Glue data catalogs on Amazon Redshift for a simplified experience.

Data Warehouse 130

Data Warehouse Analytics Data Lake Machine Learning 130

AWS Big Data

DECEMBER 16, 2024

Third, some services require you to set up and manage compute resources used for federated connectivity, and capabilities like connection testing and data preview arent available in all services. To solve for these challenges, we launched Amazon SageMaker Lakehouse unified data connectivity.

Visualization 95

Visualization Data Processing Testing Publishing 95

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

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. It provides secure, real-time access to Redshift data without copying, keeping enterprise data in place.

Data Lake 121

Data Lake Cost-Benefit Data-driven Data Warehouse 121

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

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. To achieve this, they plan to use machine learning (ML) models to extract insights from data.

Sales 115

Sales Data-driven Data Processing Key Performance Indicator 115

Data Virtualization

MARCH 27, 2019

With data becoming the brain food to the intelligence of every organization, regardless of size or sector, it has become crucial to harness this data to achieve the best results, make the most informed decisions and improve productivity. However, with.

Data Lake 53

Data Lake Machine Learning IT Data Integration 53

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 115

Data Lake Data Warehouse Data-driven Optimization 115

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

CIO Business Intelligence

AUGUST 3, 2022

CIOs who use low-code/no-code platforms and new governance models to create self-service data capabilities are turning shadow IT into citizen developers who can fish for their own data. The challenge for CIOs who want to improve their company’s analytics capabilities is a familiar one: data integrity versus innovation. “In

Finance 145

Finance IoT Digital Transformation Sales 145

CIO Business Intelligence

APRIL 25, 2022

The data lakehouse is a relatively new data architecture concept, first championed by Cloudera, which offers both storage and analytics capabilities as part of the same solution, in contrast to the concepts for data lake and data warehouse which, respectively, store data in native format, and structured data, often in SQL format.

Recreation/Entertainment 119

Recreation/Entertainment Data Lake Data Warehouse Unstructured Data 119

Cloudera

JULY 18, 2018

To arrive at quality data, organizations are spending significant levels of effort on data integration, visualization, and deployment activities. Additionally, organizations are increasingly restrained due to budgetary constraints and having limited data sciences resources.

Machine Learning 51

Machine Learning Predictive Analytics Analytics Prescriptive Analytics 51

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 110

Data Lake Big Data Data Warehouse Consulting 110

AWS Big Data

DECEMBER 18, 2023

Customers use Amazon Redshift as a key component of their data architecture to drive use cases from typical dashboarding to self-service analytics, real-time analytics, machine learning (ML), data sharing and monetization, and more.

Data Warehouse 110

Data Warehouse Machine Learning Data-driven Data Lake 110

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 110

Data Processing Data Lake Data Warehouse Optimization 110

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.

Cost-Benefit 105

Cost-Benefit Data-driven Software Testing 105

DataKitchen

DECEMBER 9, 2022

ChatGPT> DataOps is a term that refers to the set of practices and tools that organizations use to improve the quality and speed of data analytics and machine learning. It involves bringing together people, processes, and technology to enable data-driven decision making and improve the efficiency of data-related workflows.

Machine Learning 130

Machine Learning Data-driven Optimization Data Analytics 130

AWS Big Data

NOVEMBER 13, 2023

He highlights innovations in data, infrastructure, and artificial intelligence and machine learning that are helping AWS customers achieve their goals faster, mine untapped potential, and create a better future. KEY003 | Swami Sivasubramanian (Vice President, Data and AI at AWS) | Nov.

Analytics 118

Analytics Data Lake Data Warehouse Data-driven 118

CIO Business Intelligence

FEBRUARY 20, 2024

Data also needs to be sorted, annotated and labelled in order to meet the requirements of generative AI. No wonder CIO’s 2023 AI Priorities study found that data integration was the number one concern for IT leaders around generative AI integration, above security and privacy and the user experience.

Cost-Benefit 115

Cost-Benefit Data Lake Data Warehouse Data Processing 115

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 118

Data Lake Data Warehouse Big Data Structured Data 118

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 62

Analytics Data Lake Metadata Data Warehouse 62

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 115

Data Lake Snapshot Metadata Optimization 115

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

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 110

Data Warehouse Analytics Data Lake Data Science 110

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

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.

Analytics 118

Analytics Data-driven Data Integration Data Lake 118

AWS Big Data

NOVEMBER 30, 2023

In this post, we explore how to use the AWS Glue native connector for Teradata Vantage to streamline data integrations and unlock the full potential of your data. Businesses often rely on Amazon Simple Storage Service (Amazon S3) for storing large amounts of data from various data sources in a cost-effective and secure manner.

IT 115

IT Visualization Machine Learning Data Integration 115