KDnuggets

AUGUST 1, 2022

Extract-Transform-Load vs Extract-Load-Transform: Data integration methods used to transfer data from one source to a data warehouse. Their aims are similar, but see how they differ.

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Data Integration Data Warehouse Data Science 106

AWS Big Data

AUGUST 15, 2024

Unifying these necessitates additional data processing, requiring each business unit to provision and maintain a separate data warehouse. This burdens business units focused solely on consuming the curated data for analysis and not concerned with data management tasks, cleansing, or comprehensive data processing.

Data Lake 121

Data Lake Data Warehouse Data Governance Publishing 121

BI-Survey

AUGUST 21, 2020

But what are the right measures to make the data warehouse and BI fit for the future? Can the basic nature of the data be proactively improved? The following insights came from a global BARC survey into the current status of data warehouse modernization. They are opting for cloud data services more frequently.

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Data Warehouse Data Lake Data Governance Data Architecture 98

AWS Big Data

DECEMBER 17, 2024

Amazon Redshift , launched in 2013, has undergone significant evolution since its inception, allowing customers to expand the horizons of data warehousing and SQL analytics. Industry-leading price-performance Amazon Redshift offers up to three times better price-performance than alternative cloud data warehouses.

Data Lake 96

Data Lake Data Warehouse Data-driven Optimization 96

CIO Business Intelligence

OCTOBER 19, 2023

The growing volume of data is a concern, as 20% of enterprises surveyed by IDG are drawing from 1000 or more sources to feed their analytics systems. Data integration needs an overhaul, which can only be achieved by considering the following gaps. Heterogeneous sources produce data sets of different formats and structures.

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Data Integration Unstructured Data Data-driven Data Warehouse 126

CIO Business Intelligence

APRIL 25, 2024

Currently, a handful of startups offer “reverse” extract, transform, and load (ETL), in which they copy data from a customer’s data warehouse or data platform back into systems of engagement where business users do their work. Sharing Customer 360 insights back without data replication.

Data Integration 119

Data Integration Data Lake Data Warehouse Metadata 119

AWS Big Data

SEPTEMBER 4, 2024

Effective data analytics relies on seamlessly integrating data from disparate systems through identifying, gathering, cleansing, and combining relevant data into a unified format. Reverse ETL use cases are also supported, allowing you to write data back to Salesforce. Kamen Sharlandjiev is a Sr. His secret weapon?

Data Integration 107

Data Integration Data Lake Data-driven Cost-Benefit 107

datapine

MAY 29, 2019

One of the BI architecture components is data warehousing. Organizing, storing, cleaning, and extraction of the data must be carried by a central repository system, namely data warehouse, that is considered as the fundamental component of business intelligence. What Is Data Warehousing And Business Intelligence?

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Business Intelligence Data Warehouse Dashboards Visualization 196

Analytics Vidhya

JULY 29, 2022

This article was published as a part of the Data Science Blogathon. Introduction Processing large amounts of raw data from various sources requires appropriate tools and solutions for effective data integration. Building an ETL pipeline using Apache […].

Data Science 383

Data Science Data Integration Publishing Analytics 383

AWS Big Data

AUGUST 22, 2024

The infrastructure provides an analytics experience to hundreds of in-house analysts, data scientists, and student-facing frontend specialists. The data engineering team is on a mission to modernize its data integration platform to be agile, adaptive, and straightforward to use.

Data Warehouse 116

Data Warehouse Data Lake Data Integration Management 116

AWS Big Data

MARCH 13, 2025

Unified access to your data is provided by Amazon SageMaker Lakehouse , a unified, open, and secure data lakehouse built on Apache Iceberg open standards. Now, theyre able to build and collaborate with their data and tools available in one experience, dramatically reducing time-to-value.

Analytics 88

Analytics Data Lake Data Warehouse Data-driven 88

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

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 102

Data Analytics Analytics Data Lake Data Quality 102

Alation

JULY 28, 2022

It’s costly and time-consuming to manage on-premises data warehouses — and modern cloud data architectures can deliver business agility and innovation. However, CIOs declare that agility, innovation, security, adopting new capabilities, and time to value — never cost — are the top drivers for cloud data warehousing.

Data Warehouse 69

Data Warehouse Cost-Benefit Data-driven Data Governance 69

AWS Big Data

JANUARY 6, 2025

Amazon AppFlow automatically encrypts data in motion, and allows you to restrict data from flowing over the public internet for SaaS applications that are integrated with AWS PrivateLink , reducing exposure to security threats. He has worked with building data warehouses and big data solutions for over 13 years.

Analytics 98

Analytics Data Warehouse Metrics Big Data 98

Data Virtualization

NOVEMBER 24, 2022

Reading Time: 4 minutes My previous post explained that, in my mind, the data lakehouse differs hardly at all from the traditional data warehouse architectural design pattern (ADP). It consists largely of the application of new cloud-based technology to the same requirements and constraints.

Data Warehouse 52

Data Warehouse Data Integration Technology Management 52

Data Virtualization

APRIL 21, 2022

Reading Time: 3 minutes First we had data warehouses, then came data lakes, and now the new kid on the block is the data lakehouse. But what is a data lakehouse and why should we develop one? In a way, the name describes what.

Data Lake 59

Data Lake Data Warehouse Data Integration Management 59

Data Virtualization

APRIL 13, 2022

Reading Time: < 1 minute The Denodo Platform, based on data virtualization, enables a wide range of powerful, modern use cases, including the ability to seamlessly create a logical data warehouse. Logical data warehouses have all of the capabilities of traditional data warehouses, yet they.

Data Warehouse 52

Data Warehouse Marketing Data Integration Management 52

In(tegrate) the Clouds

JUNE 23, 2016

This week SnapLogic posted a presentation of the 10 Modern Data Integration Platform Requirements on the company’s blog. They are: Application integration is done primarily through REST & SOAP services. Large-volume data integration is available to Hadoop-based data lakes or cloud-based data warehouses.

Data Integration 49

Data Integration Data Lake Data Warehouse Data-driven 49

Smart Data Collective

SEPTEMBER 8, 2021

The ETL process is defined as the movement of data from its source to destination storage (typically a Data Warehouse) for future use in reports and analyzes. The data is initially extracted from a vast array of sources before transforming and converting it to a specific format based on business requirements.

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Data Warehouse Data Integration Marketing Software 126

AWS Big Data

NOVEMBER 29, 2023

In 2013, Amazon Web Services revolutionized the data warehousing industry by launching Amazon Redshift , the first fully-managed, petabyte-scale, enterprise-grade cloud data warehouse. Amazon Redshift made it simple and cost-effective to efficiently analyze large volumes of data using existing business intelligence tools.

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Data Warehouse Analytics Data Lake Machine Learning 128

AWS Big Data

JANUARY 15, 2025

AWS Database Migration Service (AWS DMS) is used to securely transfer the relevant data to a central Amazon Redshift cluster. The data in the central data warehouse in Amazon Redshift is then processed for analytical needs and the metadata is shared to the consumers through Amazon DataZone.

IoT 111

IoT Machine Learning Metadata Data-driven 111

erwin

SEPTEMBER 26, 2019

The benefits of Data Vault automation from the more abstract – like improving data integrity – to the tangible – such as clearly identifiable savings in cost and time. So Seriously … You Should Automate Your Data Vault. By Danny Sandwell.

Data Warehouse 108

Data Warehouse Cost-Benefit Data Integration Consulting 108

CIO Business Intelligence

JULY 18, 2022

Central to Byrdak’s multi-year transformation plan is the expansion of MealConnect, the first nationally available food rescue and sourcing platform, and a new data warehouse to anchor an analytics offering that helps food banks analyze and visualize their food sourcing and distribution data.

Data Warehouse 141

Data Warehouse Dashboards Reporting Manufacturing 141

Smart Data Collective

MAY 31, 2022

Data activation is a new and exciting way that businesses can think of their data. It’s more than just data that provides the information necessary to make wise, data-driven decisions. It’s more than just allowing access to data warehouses that were becoming dangerously close to data silos.

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Data Warehouse Big Data Data-driven Technology 142

CIO Business Intelligence

OCTOBER 7, 2022

BI analysts, with an average salary of $71,493 according to PayScale , provide application analysis and data modeling design for centralized data warehouses and extract data from databases and data warehouses for reporting, among other tasks. BI encompasses numerous roles.

Business Intelligence 145

Business Intelligence Data Warehouse Visualization Dashboards 145

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

DataKitchen

APRIL 13, 2021

RightData – A self-service suite of applications that help you achieve Data Quality Assurance, Data Integrity Audit and Continuous Data Quality Control with automated validation and reconciliation capabilities. QuerySurge – Continuously detect data issues in your delivery pipelines. Production Monitoring Only.

Testing 304

Testing Machine Learning Consulting Data Science 304

CIO Business Intelligence

APRIL 5, 2022

Investment in data warehouses is rapidly rising, projected to reach $51.18 billion by 2028 as the technology becomes a vital cog for enterprises seeking to be more data-driven by using advanced analytics. Data warehouses are, of course, no new concept. More data, more demanding. “As

Data Warehouse 98

Data Warehouse Visualization Data-driven Data Architecture 98

AWS Big Data

NOVEMBER 28, 2023

To run analytics on their operational data, customers often build solutions that are a combination of a database, a data warehouse, and an extract, transform, and load (ETL) pipeline. ETL is the process data engineers use to combine data from different sources.

Data Warehouse 122

Data Warehouse Data-driven Machine Learning B2B 122

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. These upstream data sources constitute the data producer components.

Data Warehouse 111

Data Warehouse Analytics Data Lake Data Science 111

BizAcuity

NOVEMBER 22, 2022

This typically requires a data warehouse for analytics needs that is able to ingest and handle real time data of huge volumes. Snowflake is a cloud-native platform that eliminates the need for separate data warehouses, data lakes, and data marts allowing secure data sharing across the organization.

Data Warehouse 98

Data Warehouse Cost-Benefit Data Lake Internet of Things 98

AWS Big Data

JANUARY 30, 2025

Diagram 1: Overall architecture of the solution, using AWS Step Functions, Amazon Redshift and Amazon S3 The following AWS services were used to shape our new ETL architecture: Amazon Redshift A fully managed, petabyte-scale data warehouse service in the cloud. Its also serverless, which means theres no infrastructure to manage.

Data Warehouse 53

Data Warehouse Data Architecture Data Transformation Machine Learning 53

AWS Big Data

DECEMBER 15, 2023

Many companies identify and label PII through manual, time-consuming, and error-prone reviews of their databases, data warehouses and data lakes, thereby rendering their sensitive data unprotected and vulnerable to regulatory penalties and breach incidents. For our solution, we use Amazon Redshift to store the data.

Data Warehouse 119

Data Warehouse Data Lake Big Data Structured Data 119

AWS Big Data

DECEMBER 9, 2024

The importance of publishing only high-quality data cant be overstatedits the foundation for accurate analytics, reliable machine learning (ML) models, and sound decision-making. AWS Glue is a serverless data integration service that you can use to effectively monitor and manage data quality through AWS Glue Data Quality.

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Data Quality Publishing Snapshot Data Lake 124

Jen Stirrup

MARCH 29, 2023

However, to turn data into a business problem, organizations need support to move away from technical issues to start getting value as quickly as possible. SAP Datasphere simplifies data integration, cataloging, semantic modeling, warehousing, federation, and virtualization through a unified interface. Why is this interesting?

Data Warehouse 121

Data Warehouse Metadata Data Integration Business Intelligence 121

AWS Big Data

JUNE 25, 2024

This post is co-authored by Vijay Gopalakrishnan, Director of Product, Salesforce Data Cloud. 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.

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Data Lake Cost-Benefit Data-driven Data Warehouse 122