Dataconomy

OCTOBER 17, 2023

Want to create a robust data warehouse architecture for your business? The sheer volume of data that companies are now gathering is incredible, and understanding how best to store and use this information to extract top performance can be incredibly overwhelming.

Data Warehouse 103

Data Warehouse Big Data Big Data ETL 103

Dataconomy

MARCH 6, 2025

Data vault is not just a method; its an innovative approach to data modeling and integration tailored for modern data warehouses. As businesses continue to evolve, the complexity of managing data efficiently has grown. As businesses continue to evolve, the complexity of managing data efficiently has grown.

Data Warehouse 91

Data Warehouse Data Quality Data Models Data Modeling 91

phData

JUNE 13, 2023

While the front-end report visuals are important and the most visible to end users, a lot goes on behind the scenes that contribute heavily to the end product, including data modeling. In this blog, we’ll describe data modeling and its significance in Power BI. What is Data Modeling?

Power BI 93

Power BI Data Modeling Data Models Data Warehouse 93

Data Science Dojo

JULY 6, 2023

Data engineering tools offer a range of features and functionalities, including data integration, data transformation, data quality management, workflow orchestration, and data visualization. Essential data engineering tools for 2023 Top 10 data engineering tools to watch out for in 2023 1.

Data Engineer 195

Data Engineer Data Engineering Data Engineering Data Engineering 195

Dataversity

JUNE 24, 2022

Data models play an integral role in the development of effective data architecture for modern businesses. They are key to the conceptualization, planning, and building of an integrated data repository that drives advanced analytics and BI.

Data Modeling 52

Data Modeling Data Models Data Warehouse Analytics 52

The Data Administration Newsletter

APRIL 6, 2021

A metadata-driven data warehouse (MDW) offers a modern approach that is designed to make EDW development much more simplified and faster. It makes use of metadata (data about your data) as its foundation and combines data modeling and ETL functionalities to build data warehouses.

Data Warehouse 52

Data Warehouse ETL Data Models Data Modeling 52

Data Science Connect

JANUARY 27, 2023

Understanding how data warehousing works and how to design and implement a data warehouse is an important skill for a data engineer. Learn about data modeling: Data modeling is the process of creating a conceptual representation of data.

Data Engineer 130

Data Engineer Data Engineering Data Engineering Data Engineering 130

Precisely

MARCH 9, 2023

Data warehouse vs. data lake, each has their own unique advantages and disadvantages; it’s helpful to understand their similarities and differences. In this article, we’ll focus on a data lake vs. data warehouse. Read Many of the preferred platforms for analytics fall into one of these two categories.

Data Warehouse 59

Data Warehouse Data Lakes Hadoop Big Data 59

phData

SEPTEMBER 19, 2023

However, to fully harness the potential of a data lake, effective data modeling methodologies and processes are crucial. Data modeling plays a pivotal role in defining the structure, relationships, and semantics of data within a data lake. Consistency of data throughout the data lake.

Data Lakes 52

Data Lakes Data Modeling Data Models Data Warehouse 52

Pickl AI

FEBRUARY 23, 2023

Organisations must store data in a safe and secure place for which Databases and Data warehouses are essential. You must be familiar with the terms, but Database and Data Warehouse have some significant differences while being equally crucial for businesses. What is Data Warehouse?

Data Warehouse 52

Data Warehouse Database Data Analysis Data Analysis 52

Dataversity

NOVEMBER 2, 2023

Among these advancements is modern data warehousing, a comprehensive approach that provides access to vast and disparate datasets. The concept of data warehousing emerged as organizations began to […] The post The Data Warehouse Development Lifecycle Explained appeared first on DATAVERSITY.

Data Warehouse 59

Data Warehouse Data Modeling Data Models 59

Women in Big Data

NOVEMBER 27, 2024

A data warehouse is a centralized repository designed to store and manage vast amounts of structured and semi-structured data from multiple sources, facilitating efficient reporting and analysis. Begin by determining your data volume, variety, and the performance expectations for querying and reporting.

Data Warehouse 59

Data Warehouse Big Data Big Data Azure 59

Dataversity

MARCH 1, 2021

Data warehouse (DW) testers with data integration QA skills are in demand. Data warehouse disciplines and architectures are well established and often discussed in the press, books, and conferences. Each business often uses one or more data […]. Each business often uses one or more data […].

Data Warehouse 52

Data Warehouse ETL Data Governance Data Quality 52

Smart Data Collective

MAY 16, 2022

These include, but are not limited to, database management systems, data mining software, decision support systems, knowledge management systems, data warehousing, and enterprise data warehouses. Some data management strategies are in-house and others are outsourced. They are a part of the data management system.

Data Warehouse 136

Data Warehouse Data Mining Data Mining Data Mining 136

phData

SEPTEMBER 27, 2024

Introduction: The Customer Data Modeling Dilemma You know, that thing we’ve been doing for years, trying to capture the essence of our customers in neat little profile boxes? For years, we’ve been obsessed with creating these grand, top-down customer data models. Yeah, that one.

Data Modeling 52

Data Modeling Data Models Apache Kafka Data Lakes 52

ODSC - Open Data Science

SEPTEMBER 27, 2023

In this article, we will delve into the concept of data lakes, explore their differences from data warehouses and relational databases, and discuss the significance of data version control in the context of large-scale data management. Schema Enforcement: Data warehouses use a “schema-on-write” approach.

Data Lakes 98

Data Lakes Data Warehouse Database Big Data 98

Smart Data Collective

JUNE 16, 2022

Data is fed into an Analytical server (or OLAP cube), which calculates information ahead of time for later analysis. A data warehouse extracts data from a variety of sources and formats, including text files, excel sheets, multimedia files, and so on. Types: HOLAP stands for Hybrid Online Analytical Processing.

Analytics 139

Analytics Analytics Data Scientist Data Warehouse 139

ODSC - Open Data Science

JUNE 12, 2023

This article is an excerpt from the book Expert Data Modeling with Power BI, Third Edition by Soheil Bakhshi, a completely updated and revised edition of the bestselling guide to Power BI and data modeling. in an enterprise data warehouse. What is a Datamart?

Power BI 52

Power BI Data Warehouse ETL Data Preparation 52

Smart Data Collective

JULY 9, 2023

ETL is a three-step process that involves extracting data from various sources, transforming it into a consistent format, and loading it into a target database or data warehouse. Extract The extraction phase involves retrieving data from diverse sources such as databases, spreadsheets, APIs, or other systems.

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ETL Data Quality Data Warehouse Analytics 105

The Data Administration Newsletter

APRIL 19, 2022

Introduction We are living in the age of a data revolution, and more corporations are realizing that to lead—or in some cases, to survive—they need to harness their data wealth effectively.

Data Warehouse 72

Data Warehouse Data Modeling Data Models Business Intelligence 72

Dataconomy

SEPTEMBER 4, 2023

Key features of cloud analytics solutions include: Data models , Processing applications, and Analytics models. Data models help visualize and organize data, processing applications handle large datasets efficiently, and analytics models aid in understanding complex data sets, laying the foundation for business intelligence.

Analytics 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

Tableau

APRIL 3, 2023

Madeleine Corneli Senior Manager, Product Management, Tableau Adiascar Cisneros Manager, Product Management, Tableau Bronwen Boyd April 3, 2023 - 5:27pm April 3, 2023 Google Cloud’s BigQuery is a serverless, highly-scalable cloud-based data warehouse solution that allows users to store, query, and analyze large datasets quickly.

Tableau 98

Tableau SQL Data Warehouse Database 98

Smart Data Collective

NOVEMBER 18, 2020

Data Mining Techniques and Data Visualization. Data Mining is an important research process. Practical experience. It is not very interesting to be engaged exclusively in theory, it is important to try your hand at practice.

Data Mining 144

Data Mining Data Mining Data Mining Data Science 144

Tableau

MAY 11, 2022

At Tableau, we’re leading the industry with capabilities to connect to a wide variety of data, and we have made it a priority for the years to come. Connector library for accessing databases and applications outside of Tableau regardless of the data source (data warehouse, CRM, etc.)

Tableau 98

Tableau Data Warehouse Database Data Analyst 98

Tableau

MAY 11, 2022

At Tableau, we’re leading the industry with capabilities to connect to a wide variety of data, and we have made it a priority for the years to come. Connector library for accessing databases and applications outside of Tableau regardless of the data source (data warehouse, CRM, etc.)

Tableau 98

Tableau Data Warehouse Database Data Analyst 98

phData

OCTOBER 9, 2023

Understanding Data Vault Modeling Created in the 1990s by a team at Lockheed Martin, data vault modeling is a hybrid approach that combines traditional relational data warehouse models with newer big data architectures to build a data warehouse for enterprise-scale analytics.

ETL 69

ETL Clustering Data Warehouse SQL 69

Pickl AI

NOVEMBER 4, 2024

Summary: The fundamentals of Data Engineering encompass essential practices like data modelling, warehousing, pipelines, and integration. Understanding these concepts enables professionals to build robust systems that facilitate effective data management and insightful analysis. What is Data Engineering?

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

phData

JULY 17, 2023

Over the past few decades, the corporate data landscape has changed significantly. The shift from on-premise databases and spreadsheets to the modern era of cloud data warehouses and AI/ LLMs has transformed what businesses can do with data. Data modeling, data cleanup, etc.

Data Warehouse 52

Data Warehouse Data Pipeline Cloud Data ETL 52

Mlearning.ai

MAY 16, 2023

ETL Design Pattern The ETL (Extract, Transform, Load) design pattern is a commonly used pattern in data engineering. It is used to extract data from various sources, transform the data to fit a specific data model or schema, and then load the transformed data into a target system such as a data warehouse or a database.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

Tableau

DECEMBER 7, 2022

Traditionally, organizations built complex data pipelines to replicate data. Those data architectures were brittle, complex, and time intensive to build and maintain, requiring data duplication and bloated data warehouse investments. Natively connect to trusted, unified customer data.

Tableau 98

Tableau Data Warehouse Data Pipeline Data Visualization 98

Tableau

DECEMBER 7, 2022

Traditionally, organizations built complex data pipelines to replicate data. Those data architectures were brittle, complex, and time intensive to build and maintain, requiring data duplication and bloated data warehouse investments. Natively connect to trusted, unified customer data.

Tableau 98

Tableau Data Warehouse Data Pipeline Data Visualization 98

phData

JUNE 6, 2024

These traditional CDPs are designed to gather and house their own data store—separate from the core data infrastructure. Because of this separation, data models are rigid, and the setup process is costly and lengthy. Data gets ingested, centralized, and deployed within your cloud data warehouse.

Data Warehouse 52

Data Warehouse Cloud Data ETL Data Models 52

Mlearning.ai

FEBRUARY 16, 2023

The ultimate need for vast storage spaces manifests in data warehouses: specialized systems that aggregate data coming from numerous sources for centralized management and consistency. In this article, you’ll discover what a Snowflake data warehouse is, its pros and cons, and how to employ it efficiently.

Data Warehouse 52

Data Warehouse Business Intelligence Business Intelligence Database 52

phData

MAY 25, 2023

One of the easiest ways for Snowflake to achieve this is to have analytics solutions query their data warehouse in real-time (also known as DirectQuery). Creating an efficient data model can be the difference between having good or bad performance, especially when using DirectQuery.

Power BI 84

Power BI Analytics Analytics Azure 84

Tableau

APRIL 18, 2022

Monitor data sources according to policies you customize to help users know if fresh, quality data is ready for use. Shine a light on who or what is using specific data to speed up collaboration or reduce disruption when changes happen. Data modeling. Data preparation. Data integration. Orchestration.

Tableau 102

Tableau Data Quality Analytics Analytics 102

Tableau

APRIL 18, 2022

Monitor data sources according to policies you customize to help users know if fresh, quality data is ready for use. Shine a light on who or what is using specific data to speed up collaboration or reduce disruption when changes happen. Data modeling. Data preparation. Data integration. Orchestration.

Tableau 98

Tableau Data Quality Analytics Analytics 98

phData

AUGUST 16, 2023

In the era of data modernization, organizations face the challenge of managing vast volumes of data while ensuring data integrity, scalability, and agility. What is a Data Vault Architecture? It is agile, scalable, no pre-modeling required, and well-suited for fluid designs. Using dbt is one of the best choices.

Data Warehouse 52

Data Warehouse Data Governance SQL Data Models 52