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Data Warehouse Interview Questions

Analytics Vidhya

source: svitla.com Introduction Before jumping to the data warehouse interview questions, let’s first understand the overview of a data warehouse. The data is then organized and structured […] The post Data Warehouse Interview Questions appeared first on Analytics Vidhya.

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Data Exchange with Modern Data Warehouse – Snowflake

Analytics Vidhya

Introduction Snowflake has long been a Cloud Data Warehouse. The organization completely changed the game with a unique architecture purpose-built for the cloud: enabling scalable storage and computing for data warehouse projects, all in a SQL database.

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Data Warehouse for the Beginners!

Analytics Vidhya

DHW, short for Data Warehouse, was presented first by great IBM researchers Barry Devlin and Paul […]. The post Data Warehouse for the Beginners! IBM is one name that easily enters the picture whenever long history in computer science is involved. appeared first on Analytics Vidhya.

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An Introduction to Data Warehouse

Analytics Vidhya

Introduction The following is an in-depth article explaining what data warehousing is as well as its types, characteristics, benefits, and disadvantages. What is a data warehouse? The post An Introduction to Data Warehouse appeared first on Analytics Vidhya. Why is […].

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Checklist Report: Preparing for the Next-Generation Cloud Data Architecture

Data architectures to support reporting, business intelligence, and analytics have evolved dramatically over the past 10 years.

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Building a Data Warehouse using Google BigQuery

Analytics Vidhya

Introduction Like many marketers, I’m sure your marketing data comes from multiple platforms, and you must juggle a mix of classified data to analyze and understand your customer journey. Source: cloud.google.com Classified data from different sources rarely communicate with […]. Pretty annoying, isn’t it?

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Data Warehouses: Basic Concepts for data enthusiasts

Analytics Vidhya

Introduction The purpose of a data warehouse is to combine multiple sources to generate different insights that help companies make better decisions and forecasting. It consists of historical and commutative data from single or multiple sources. Most data scientists, big data analysts, and business […].

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The Unexpected Cost of Data Copies

An organization’s data is copied for many reasons, namely ingesting datasets into data warehouses, creating performance-optimized copies, and building BI extracts for analysis.

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The Next-Generation Cloud Data Lake: An Open, No-Copy Data Architecture

However, they often struggle with increasingly larger data volumes, reverting back to bottlenecking data access to manage large numbers of data engineering requests and rising data warehousing costs. This new open data architecture is built to maximize data access with minimal data movement and no data copies.

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Top Considerations for Building an Open Cloud Data Lake

The key prerequisites for meeting the needs of non-technical users while adhering to data governance policies. How cloud data lake engines enable a better balance between data warehouse investments versus those in the cloud data lake

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TCO Considerations of Using a Cloud Data Warehouse for BI and Analytics

Enterprises are pouring money into data management software – to the tune of $73 billion in 2020 – but are seeing very little return on their data investments.