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Building Data Warehouse Using Google Big Query

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction to Data Warehouse In today’s data-driven age, a large amount of data gets generated daily from various sources such as emails, e-commerce websites, healthcare, supply chain and logistics, transaction processing systems, etc.

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Snowflake: 6 Compelling Reasons to Modernize Your Data Warehouse

Corinium

Are you extracting maximum insights from your data? Data is the same. Conventional data warehouses can’t handle the volume, complexity, and variety of today’s data, and they can’t empower all your teams to access and analyze that data in real time. You know crude oil is more valuable when it’s processed.

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The Ultimate Guide to Modern Data Quality Management (DQM) For An Effective Data Quality Control Driven by The Right Metrics

datapine

1) What Is Data Quality Management? 4) Data Quality Best Practices. 5) How Do You Measure Data Quality? 6) Data Quality Metrics Examples. 7) Data Quality Control: Use Case. 8) The Consequences Of Bad Data Quality. 9) 3 Sources Of Low-Quality Data. 10) Data Quality Solutions: Key Attributes.

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Cloudera Data Warehouse outperforms Azure HDInsight in TPC-DS benchmark

Cloudera

Performance is one of the key, if not the most important deciding criterion, in choosing a Cloud Data Warehouse service. In today’s fast changing world, enterprises have to make data driven decisions quickly and for that they rely heavily on their data warehouse service. . benchmark.

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

In an effort to be data-driven, many organizations are looking to democratize data. 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.

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Modernizing the Data Warehouse: Challenges and Benefits

BI-Survey

Data warehousing is getting on in years. However, data warehousing and BI applications are only considered moderately successful. Advanced analytics and new ways of working with data also create new requirements that surpass the traditional concepts. Can the basic nature of the data be proactively improved?

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Migrate a petabyte-scale data warehouse from Actian Vectorwise to Amazon Redshift

AWS Big Data

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data.