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Data Modeling 201 for the cloud: designing databases for data warehouses

erwin

Designing databases for data warehouses or data marts is intrinsically much different than designing for traditional OLTP systems. Accordingly, data modelers must embrace some new tricks when designing data warehouses and data marts. Figure 1: Pricing for a 4 TB data warehouse in AWS.

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Build an Amazon Redshift data warehouse using an Amazon DynamoDB single-table design

AWS Big Data

In traditional databases, we would model such applications using a normalized data model (entity-relation diagram). Deriving business insights by identifying year-on-year sales growth is an example of an online analytical processing (OLAP) query. These types of queries are suited for a data warehouse.

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Database vs. Data Warehouse: What’s the Difference?

Jet Global

Whether the reporting is being done by an end user, a data science team, or an AI algorithm, the future of your business depends on your ability to use data to drive better quality for your customers at a lower cost. So, when it comes to collecting, storing, and analyzing data, what is the right choice for your enterprise?

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Data Modeling 301 for the cloud: data lake and NoSQL data modeling and design

erwin

For NoSQL, data lakes, and data lake houses—data modeling of both structured and unstructured data is somewhat novel and thorny. This blog is an introduction to some advanced NoSQL and data lake database design techniques (while avoiding common pitfalls) is noteworthy. Data modeling basics.

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Master Your Power BI Environment with Tabular Models

Jet Global

As the Microsoft Dynamics ERP products transition to a cloud-first model, Microsoft has positioned Power BI as the future of business intelligence for its Dynamics family of products. OLAP Cubes vs. Tabular Models. Let’s begin with an overview of how data analytics works for most business applications.

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Navigating Data Entities, BYOD, and Data Lakes in Microsoft Dynamics

Jet Global

Consultants and developers familiar with the AX data model could query the database using any number of different tools, including a myriad of different report writers. Data entities are more secure and arguably easier to master than the relational database model, but one downside is there are lots of them! Data Lakes.

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How Aura from Unity revolutionized their big data pipeline with Amazon Redshift Serverless

AWS Big Data

Amazon Redshift is a recommended service for online analytical processing (OLAP) workloads such as cloud data warehouses, data marts, and other analytical data stores. Lastly, it’s billed in a pay-for-what-you-use model, and provisioning is straightforward and quick.