Remove Data Warehouse Remove Events Remove OLAP Remove Online Analytical Processing
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How gaming companies can use Amazon Redshift Serverless to build scalable analytical applications faster and easier

AWS Big Data

This post provides guidance on how to build scalable analytical solutions for gaming industry use cases using Amazon Redshift Serverless. This post also discusses the art of the possible with newer innovations in AWS services around streaming, machine learning (ML), data sharing, and serverless capabilities.

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Financial Intelligence vs. Business Intelligence: What’s the Difference?

Jet Global

There was always a delay between the events being recorded in financial systems (for example, the purchase of a product or service) and the ability to put that information in context and draw useful conclusions from it (for example, a weekly sales report). What Is Financial Intelligence? Today’s technology takes this evolution a step further.

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What Role Does Data Mining Play for Business Intelligence?

Jet Global

But data alone is not the answer—without a means to interact with the data and extract meaningful insight, it’s essentially useless. Business intelligence (BI) software can help by combining online analytical processing (OLAP), location intelligence, enterprise reporting, and more.

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Data Model Development Using Jinja

Sisense

Data warehouses have become intensely important in the modern business world. For many organizations, it’s not uncommon for all their data to be extracted, loaded unchanged into data warehouses, and then transformed via cleaning, merging, aggregation, etc. OLTP does not hold historical data, only current data.

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

AWS Big Data

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. Amazon Redshift is fully managed, scalable, cloud data warehouse.