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

Jet Global

Data warehouses gained momentum back in the early 1990s as companies dealing with growing volumes of data were seeking ways to make analytics faster and more accessible. Online analytical processing (OLAP), which enabled users to quickly and easily view data along different dimensions, was coming of age. Data Lakes.

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How OLAP and AI can enable better business

IBM Big Data Hub

Online analytical processing (OLAP) database systems and artificial intelligence (AI) complement each other and can help enhance data analysis and decision-making when used in tandem. As AI techniques continue to evolve, innovative applications in the OLAP domain are anticipated.

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

erwin

The first and most important thing to recognize and understand is the new and radically different target environment that you are now designing a data model for. Star schema: a data modeling and database design paradigm for data warehouses and data lakes. Don’t obstruct the optimizer from seeing it’s a star schema.

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How gaming companies can use Amazon Redshift Serverless to build scalable analytical applications faster and easier

AWS Big Data

Flexible and easy to use – The solutions should provide less restrictive, easy-to-access, and ready-to-use data. They should also provide optimal performance with low or no tuning. A data hub contains data at multiple levels of granularity and is often not integrated. Data repositories represent the hub.

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Understanding Data Entities in Microsoft Dynamics 365

Jet Global

In the future, customers will be able to deploy Data Entities and replicate transactional tables in an Azure Data Lake. Jet Analytics provides a pre-built data warehouse , OLAP cubes , and tabular models with a platform for non-technical users to easily create their own reports in Excel or Power BI.

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Why Business Intelligence is Top of Mind for CFOs for 2022

Jet Global

The term “ business intelligence ” (BI) has been in common use for several decades now, referring initially to the OLAP systems that drew largely upon pre-processed information stored in data warehouses. This will ensure that you have the information you need to optimize your marketing spend.

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Accelerating revenue growth with real-time analytics: Poshmark’s journey

AWS Big Data

The AWS Data Lab offers accelerated, joint engineering engagements between customers and AWS technical resources to create tangible deliverables that accelerate data and analytics modernization initiatives. The data from the S3 data lake is used for batch processing and analytics through Amazon EMR and Amazon Redshift.