Remove Dashboards Remove Data Warehouse Remove Modeling Remove Online Analytical Processing
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Data Model Development Using Jinja

Sisense

Every aspect of analytics is powered by a data model. A data model presents a “single source of truth” that all analytics queries are based on, from internal reports and insights embedded into applications to the data underlying AI algorithms and much more. Data modeling organizes and transforms data.

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How to Build a Performant Data Warehouse in Redshift

Sisense

This blog is intended to give an overview of the considerations you’ll want to make as you build your Redshift data warehouse to ensure you are getting the optimal performance. First, we’ll dive into the two types of databases: OLAP (Online Analytical Processing) and OLTP (Online Transaction Processing).

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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. Power BI provides users with some very nice dashboarding and reporting capabilities. OLAP Cubes vs. Tabular Models. The first is an OLAP model.

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

AWS Big Data

Data lakes are more focused around storing and maintaining all the data in an organization in one place. And unlike data warehouses, which are primarily analytical stores, a data hub is a combination of all types of repositories—analytical, transactional, operational, reference, and data I/O services, along with governance processes.

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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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Business Intelligence Solutions: Every Thing You Need to Know

FineReport

Technicals such as data warehouse, online analytical processing (OLAP) tools, and data mining are often binding. On the opposite, it is more of a comprehensive application of data warehouse, OLAP, data mining, and so forth. Predictive analytics and modeling.

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The Enterprise AI Revolution Starts with BI

Jet Global

Many of the features frequently attributed to AI in business, such as automation, analytics, and data modeling aren’t actually features of AI at all. Which problems do disparate data points speak to? Enter data warehousing. So how is the data extracted?