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What are decision support systems? Sifting data for better business decisions

CIO Business Intelligence

The data sources used by a DSS could include relational data sources, cubes, data warehouses, electronic health records (EHRs), revenue projections, sales projections, and more. ERP dashboards. For example, they could be used to analyze sales in relation to location or weather. Clinical DSS. Sensitivity analysis models.

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Reporting Analytics vs. Financial Reporting: Is There a Difference?

Jet Global

Following on the sales example cited above, a user might choose to view sales of different product lines, with a secondary breakdown of those sales by region. Following on the sales example cited above, a user might choose to view sales of different product lines, with a secondary breakdown of those sales by region.

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What Role Does Data Mining Play for Business Intelligence?

Jet Global

Data drives everything in the business world, from manufacturing to supply chain logistics to retail sales to customer experience to post-sale marketing and beyond, data holds the secrets to making processes more efficient, production costs cheaper, profit margins higher and marketing campaigns more effective.

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Reporting System: Everything You Need to Know

FineReport

The data analysis part is responsible for extracting data from the data warehouse, using the query, OLAP, data mining to analyze data, and forming the data conclusion with data visualization. For instance, when you generate a sales report with the sales data stored in the CRM, the presentation layers will send API calls to the data layer.

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The Enterprise AI Revolution Starts with BI

Jet Global

Data warehouses are a means of taking data points from disparate touchpoints (such as point-of-sale, CRM, inventory, and warehouse management systems), standardizing the data collected, structuring it to extract necessary insights, and running analysis. Enter data warehousing. So how is the data extracted?

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The Future of AI in the Enterprise

Jet Global

Data warehouses are a means of taking data points from disparate touchpoints (such as point-of-sale, CRM, inventory, and warehouse management systems), standardizing the data collected, structuring it to extract necessary insights, and running analysis. Enter data warehousing. So how is the data extracted?

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CCPA 2020: Getting Your Data Landscape Ready

Octopai

With metadata queries, you can account for all appropriate inputs to your sales and inventory forecasts (among others). As a company’s data landscape grows and evolves, more computing “horsepower” is needed to perform the ETL and OLAP cube processing required to populate data warehouses and drive reports and dashboards.