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

CIO Business Intelligence

A DSS supports the management, operations, and planning levels of an organization in making better decisions by assessing the significance of uncertainties and the tradeoffs involved in making one decision over another. The size of the DSS database will vary based on need, from a small, standalone system to a large data warehouse.

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Perform time series forecasting using Amazon Redshift ML and Amazon Forecast

AWS Big Data

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Tens of thousands of customers use Amazon Redshift to process exabytes of data every day to power their analytics workloads. Forecasting acts as a planning tool to help enterprises prepare for the uncertainty that can occur in the future.

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Quantitative and Qualitative Data: A Vital Combination

Sisense

As quantitative data is always numeric, it’s relatively straightforward to put it in order, manage it, analyze it, visualize it, and do calculations with it. Spreadsheet software like Excel, Google Sheets, or traditional database management systems all mainly deal with quantitative data.

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Bridging the Gap: How ‘Data in Place’ and ‘Data in Use’ Define Complete Data Observability

DataKitchen

Bridging the Gap: How ‘Data in Place’ and ‘Data in Use’ Define Complete Data Observability In a world where 97% of data engineers report burnout and crisis mode seems to be the default setting for data teams, a Zen-like calm feels like an unattainable dream. What is Data in Use?

Testing 169
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Two Birds, One Stone: How to Get Better AX Reporting and Prepare for Future D365 Migration Today

Jet Global

Although Microsoft’s rollout of its two ERP cloud products (D365 F&SCM, and for smaller businesses, D365 Business Central) has been going on for some time, the current climate of economic uncertainty has prompted a lot of companies to hit the pause button on migration, choosing instead to stay the course with their existing Dynamics AX systems.

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Data Science, Past & Future

Domino Data Lab

He also really informed a lot of the early thinking about data visualization. It involved a lot of interesting work on something new that was data management. It involved a lot of work with applied math, some depth in statistics and visualization, and also a lot of communication skills. Then we roll out a decade later.

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Player retention is a strategic imperative for Casinos

BizAcuity

The data points related to users/players reside across multiple channels and platforms i.e. websites, apps, CRMs, Ad networks, and financial software. A data management strategy including business intelligence (BI) tools, data visualization software, and a data warehouse, maybe good ideas to consider.