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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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Powerful Video Summaries, Powered by AI

Timo Elliott

He explains that automation and innovation have become critical as the world experiences supply chain disruptions, inflation, extreme weather events, worker shortages, and uncertainty. He focuses on three big opportunities: faster innovation, empowering business people, and moving from analytics to action.

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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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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.

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Cloudera + Hortonworks, from the Edge to AI

Cloudera

The tremendous growth in both unstructured and structured data overwhelms traditional data warehouses. We are both convinced that a scale-out, shared-nothing architecture — the foundation of Hadoop — is essential for IoT, data warehousing and ML. We have each innovated separately in those areas.

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Topics to watch at the Strata Data Conference in New York 2019

O'Reilly on Data

Increasingly, the term “data engineering” is synonymous with the practice of creating data pipelines, usually by hand. In quite another respect, however, modern data engineering has evolved to support a range of scenarios that simply were not imaginable 40 years ago. Different kinds of sensors generate different types of data.

IoT 20
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Why Construction Businesses Should Track KPIs to Conquer Economic Uncertainty

Jet Global

Due to the Infrastructure Investment and Jobs Act of 2022 in the United States, nonresidential construction is expected to continue expanding despite expected uncertainty in 2023. Get a Demo See how companies are getting live data from their ERP into Excel, and closing their books 4 days faster every month. trillion worldwide by 2030.