Remove Data Warehouse Remove Reporting Remove Technology Remove Uncertainty
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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. Data-driven DSS. These systems integrate storage and processing technologies for document retrieval and analysis.

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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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Banking on mainframe-led digital transformation for financial services

IBM Big Data Hub

Banks have the most to gain if they succeed (and the most to lose if they fail) at bringing their mainframe application and data estates up to modern standards of cloud-like flexibility, agility and innovation to meet customer demand. Atruvia AG is one of the world’s leading banking service technology vendors.

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Quantitative and Qualitative Data: A Vital Combination

Sisense

All descriptive statistics can be calculated using quantitative data. It’s analyzed through numerical comparisons and statistical inferences and is reported through statistical analyses. Consequently, using quantitative data, you can make strategic and tactical decisions that will benefit your organization and drive growth.

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New Thinking, Old Thinking and a Fairytale

Peter James Thomas

An obvious parallel in my world is to consider another business activity that reached peak popularity in the 2000s, Data Warehouse programmes [4]. Figures suggest that both BPR and Data Warehouse programmes have a failure rate of 60 – 70% [5]. King was a wise King, but now he was gripped with uncertainty.

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Data Science, Past & Future

Domino Data Lab

The data governance, however, is still pretty much over on the data warehouse. Toward the end of the 2000s is when you first started getting teams and industry, as Josh Willis was showing really brilliantly last night, you first started getting some teams identified as “data science” teams. You know what?

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Cloudera + Hortonworks, from the Edge to AI

Cloudera

They, too, saw the enormous potential for data at scale in the enterprise. They had proven their ability to build and deliver the technology at Yahoo. In the competitive world of data management, we can each look with respect at the success of the other. Forward-Looking Statements.