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AzureML and CRISP-DM – a Framework to help the Business Intelligence professional move to AI

Jen Stirrup

If you’ve previously done work in SQL Server Analysis Services, you will know that Analysis Services had data mining functionality. Excel specialists may know that Excel also has a series of Data Mining Add-ins. This may also involve the generation of a preliminary plan designed to deliver the business objectives.

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Top 10 Data Innovation Trends During 2020

Rocket-Powered Data Science

The almost forgotten “orphan” in these architectures, Fog Computing (living between edge and cloud), is now moving to a more significant status in data and analytics architecture design. The key difference is this: monitoring is what you do, and observability is why you do it.

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Predictive Analytics: 4 Primary Aspects of Predictive Analytics

Smart Data Collective

Predictive analytics, sometimes referred to as big data analytics, relies on aspects of data mining as well as algorithms to develop predictive models. These predictive models can be used by enterprise marketers to more effectively develop predictions of future user behaviors based on the sourced historical data.

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Belcorp reimagines R&D with AI

CIO Business Intelligence

It’s worth noting that each initiative carried its own unique complexity, such as varying data sizes, data variety, statistical and computational models, and data mining processing requirements. Working with non-typical data presents us with a reality where encountering challenges is part of our daily operations.”

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IT Budgeting Practices for Data-Driven Companies

Smart Data Collective

While there are many benefits of big data technology, the steep price tag can’t be ignored. Companies need to appreciate the reality that they can drain their bank accounts on data analytics and data mining tools if they don’t budget properly. Look for inefficiencies that can be streamlined.

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Self-Service BI vs Traditional BI: What’s Next?

Alation

Slow requirements led technology leaders to demand proactive business intelligence. As Business Objects founder Bernard Liautaud notes in e-Business Intelligence: Turning Information Into Knowledge Into Profit (McGraw-Hill, 2001), the lack of ad hoc data access causes IT staff to drown in requests.

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A Guide To Starting A Career In Business Intelligence & The BI Skills You Need

datapine

S/He is responsible for providing cost-effective solutions to achieve business objectives, comparing operational progress against project development while assisting in planning budgets, forecasts, timelines, and developing reports on performance metrics. SAS BI: SAS can be considered the “mother” of all BI tools.