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Top 10 Analytics And Business Intelligence Trends For 2020

datapine

Often seen as the highest foe-friend of the human race in movies ( Skynet in Terminator, The Machines of Matrix or the Master Control Program of Tron), AI is not yet on the verge to destroy us, in spite the legit warnings of some reputed scientists and tech-entrepreneurs. 4) Predictive And Prescriptive Analytics Tools.

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Top 10 Analytics And Business Intelligence Buzzwords For 2020

datapine

Predictive & Prescriptive Analytics. Predictive Analytics: What could happen? We mentioned predictive analytics in our business intelligence trends article and we will stress it here as well since we find it extremely important for 2020. Prescriptive Analytics: What should we do? Cognitive Computing.

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Three Types of Actionable Business Analytics Not Called Predictive or Prescriptive

Rocket-Powered Data Science

Decades (at least) of business analytics writings have focused on the power, perspicacity, value, and validity in deploying predictive and prescriptive analytics for business forecasting and optimization, respectively. How do predictive and prescriptive analytics fit into this statistical framework?

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The Power of Graph Databases, Linked Data, and Graph Algorithms

Rocket-Powered Data Science

The book is awesome, an absolute must-have reference volume, and it is free (for now, downloadable from Neo4j ). Finally, in Chapter 8, the connection between graph algorithms and machine learning that was implicit throughout the book now becomes explicit. Graph Algorithms book. Your team will become graph heroes.

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Three Emerging Analytics Products Derived from Value-driven Data Innovation and Insights Discovery in the Enterprise

Rocket-Powered Data Science

If my explanation above is the correct interpretation of the high percentage, and if the statement refers to successfully deployed applications (i.e., One could say that sentinel analytics is more like unsupervised machine learning, while precursor analytics is more like supervised machine learning.

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Delivering Low-latency Analytics Products for Business Success

Rocket-Powered Data Science

The criticality of these synergies becomes obvious when we recognize analytics as the products (the outputs and deliverables) of the data science and machine learning activities that are applied to enterprise data (the inputs). A similarly high percentage of tabular data usage among data scientists was mentioned here.

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Data science vs. machine learning: What’s the difference?

IBM Big Data Hub

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is machine learning? This post will dive deeper into the nuances of each field.