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process.science presents a new release
/in Business Analytics, Business Intelligence, Main Category, Process Mining, Sponsoring Partner Posts, Tools/by Editorial Staffprocess.science, specialist in the development of process mining plugins for BI systems, presents its upgraded version of their product ps4pbi. Process.science has added the following improvements to their plug-in for Microsoft Power BI. Identcal upgrades will soon also be released for ps4qlk, the corresponding plug-in for Qlik Sense.
Business Intelligence – 5 Tips for better Reporting & Visualization
/in Business Analytics, Business Intelligence, Insights, Main Category, Visualization/by Benjamin AunkoferData and BI Analysts often concentrate on learning a BI Tool, but the main thing to do is learn how to create good data visualization! BI reporting has become an […]
6 Ways to Optimize Your Database for Performance
/in Data Engineering/by Shannon FlynnKnowing how to optimize your organization’s database for maximum performance can lead to greater efficiency, productivity, and user satisfaction. While it may seem challenging at first, there are a few […]
CAP Theorem
/in Big Data, Business Intelligence, Data Engineering, Data Warehousing, Main Category/by Benjamin AunkoferUnderstanding databases for storing, updating and analyzing data requires the understanding of the CAP Theorem. This is the second article of the article series Data Warehousing Basics. Understanding NoSQL Databases […]
Graphical understanding of dynamic programming and the Bellman equation: taking a typical approach at first
/in Artificial Intelligence, Data Mining, Data Science, Deep Learning, Main Category/by Yasuto TamuraThis is the second article of the series My elaborate study notes on reinforcement learning. 1, Before getting down on business As the title of this article suggests, this article […]
ACID vs BASE Concepts
/in Big Data, Business Intelligence, Data Engineering, Data Warehousing, Database, Main Category/by Benjamin AunkoferUnderstanding databases for storing, updating and analyzing data requires the understanding of two concepts: ACID and BASE. This is the first article of the article series Data Warehousing Basics. The […]
Data Warehousing Basiscs
/in Big Data, Business Intelligence, Data Engineering, Data Migration, Data Warehousing, Database, ETL, Graph Database, InMemory, Main Category/by Benjamin AunkoferData Warehousing is applied Big Data Management and a key success factor in almost every company. Without a data warehouse, no company today can control its processes and make the […]
Why Do Companies Use Data Lakes?
/in Data Engineering, Data Warehousing/by Philip PileticModern enterprise-level computing operations have to capture a truly monumental amount of information every single hour. As the scale of data has grown almost exponentially over the years, so has […]
Understanding the “simplicity” of reinforcement learning: comprehensive tips to take the trouble out of RL
/in Artificial Intelligence, Data Science, Deep Learning, Machine Learning, Main Category/by Yasuto Tamura*I adjusted mathematical notations in this article as close as possible to “Reinforcement Learning:An Introduction.” This book by Sutton and Barto is said to be almost mandatory for those who […]
The Basics of Logistic Regression in Data Science
/in Data Science/by Shannon FlynnData science is a field that is growing by leaps and bounds. A couple decades ago, using a machine learning program to make predictions about datasets was the purview of […]