10 Best Resources To Learn Data Science Online in 2022
Increasing technology and big data mean that organizations must leverage their data in order to deliver more powerful products and services to the world by analyzing that data and gaining insight, which is what the term "Data Science" means. You can jumpstart your career in Data Science by utilizing any of the resources listed above. Make sure you have the right resources and certifications. Now is the time to work in the data industry.
Mainframe Modernization: Making It Happen
Mainframe modernization is a major undertaking that presents a host of options for every organization. These options will vary depending on a number of factors, including business size, tenure, and industry. The following, however, are a few of the key considerations in modernization.
5 Best Practices for Performing Data Backup and Recovery
Data backup and recovery are critical for any organization in the digital age. The field of data science has developed advanced, secure, user-friendly backup and recovery technology over recent years. For anyone new to data backup and recovery, it can be challenging knowing where to start, especially when dealing with large quantities of data. There are some best practices in data backup and recovery that are beneficial for any user or organization. These tips will provide a jumping-off point for creating a customized data protection strategy.
process.science presents a new release
process.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.
Data Science mit Python - Aktuelle Buchempfehlungen
Als Dozent für Data Science und Python Programmierung für Hochschulen und Unternehmen (Mitarbeiter-Training) werde ich natürlich immer wieder zu Literatur-Empfehlungen gefragt. Aus aktuellem Anlass gebe ich hiermit eine Empfehlung von Büchern, die ich auch für meine Trainingserklärungen und -beispiele verwende oder einfach generell empfehlen kann.
Business Intelligence - 5 Tips for better Reporting & Visualization
Data 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…
6 Ways to Optimize Your Database for Performance
Knowing how to optimize your organization’s database for maximum performance can lead to greater efficiency, productivity,…
CAP Theorem
Understanding databases for storing, updating and analyzing data requires the understanding of the CAP Theorem. This is the…
Graphical understanding of dynamic programming and the Bellman equation: taking a typical approach at first
This is the second article of the series My elaborate study notes on reinforcement learning.
1, Before getting down on business
As…
ACID vs BASE Concepts
Understanding databases for storing, updating and analyzing data requires the understanding of two concepts: ACID and BASE.…
Data Warehousing Basiscs
/1 Comment/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 right decisions on a strategic level as there would be a lack of data transparency for all decision makers. Bigger comanies even have multiple data […]
Why Do Companies Use Data Lakes?
/0 Comments/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 the scale and complexity of data stores. Traditional databases couldn’t possibly keep up with the massive numbers of records that have to be created today, […]
Understanding the “simplicity” of reinforcement learning: comprehensive tips to take the trouble out of RL
/0 Comments/in Uncategorized /by Yasuto TamuraThis is the first article of my article series “My elaborate study notes on reinforcement learning.” *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 studying reinforcement learning. Also I tried to avoid as […]
The Basics of Logistic Regression in Data Science
/0 Comments/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 science fiction. Today, all you need is a computer, some solid programming, and a bit of patience, and you, too, can have your own digital […]
Process Mining mit Fluxicon Disco – Artikelserie
/0 Comments/in Business Analytics, Business Intelligence, Main Category, Process Mining, Tool Introduction, Tools /by Benjamin AunkoferDieser Artikel der Artikelserie Process Mining Tools beschäftigt sich mit dem Anbieter Fluxicon. Das im Jahr 2010 gegründete Unternehmen, bis heute geführt von den zwei Gründern Dr. Anne Rozinat und Dr. Christian W. Günther, die beide bei Prof. Wil van der Aalst in Eindhoven promovierten, sowie einem weiteren Mitarbeiter, ist eines der ersten Tool-Anbieter für Process […]
Why Your Data Science Team Needs Separate Testing, Validation & Training Sets
/0 Comments/in Data Science /by Philip PileticAutomated testing of machine learning models can help to dramatically reduce the amount of time and effort that your team has to dedicate to debugging them. Not applying these techniques properly, however, could potentially do a great deal of harm if the process is completely unmonitored and doesn’t adhere to a list of best practices. […]
My elaborate study notes on reinforcement learning
/0 Comments/in Artificial Intelligence, Data Science, Data Science Hack, Deep Learning, Machine Learning, Main Category, Use Cases /by Yasuto TamuraThis article is going to be composed of the following contents.
Understanding the “simplicity” of reinforcement learning: comprehensive tips to take the trouble out of RL
Graphical understanding of dynamic programming and the Bellman equation: taking a typical approach at first
AI Platforms – A Comprehensive Guide
/0 Comments/in Tool Introduction /by Jaimin DaveA comprehensive guide compiled to introduce readers to AI platforms, their types, and benefits. A concluding section to discuss AI platform selection strategy with Attri’s Best of Breed approach to build AI platforms. Don’t you think that this century is really fortunate? In my opinion, the answer is yes; we witnessed technological transformations and their […]
Predictive Maintenance – Konzept und Chancen
/0 Comments/in Uncategorized /by Georg Ungerböck(Maschinen)Zeit ist kostbar. Das trifft besonders auf produzierende Unternehmen zu. Denn hier gilt, jeder Stillstand einer Anlage kostet wertvolle Produktionskapazität. Stillstände einer Maschine lassen sich nicht 100%ig vermeiden, nur können sie mit dem passenden Predictive Maintenance Konzept (im weiteren Text als PdM abgekürzt) reduziert und besser planbar gemacht werden. Mit intelligenten Add-ons wie IoT Anbindung […]
How to Successfully Perform a Data Quality Assessment (DQA)
/0 Comments/in Business Analytics, Data Migration, Data Warehousing /by Shannon FlynnPeople generate 2.5 quintillion bytes of data every single day. That’s 1.7 megabytes generated every second for each of the 7.8 billion residents of Earth. A lot of that information is junk that somebody can easily discard, but just as much can prove to be vital. How do you tell the difference? According to industry […]