Introduction
“Data science” has quickly become the buzzword of the tech industry. It’s the process of using data to solve business problems — and it’s growing in popularity. Data science is an impressive discipline, but there are a few things that casual observers might not know about it. In this article, we’ll discuss what data visualization and analytics are, how they contribute to big data projects, and why they’re becoming so popular among businesses today.”
Data Visualization
Data visualization is the process of creating human-readable representations of abstract data. Data visualization can be used for many purposes, including the following:
- Explaining complex data
- Presenting information in a more understandable way (visualization can help people make decisions)
Analytics
Analytics is the process of transforming raw data into actionable insights. It’s a very broad term, but in general analytics can be used to measure and improve business processes, predict trends and outcomes, or make decisions based on data analysis.
It’s also used in sports where teams use analytics to analyze their opponents’ strengths and weaknesses. This helps them come up with strategies for winning games or matches. Analytics has been around for decades; however it has seen an increased usage over time due to better technology as well as more people being interested in data science careers (or just generally wanting more information about what’s happening around them).
An End To The Internet Of Things?
The Internet of Things (IoT) is the network of physical objects, vehicles, buildings and other items embedded with electronics, software, sensors and network connectivity that enables these objects to collect and exchange data. IoT can be used in smart homes, smart cities and manufacturing processes.
The concept of IoT was first introduced by Kevin Ashton in 1999 who saw it as a system where electronic devices such as sensors could be linked via the internet and would communicate with each other through standard protocols like HTTP/IP or Bluetooth. With this vision in mind he founded the Auto-ID Center at MIT which brought together various companies interested in developing standards for automatic identification technology (AIT).
Data Visualization And Analytics
Data visualization is a form of communication. It’s also a form of analysis. It helps you make sense of the data, and it can be used as a tool for analysis or decision making.
It’s not just about making pretty pictures; data visualizations tell stories based on your data, helping you understand what happened and why it happened that way.
Conclusion
Data Visualization And Analytics are two of the most important concepts in Business Intelligence. They allow you to make better decisions, by providing an understanding of the data that is available. With this knowledge, we can predict future trends and plan accordingly.
