QlikView for Data Analyst – QlikView – Architecture

Personal Career & Learning Guide for Data Analyst, Data Engineer and Data Scientist

QlikView is a powerful business intelligence and data visualization tool that is widely used by data analysts to access, analyze, and present data. The architecture of QlikView is designed to provide fast and efficient access to data, making it easy for data analysts to access, analyze, and present data in a clear and effective manner.

The architecture of QlikView can be broken down into three main components: the front-end, the back-end, and the data layer.

Front-end: The front-end is the user interface of QlikView and includes tools and functions that are used to access and analyze data. This includes a range of data visualization tools, such as charts, graphs, and tables, as well as a powerful search engine that makes it easy to find specific data points.

Back-end: The back-end of QlikView is responsible for storing and processing data. This includes a powerful data engine that can handle large amounts of data, as well as a range of data management and data processing tools that make it easy to manage data.

Data Layer: The data layer is the foundation of QlikView and includes a range of data sources, such as databases, spreadsheets, and cloud-based platforms. QlikView supports a wide variety of data sources, making it easy for data analysts to access the data they need to make informed decisions.

The architecture of QlikView is designed to provide fast and efficient access to data, making it easy for data analysts to access, analyze, and present data in a clear and effective manner. With QlikView, data analysts can access large amounts of data in a matter of seconds, making it easy to uncover valuable insights and make informed decisions based on their findings.

In conclusion, the architecture of QlikView is designed to provide fast and efficient access to data, making it easy for data analysts to access, analyze, and present data in a clear and effective manner. Whether you’re working with large amounts of data or just a small dataset, QlikView provides a wide range of data analysis and visualization tools that will help you uncover valuable insights and make informed decisions based on your findings.

QlikView for Data Analyst – QlikView – Architecture

Loader Loading...
EAD Logo Taking too long?

Reload Reload document
| Open Open in new tab

Download PDF [428.38 KB]

Personal Career & Learning Guide for Data Analyst, Data Engineer and Data Scientist

Applied Machine Learning & Data Science Projects and Coding Recipes for Beginners

A list of FREE programming examples together with eTutorials & eBooks @ SETScholars

95% Discount on “Projects & Recipes, tutorials, ebooks”

Projects and Coding Recipes, eTutorials and eBooks: The best All-in-One resources for Data Analyst, Data Scientist, Machine Learning Engineer and Software Developer

Topics included: Classification, Clustering, Regression, Forecasting, Algorithms, Data Structures, Data Analytics & Data Science, Deep Learning, Machine Learning, Programming Languages and Software Tools & Packages.
(Discount is valid for limited time only)

Disclaimer: The information and code presented within this recipe/tutorial is only for educational and coaching purposes for beginners and developers. Anyone can practice and apply the recipe/tutorial presented here, but the reader is taking full responsibility for his/her actions. The author (content curator) of this recipe (code / program) has made every effort to ensure the accuracy of the information was correct at time of publication. The author (content curator) does not assume and hereby disclaims any liability to any party for any loss, damage, or disruption caused by errors or omissions, whether such errors or omissions result from accident, negligence, or any other cause. The information presented here could also be found in public knowledge domains.

Learn by Coding: v-Tutorials on Applied Machine Learning and Data Science for Beginners

Please do not waste your valuable time by watching videos, rather use end-to-end (Python and R) recipes from Professional Data Scientists to practice coding, and land the most demandable jobs in the fields of Predictive analytics & AI (Machine Learning and Data Science).

The objective is to guide the developers & analysts to “Learn how to Code” for Applied AI using end-to-end coding solutions, and unlock the world of opportunities!