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

As a data analyst, you need to be familiar with a variety of data analysis techniques and tools to effectively analyze data. One of these tools is aggregate functions in QlikView. In this article, we’ll take a closer look at aggregate functions, what they are, and why they’re so important for data analysts.

What are Aggregate Functions in QlikView?

Aggregate functions in QlikView are functions that allow you to perform calculations on data in a set or group. These functions are used to summarize data, and they allow you to see patterns and trends in your data. Some of the most common aggregate functions in QlikView include SUM, AVG, MIN, MAX, and COUNT.

Why are Aggregate Functions Important for Data Analysts?

Aggregate functions are important for data analysts because they allow you to quickly and easily summarize data. This is useful when you have large datasets, and you want to see patterns and trends in your data without having to go through the data in detail.

Aggregate functions also make it easier to analyze data over time. For example, if you have a dataset with sales data over time, you can use aggregate functions to see trends in sales over time. This makes it easier to make decisions based on the data, and to see how your business is performing over time.

How to Use Aggregate Functions in QlikView?

To use aggregate functions in QlikView, you need to use the QlikView Desktop. This is a graphical user interface that allows you to create, edit, and manage your QlikView documents.

To use aggregate functions, you simply need to write a formula that includes the aggregate function you want to use. For example, if you want to see the sum of sales amounts, you can write a formula like “SUM(SalesAmount)”.

You can also use aggregate functions in combination with other functions, such as IntervalMatch. For example, if you want to see the sum of sales amounts for a specific date range, you can write a formula like “SUM(IF(OrderDate >= ’01/01/2022′ AND OrderDate <= ’12/31/2022′, SalesAmount))”.

Conclusion

In conclusion, aggregate functions are an important tool for data analysts using QlikView. They allow you to quickly and easily summarize data, and they make it easier to analyze data over time. Understanding how to use aggregate functions in QlikView is an important part of becoming a successful data analyst. Whether you’re a beginner or an experienced data analyst, taking the time to learn about aggregate functions and how to use them in QlikView will help you to become more efficient and effective in your data analysis tasks.

# QlikView for Data Analyst – QlikView – Aggregate Functions

Taking too long?

| Open in new tab

# 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

# 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!