Qlikview is a very popular BI (Business Intelligence) tool and a leading Business discovery platform. This Qlikview tutorial gives complete information regarding Qlikview, right from its features, architecture, to its installation, work procedure, and its various other concepts.
Thriving in a world of information, we are pushed to handle the Big Data problems in our everyday work, at the office. Each enterprise faces its own problems, associated with data curation and analysis. The dull figures and numbers often saturate our brains with unsolved information. We need brighter and effective ways of data visualization and data handling.
Qlikview is one such tool that is programmed to perform data analysis, adopting better and more effective ways of data visualization. It is one of the leading BI platforms in the market. It is important to get acquainted with Qlikview and understand the effective differences between Qlikview and significant other peers so that we can adopt the right one for our requirements.
Qlikview is one of the fastest developing Business Intelligence and data visualization tools which aims to provide all enterprises (big and small) with data discovery and analysis.
Approximately 30,000 organizations across the world are happy customers of Qlikview. It is an easy application to load or deploy, with a very intuitive user interface. It helps you with better data visualization, by representing the relationship between data, using different colors. This enhances understanding and improves the degree of data analysis.
It is a patented technology for in-memory data processing, which aims to improve the rate of data processing. One of the highlights of Qlikview is that it compresses the data to 10% of its original size, enabling it to handle big data efficiently.
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Information is the king in the present world. For example, the shares and investors breathe on data. The weather forecast has its base in data. Facebook and Instagram live on data. Forget it. Everything runs on data. It is the data that is a boon and bane at the same time. The world is overflowing with data in all spheres. We need to efficiently manage it and utilize its metrics, to thrive well today.
Understanding and analyzing the whooping information day in, day out, through facts and numbers becomes a weak approach. We can hardly perceive and remember everything in numbers. We need charts, diagrams, graphs, and colors to dictate us through the data analysis. We will not only analyze data better through the visual medium, but we will also get the details that otherwise would go missing.
Qlikview is built to cater to the needs of handling big data with better visuals and adopting a better data analysis approach. It has many critical features that ensure complete user interaction and satisfaction while dealing with data.
Explore - QlikView Interview Questions |
There are a couple of powerful reasons that cause a wide range of acceptance of Qlikview across the companies. Some of them being: in-memory storage and effective data visualization.
There is no need for any data staging or to store it in any intermediate forms like cubes, hence enabling Qlikview to pull data extremely fast.
It also efficiently offers associative search, to enable data searching, both directly and indirectly. The combination of these advantages is seldom seen in other substantial competitors in the market.
All these attributes, together, enable meticulous data analysis along with faster data processing.
Some of the important features of Qlikview are given below:
Explore - Script Editor Features and Commands in QlikView |
Feature
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Tableau
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Qlikview
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Deployment Process
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Ease of Use
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Ease of Learning
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A simple drag and drop feature enables you to learn things quickly.
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You can learn to work with Qlikview easily, being guided by community support.
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Connectivity with other tools
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Mobility
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It is available on all the devices
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It is available on both web-based and mobile-based clients.
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Maintainability
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Easy to maintain
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Easy to maintain
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Security
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Explore - Table Viewer in QlikView |
The term Big Data is applied to the set of data where the size of the data is beyond the capability of the generally used software tools to manage, capture, and procedure the series of actions within the given time elapse.
According to the report provided by IDC, the content in the digital world will reach the heights of billion terabytes plus of data with which it becomes highly tough to be sustainable for managing and structuring the data for the concepts under the Big Data categorization as Volume, Velocity, and Variety. To avoid the big data capabilities, it ties up with the most flexible business intelligence platform Qlikview which turns the data into knowledge.
The most adorable features of Qlikview Big data is its flexibility to adapt to the data, technology associative in nature, it offers speed of thought, analytics within the self-service with the big data which was a critical and effective success for getting numerous organizations almost close to 24000 plus organizations reach and use to analyze their data with the help of Qlikview big data to enhance their business insights.
Big data detect new trends in the market and discovers fraud data or duplications in the data which became an added advantage to the big data. The other specific and most fascinating feature of Big data is its expansion towards its capability of data storage with which most of the business users such as managers of product, business, marketing, sales, advertising, game designing business, and customer service companies utilize the advanced features of Big data and got furnished by using it for making decisions which are mandatory on daily basis.
These Big data helped most of the businesses for a longer time in every aspect of their business needs and gained a deeper understanding of the structure of the big data and enjoyed comfort using it. But within no time, most organizations came up with the concept of extra and prominent capability self-service where the users can remix and re-engineer the big data to achieve new insights with plenty of dimensions available.
Where in real-time, the IT industry’s got the requirement for tremendous solutions with analytics that can handle the billions amount of data within a self-service manner. Then Qlikview came into the picture where it can merge with big data and can harvest the value of the big data. Henceforth, most IT and non-IT business users got attracted to the Qlikview analytics application which enables the business users to seamlessly maintain a million rows of data.
Explore - QlikView vs Qlik Sense |
In short, Big Data is referred to be as the size of data that matters more in every action performed in the data we have. Big Data is a term of data groups that are too large and complex. Big Data also refers to the use of predictive analysis, user behavior analysis, and definite other advanced data analytics methods which can be extracted from data. Big data has a challenge of its three dimensions: Volume, Variety, and Velocity.
As per 2015, Big data has a volume of 8 billion terabytes of data in the world; Variety types are Structured, Unstructured, and Semi-structured; Velocity means updates of machine status and streaming data, etc.,. it became a challenging task for businesses to achieve agile property when finding new insights for most emerging types of data and content.
Henceforth every business is running hard to harvest finding new solutions on daily basis support to ease their process of data storage, retrieval, and other performances on their data.
Qlikview along with big data is an admirable combination for finding more insights for the business users.:
Qlikview provides a great solution that is fast and powerful for the analysis of memory.
This API technique enables Qlik apps to create temporary applications or session applications or permanent applications based on the inputs provided.
Explore - QlikView Management API |
In few cases, we may require a large amount of data with high speed where Qlikview helps with its Query mode feature. By using we can get the data accordingly as per our need with fast speed and accurate results.
Qlikview is made of a number of components, which together function as a powerful BI tool. Below are the components, that makeup Qlikview.
The diagram below gives an overview of the architecture of the Qlikview.
There are two main segments in the Qlikview architecture. One is front-end and the other is back-end. The front-end is used to visualize the processed data, while the back-end provides the security and publication mechanism for the user's documents.
Explore - QlikView Architecture |
This is the front face for the Qlikview application, which is the interactive interface for the end-users. It is the singular, browser-based access point to view the user documents and other available data (which they are typically authorized to see). It is mainly made of the Qlikview Server, which is used to access the already created BI reports using the internet or intranet through URL. The user authentication and other security concerns are taken care of by the Qlikview Server.
The front-end is dependent on the resources offered by the infrastructure of the system.
The documents and reports created by the business users on the front-end are stored in the .qvw format, which on Windows is recognized as a standalone document. The user documents that you can see here are the ones created by the Qlikview Publisher.
The front end is the main interface, where the client-server communication happens.
The back-end is mainly made of the Qlikview Publisher and Qlikview Desktop. The Qlikview source documents, which are created by the Qlikview developer, are stored here. These source files have the script expressions required to pull the data from different data sources, like data warehouses, Microsoft Excel files, SAP, and Salesforce.com. The main function of loading and distribution is carried out by the Distribution Service.
The back-end relies on the resources from the infrastructure for clustering. Other services like SMTP and directory catalogs are also accessed by the back-end for various purposes.
The Qlikview Desktop is the wizard-driven environment, which is responsible to load and distribute data from its source. It is here that the drag-and-drop feature is implemented to create GUI layouts of the reports, which will be viewed in the front end.
Qlikview publisher is used for the distribution service. It is used to distribute the created .qvw files between the users and the servers. It performs the direct loading of the data from the data sources using the connection strings that are written in the .qvw files.
Visual cues are a handy (and perhaps simpler) way to create visual color alerts in tables. To create a visual cue, follow these steps:
Holding Ctrl pressed, click-and-drag the chart you just made to another area of the sheet. This will duplicate the object (and is a very useful trick). In the dimensions tab, delete the expression we used to set the background color.
By default users, selections in QlikView are stored in ‘$’. Alternate states make it possible to create additional selection states besides $.
Alternate states can help business users compare two different dimensions (whether they are related or unrelated). It performs a comparative analysis between sets of multiple data items. The developer creates multiple states within a Qlikview document and applies them to specific objects. Alternate state functionality is not accessible in the load script.
An analysis like this can be quite useful, particularly when combined with set analysis (described in the next section), because state settings can be used in an expression in conjunction with a set modifier. Alternate states refer to setting a state of a sheet or object, and sheets and objects with that assigned state will respond to each other. Objects of different assigned states will be disconnected from one another.
The steps for Desktop installation with necessary directions are explained below.
You need to first download the personal edition of the Qlikview. You can download it from the Official Qlikview Website. You have to fill in the details and register to be able to download it.
Once the file is downloaded, you have to agree to the License Agreement and select the target folder for installation to proceed.
The images for the installation process are given below.
Double click QlikViewDesktop_x64Setup.exe to open the language selection window. Clicking in English will present you with the following screen. Click Next.
Now accept the license agreement, by choosing the "I accept the terms in the license agreement" option. Then click on Next.
Now provide your details, such as your name and organization details, and click Next.
Choose the destination folder of your choice or retain the default one.
Now, choose the setup type as complete and click on Next.
This is the screen where you begin the process of installation. If you like to change any configuration, you can still choose to go back and change, else proceed with "Install"
Once, the installation is completed, the finish screen appears. Now, click on Finish.
You can now check on the installation, by going to the start menu and choosing the Qlikview icon. The screen shown below appears.
This ensures a successful Qlikview Desktop Application.
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This chapter deals with the basic operations, a user can perform in the Qlikview User Interface.
We will get acquainted with all the icons available on the screen and their respective functions.
Once the Qlikview Desktop Edition is installed, launch the application. The first screen presented to you is the getting started screen.
This is the first screen of the application, upon fresh installation. However, you can check the "Show start page when launching Qlikview" option, given at the bottom of the page, to go through this page, every time you launch the application.
The screen has two divisions. The left division contains the examples and getting started document. Ensure to scroll through the examples, to understand how QlikView works. The right division of the screen stores the "Recents" and "Favorites". The "Recents" will store the recently opened documents and the "Favorites" will consist of the documents that you want to visit frequently.
Upon closing the ‘Getting Started’ window, you will be presented with the menu window with all the available menu commands. They represent a complete set of features of Qlikview. Below are the details of each section of Menu commands.
This menu is used to perform two main functions:
The other important features of this menu are:
Edit menu has tools required to perform editing functions like copy, paste, cut, and format painter. Some of the important features of this Menu are:
This menu basically contains various view options. Some of the important functions of the menu are:
This is used to select and deselect the values in the sheet objects. It also helps in going back and forward, the logical statements of the sheets that are currently active. Other important features are:
The layout menu is used to add the sheets, select different sheet objects and rearrange them. Some of the important features of this menu are:
This menu allows the user to set user preferences, document properties, and Sheet properties. Some of the other associated functions are:
This menu helps to bookmark various documents for easier retrieval.
This menu allows you to create reports, edit existing reports, add or remove layouts to and from the reports and delete reports.
This is one of the important menu options in Qlikview. It lets you create charts and use the Qlikview management console. Some of the important features of this menu are:
This allows you to create new sheet objects and also modify the existing ones. The properties option displays various properties associated with a particular sheet object. Other important features of this menu are:
The Window menu helps in organizing different windows of the Qlikview application and the Help menu provides the Help documentation of Qlikview.
This topic covers details of data loading in Qlikview. The data can be loaded into Qlikview using multiple ways. It accepts data from various file formats like Excel, XML, etc. Following are the detailed explanations for data loading in Qlikview:
Qlikview can easily accept an excel file. You have to just open the Qlikview window, drag and drop the excel file into it. This will automatically create the sheet in the interface with excel data.
Select the Excel file: Open the main window of Qlikview and browse for the target excel sheet.
Select a Data Source: Upon dropping the excel file into the Qlikview interface, a file wizard appears. The file format "xlsx" is chosen by default in the wizard, as Qlikview auto-detects the file type. Under "Labels", choose Embedded Labels and click "Next step" to continue.
Load Script: The load script screen has the data loading script written. This is a SQL-like script and is editable.
Now, you will be prompted with a screen to save the file with the *.qvw extension. You need to choose a target location for this file to be saved. Click on "Next step" to proceed. Once the file is saved, the script gets executed to load the data into Qlikview.
Now, you can see the data loaded using Table Box Sheet Object.
Refer to the topic Creating Table Box, to see how to create Table Box and view the loaded data.
The data in the form of plain text, where fields and values are separated by comma, tab, or space is recognized as a valid file in Qlikview, for data loading.
For example, CSV (comma-separated values) files can be used for data loading.
You can load a CSV file into Qlikview from Data from file options available in the script editor under the File Menu. Alternatively, you can open a new Qlikview document and click Ctrl + E Keys to open the script editor window, as shown below. Now, choose your file from the appropriate path.
Upon opening the required CSV file, a window pops up as shown below. Under Labels choose Embedded Labels and click Finish.
The loading of the file happens through the load script. For delimited files, you can manually edit the file format in the script.
Now, you will be prompted with a screen to save the file with the *.qvw extension. You need to choose a target location for this file to be saved. Click on "Next step" to proceed. Once the file is saved, the script gets executed to load the data into Qlikview.
Now, you can see the data loaded using Table Box Sheet Object.
Refer to the topic Creating Table Box, to see how to create Table Box and view the loaded data.
The XML file format is most commonly used on worldwide webs, intranet, and elsewhere using the ASCII text. It is similar to HTML, where tags define the language. However, in HTML, tags define the structure, while in XML tags define the meaning of the data contained in the file.
XML stands for Extensible Markup Language (XML).
Qlikview can use XML files as a data source.
The process of loading data into Qlikview from an XML file is similar to delimited files.
To begin with, in the menu, click on Insert → Load Statement → Load from File. Now, choose the file you want to load.
On selecting the file you want to upload, a window opens up as shown below. Under the section, File Type, choose XML. The content of the XML file appears in the table with the headers. Now, click on Finish.
Once the file is loaded, the load script window appears. You can edit the script for any customization.
Now, you will be prompted with a screen to save the file with the *.qvw extension. You need to choose a target location for this file to be saved. Click on "Next step" to proceed. Once the file is saved, the script gets executed to load the data into Qlikview.
Now, you can see the data loaded using Table Box Sheet Object.
Refer to the topic Creating Table Box, to see how to create Table Box and view the loaded data.
Qlikview can process data from the web files present online. You have to specify the URL and Qlikview can fetch the HTML file and process it. Qlikview handles HTML files to analyze the structure of the file and extract the relevant data from it. To do this, choose the Web files option from the Data from files section under the Data tab of Script Editor, as shown below.
Once the web file is chosen, a window appears, with a text box, where you have to input the URL of the web file.
Upon choosing the Web file, the window given below will be seen. It has tables named @1, @2, @3, and so on. Choose the first table and click on Next, twice.
From the table selected, select the columns that are required. You can cross out the unimportant ones. Once done, click Finish.
Once the file is loaded, the load script window appears. You can edit the script for any customization.
Now, you will be prompted with a screen to save the file with *.qvw extension. You need to choose a target location for this file to be saved. Click on "Next step" to proceed. Once the file is saved, the script gets executed to load the data into Qlikview.
Now, you can see the data loaded using Table Box Sheet Object.
Refer to the topic Creating Table Box, to see how to create Table Box and view the loaded data.
Qlikview is configured to connect to the most popular databases like MySQL, SQL Server, Oracle, Postgres, etc. It can fetch tables and structures from the database and store the data in memory for future processing.
The process of connecting to a database includes creating an ODBC connection using DSN and fetching the data using DSN.
For this tutorial's sake, let us learn to connect to a MySQL database. We assume that you have the MySQL environment ready and installed. To create an ODBC DSN, follow these steps Creating ODBC DSN. Rename the DSN to mysqluserdsn or you can retain the default one.
For the tutorial's sake, we will use the inbuilt database of MySQL called "sakila".
Now, open a new Qlikview Document and open the script editor (Ctrl + E keys). Under the tab called "Data", locate a section called "Database". From the options available, choose ODBC and click Connect. This opens a window (shown below). Now, choose the DSN-created mysqluserdns and click Test Connection. The success message called the message Connection Test succeeded should appear.
Once the connection is successful, the screen given below appears. It shows the connection to DB in the main window.
Click Select in the above window, to get a list of tables and columns.
Once we click OK, you will get back to the window with a script for the selected table.
The data loaded in Qlikview needs to be permanently stored for future analysis. To do this, we need to store the file in .qvd format. Now, open the script and edit into the following code. Here the path is edited along with the name of the tables and the columns. Now, this will be saved in .qvw format.
Press Ctrl + R Keys to reload the .qvw file generated and click on Next in the chart wizard.
You will now see the chart with the data from the selected table.
The data can be loaded into Qlikview by typing or pasting data into it. This is one of the direct ways of loading data from the clipboard. This option is available in the script editor, under the Insert tab. This method of data loading is called Inline Data Loading.
Script Editor: To open through Inline Data loading, in Script Editor, navigate Insert → Load Statement → Load Inline.
On clicking on the above option, a window with a spreadsheet-like document opens. Here you can type in the data to copy-paste from the clipboard.
Note: the column header is created automatically.
Now, click on Finish.
The data in the above document is loaded into Qlikview through the loader script. This can be viewed on Script Editor.
Table Box Object: On creating the Table box sheet object, all the data loaded will be displayed. We see that this data is read from the Inline Data Load option.
Sometimes when you want to create a table, deriving data from an already existing table in the same script, you can use Resident Loading. This is the type of loading where, the data from an already existing table in RAM are processed by a script.
Note: Here the new table and the existing table must be present in the same script.
The picture given below is an example of the script of Resident Load.
This is a type of data loading, where a loaded statement takes column names from another load statement present in the same script. The load statement from which column names will be borrowed will be at the bottom of the editor window, while the data reading load statement will be placed at the top.
Load Script: The loaded script shown in the window is an example of Preceding Load. The script is loaded as Inline data and the max function is applied to one of the columns.
The load statement at the bottom makes the data available in Qlikview's memory, which can be used by the load statement at the top.
On creating the Table Box Sheet Object, the loaded data can be viewed.
With the increase in the number of data that the Qlikview processes, the time-taken increases, and the activity rate decreases. To deal with this issue, Qlikview will take up the updated or newly added records from the source. This process of data loading is called Incremental Load.
The process of identifying the new record or updated record is done using a sequential unique key or date-time stamp. These values have to flow from the source files to Qlikview's document.
One of the distinguishing features of Qlikview is to store massive data in compressed form. For any Qlikview document, you need not connect it to a data source and store it. The data will already be stored along with the layout of the document in .qvd format. QVD is a flat-file format with a .qvd extension. A QVD file stores data for one document in Qlikview and is created using the script editor of Qlikview.
Explore - Advantages of QVDs |
A Qlikview document can be stored in QVD format, using the STORE statement during the loading of the document. This creates a .qvd file in the same location as the document and will be separate from the QVW file, through which we create this.
A QVD file is loaded into a Qlikview document in a similar way as that of CSV, Excel, and delimited files. Click on the Open option under the File and select the required QVD file. Upon opening the file, you can select the columns, see the data and perform the required data transformation.
On clicking Finish, you will be presented with a window containing the script. You may want to edit this code. Upon doing changes, click OK.
Once OK is clicked, reload the document using Ctrl + R Keys. When the Window appears, choose Layout → New Sheet Objects → Table Box. A window with all the columns of the table appears. Select Add All. You may use Promote/Demote to perform a change in the order of columns. Click Finish.
You will now see the screen with the content of the QVD file.
Table Box is a Sheet object that displays the data in the tabular format. You can create a table box by Layout → New Sheet Object → Table Box.
Click Next to choose fields for Table Box, from the options available. Promote or Demote options can be used in re-arranging the fields.
Table Box Data
This completes the data loading process. Now, you can view the Table Box with the loaded data.
Every Qlikview document is made of a compulsory worksheet called Main. However, any number of additional sheets to the Qlikview Document.
Each Sheet can have multiple sheet objects, charts, and tables. The objects in a sheet can be re-arranged using Promote Sheet/Demote Sheet option and the sheet can be removed off, along with its objects using the Remove Sheet option.
The properties of Sheets include customizing the sheet with the title and colors. For example, right-click anywhere on the sheet and choose the Properties option to customize the following:
These are the data elements, embedded in the Sheets, which represent the data loaded in Qlikview's memory. Each Sheet object is attached to a data source with one or more its columns.
The above image shows the creation of Sheet Objects from the Layout Menu.
Sheets objects are arranged in a logical way in a sheet. Each object is associated with the other within a sheet. Every object displays data from a data source.
Scripting is the method to operate on data in the Qlikview database. It is a very powerful feature, which allows controlling the data loading and data transformation functions in Qlikview. It uses many built features of Qlikview to handle data.
Scripting in Qlikview is done through the scripting interface or the editor, which is accessed from the File menu using Script Editor. A shortcut key is Ctrl + E Keys.
The Script Editor has a different menu from the main menu. Various features of this interface can be accessed using this menu. These features are given below:
The dashboard is the user interface where multiple fields are displayed to the user. The associative memory of Qlikview presents dynamic values in all sheet objects.
The dashboard is made up of various components. Some of them are:
There are various types of charts available in Qlikview to represent different kinds of data sets. A chart is a graphical representation of data in the form of a diagram. Different types of charts supported in Qlikview are:
Out of these charts, Pie charts and Bar charts are the most widely used charts. To create any chart, a few common steps are followed. Below is a brief description of the steps to create a chart in general.
Under this topic, let us learn about the List Box and Multi Box.
List box represents all the values associated with a field in Qlikview. If you highlight the value in the list, related values in the other sheet objects get highlighted. This feature of auto highlighting enables better visualization and analysis. It also helps to trace down the path among various objects in the sheet. The list box also allows a search.
A list Box can be created through the layout menu like this:
IntervalMatch is a special feature of Qlickview, which is used to match distinct numeric values to numeric intervals. It helps to analyze the planned events vs. the performed events.
The application of IntervalMatch can be seen below:
Documents are the files in the Qlikview that contain everything used for proper data analysis and representation. It consists of sheets, variables, data models, source-data connection details, etc.
Proper information about Documents can be obtained through this:
Help → document Support Info. The picture given below shows a sample output.
Documents have a special feature in Qlikview, which is scheduling. A document can be scheduled to reload at desired intervals. This option is available under the Schedule tab of document properties.
The concept of the Qlikview Data Model is a very broad one. Qlikview provides its users, various methods to perfect their data model. Some of the key data model concepts are discussed below.
Many times while performing data analysis, data scientists would want some data that is generated programmatically and is not from any external data source. For example, a set of random numbers generated or the list of all the leap years. To address this need, Qlikview has come up with a feature called Autogenerate, which generates data automatically.
The picture given below is an example of the Autogenerate application.
A synthetic key is a unique key generated by Qlikview when there is an ambiguity to find a unique key between 2 tables. This scenario comes into the picture when the two tables have two or more fields in common. The associative memory of Qlikview detects this scenario and automatically creates another table to hold the value of the new key generated.
Dimensions and Measures are the fundamental entities in data analysis. Dimension can be defined as a descriptive field in the data set which represents a few discrete values. Measures can be defined as a numeric field, which calculates a specific value for each dimension.
This is used in data analysis in the following way. For example: if you want to analyze this: “what is the percentage change in the volume of sales for each quarter?”
Here, each quarter represents the Dimensions, which is the name of the quarter. The percentage change in volume describes the Measures, which is a computation of value with respect to each value in the dimension.
In Qlikview, the dimensions and measures can be applied to tables and charts.
A star schema data model denotes a case where multiple dimensions are linked to a single fact table. In bigger (higher) models, multiple fact tables can be linked with multiple dimensions and other fact tables. The basic advantage of this data model lies in faster query processing and reducing the number of joins among tables.
The fact table usually contains data, which are Measures, having numeric values. All the calculations will be performed on the fields in the fact table.
The unique keys in the Dimension tables are used to map to the fact table, where the key will usually have the same field name. Hence, the fact table contains the keys from the Dimensions table and forms a concatenated primary key, which will be used in various queries.
Data analysis is one of the most important functionalities of Qlikview. There are many tools used to perform data analysis in Qlikview. Some of them are described below.
Joins are performed to combine data from two data sets into one, depending on a certain condition. Only the column and row values that satisfy the condition are filtered into the output. The joins in the Qlikview function in the same way as the joins in the SQL.
The joins are written in the scripts and employed on the data set to perform the required operation on the data.
Let us see different types of joins performed in Qlikview.
This Join fetches only the common rows between two tables.
This Join fetches all the rows of the left table and only the matching rows from the right table.
This Join fetches all the rows of the right table and only the matching rows from the left table.
It fetches all the rows from both tables.
In order to perform each of the joins,
Tables are used to arrange data in an orderly way. In Qlikview, tables help in a systematic data analysis, by presenting the data in an organized fashion. There are different types of tables available in Qlikview, for various situations. Some of them are discussed below:
While dealing with data, many times, we need to have tables transposed, where the columns become rows and vice versa. This is carried out by rolling up many columns together or repeating many values in a row to achieve the desired layout.
To perform cross tables,
These are simple tables with powerful features like column rearrangement, background color change, and sorting.
Pivot tables are regularly used in data analysis, to present the sum of values across many dimensions present in the data. Qlikview's Chart option allows you to create a Pivot Table, by choosing the relevant chart type.
As the name suggests, the mapping table is created by mapping the column values between two tables. It is also called the Lookup table. It is generally used to check for a particular value from some other table.
The set analysis feature of Qlikview is used to segregate data from different sheet objects into many sets and maintain some of the values unchanged. The default behavior of sheet objects in Qlikview lies in the associative property.
The set analysis creates an option to not associate some of the sheet objects with others. This helps in data filtering in some sheet objects and seeing the corresponding effect in the other, while the sheet object chosen as a different one, retains its own values.
This dissociation is possible, as a clone of the original data set is created and is worked on for set analysis.
In Qlikview, sometimes, we need to create a calendar reference object, which can be linked to any data set present in Qlikview's memory. This master calendar generated will supply the missing calendar data, which might be required by the data set for further data analysis.
Data transformation involves changing the original data in a data set to a different format. This includes adding, removing, or filtering the existing data. The data transformation is carried out by Qlikview using built-in functions. Some of them are discussed below:
This is an option for data transformation in Qlikview. It modifies the data in Qlikview's external memory which is loaded from an external source. It is the transformation step from ETL (Extract, Transform, Load) process, which can perform functions like deletion (Garbage), addition or fills, column, unwrap, rotate, etc. on the data.
The fill function is used to fill or add the values from existing fields into another field. In Qlikview, the fill button of the Fill tab gives the option to perform adding values into the empty cells. You can also specify fill conditions and strategize the filling of cells in Qlikview.
In the transformation wizard, select the type of transformation to Fill, to proceed with the transformation.
This is a type of data transformation, where, a new column is populated with the values from an existing column, upon meeting certain criteria. This criterion can be an expression, created as a part of the data transformation step.
A rotating table is a concept similar to the matrix transpose function. There are different ways of transposing a table, which would yield different results.
It can be useful in data modeling to swap different rows and columns. The rotating table function is similar to the cross tables in Qlikview, but rotating doesn’t allow for the aggregation of column data.
The option to rotate tables is available in the File Wizard, as shown in the picture below. Upon selecting the rotate tab, you can choose the option to transpose to get a transformed table. The result can be viewed in a table box.
Conclusion
Qlikview Tutorial is a data visualization and analysis tool that is built robustly to perform all the functions efficiently. Many use cases are considered to develop the software, which spans all the possible edge cases to perform thorough data visualization and analysis. Any enterprise can start using Qlikview for a better BI experience while dealing with data of any size.
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Vinod Kasipuri is a seasoned expert in data analytics, holding a master's degree in the field. With a passion for sharing knowledge, he leverages his extensive expertise to craft enlightening articles. Vinod's insightful writings empower readers to delve into the world of data analytics, demystifying complex concepts and offering valuable insights. Through his articles, he invites users to embark on a journey of discovery, equipping them with the skills and knowledge to excel in the realm of data analysis. Reach Vinod at LinkedIn.