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In QlikView Admin, we generally use bar charts, line charts, combo charts, scatter charts, grid charts, etc.
Mostly used in aggregated functions like sum (year), avg, max, min, etc., set analysis is used to define a set (or a group) of data values.
In the trellis chart, we can create an array of charts based on the first dimension. It is basically a grid of small charts or a repetition of charts. Bitmap charts can also be made up of the trellis display.
In QlikView, with the help of a mini chart, we can set the type of modes, instead of values, in the table mode. We can also set colors for the chart.
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A pivot table is better at the time of grouping. We can also show a pivot table like a cross table, which is a beneficial feature. However, there is a disadvantage with pivot tables, i.e., if we have to sort a pivot table, then we have to sort it first according to the first dimension, then to the next.
A bar graph can be used for this purpose.
A straight table is much better at the time of sorting when compared to the pivot table as we can sort the former according to any column as per our choice. However, it is not good for the grouping purpose.
In a bar chart, we can use only two dimensions.
Gauge chart and list box have only expression and no dimension.
We can use macros for various purposes, such as reloading the application and creating an object.
Layers are basically set on sheet object properties in the layout tab, where there are options such as Bottom, Top, and Normal, respective to the numbers −1, 0, and 1.
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Dimensions allow data examination from various perspectives.
Star schema is the simplest form of a dimensional model, in which data is pre-arranged into facts and dimensions.
A snowflake schema is a different form of the star schema. A snowflake schema is used to improve the presentation of particular queries.
IntervalMatch prefixes with the load statement that is used for connecting different numeric values to one or more numeric intervals.
The IntervalMatch() function is used to generate data buckets of different sizes.
A container object is used to keep multiple charts. We can use a container object to keep many charts in the same box.
The extended IntervalMatch() function is used for Slowly Changing Dimensions.
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Container object, granular chart dimension control, actions like clear filed, metadata, etc. are some of the new features in QV 11.
Join is used to convert the given data, and whenever we use joins for converting data it is known as data merging. It has many types: a. Left join b. Right join c. Inner join, etc.
Left join specifies that the join between two tables should be left join; it uses before the word ‘join’. The resulting table only contains the combination among two tables with the full dataset from the first table. When we have more than one common field between two or more tables, then we have synthetic keys.
Right join specifies that the join between the two tables should be right join; it uses before the word ‘join’. The resulting table only contains the combination among two tables with the full dataset from the second table.
Inner join specifies that the join between the two tables should be inner join. The resulting table should contain the full dataset from both tables.
Modifiers deal with the Fields name.
The above code returns the sales for the current selection, but the selection in ‘Region’ is removed.
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QlikView stores data in QVD as QVD has data compression capability. QlikView has better performance than other BI tools because of its memory analytics approach.
Binary Load can be used only for one application, i.e., we can only read data from one QVW application. Moreover, set scripts is also a restriction.
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Optimized load is much faster and preferable especially for large sets of data. It is possible if no transformation is made at the time of load and no filtering is done.
Keep and Join do the same functions, but keep creates two tables whereas join merges two tables to create one table. Keep is used before the load or select statement.
A synthetic key is the key used when two or more tables consist of more than one common column among them.
Incremental load is nothing but loading new or changed records from the database. With the help of QVD files, we can use incremental load.
Resident load is a part of loading data in the QlikView application. It is used for loading the data in tables, which is already loaded in the Qlikview application.
A QV application can be optimized by creating QVDs for data. When the complete QVW application is changed into a QVD, then this QVD will be stored in the RAM.
Mapping load is used to create the mapping table that can be used for replacing field values and field names.
Apply map is used to add fields to tables with the help of other tables. It can be used as a join.
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Concatenation means a sequence of interconnected things, i.e., any columns or rows that are related to each other can be connected through concatenation.
NoConcatenation prefix is used to force two identical tables as two separate internal tables.
The connect statement is used to establish a connection to the database with the help of an ODBC or an OLEDB interface.
Fact Constellation schema is a logical database structure of a data warehouse. It is designed with the help of a denormalized fact.
RDBMS stands for ‘Relational Database Management System.’ It arranges data into respective columns and rows.
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Every client needs a CAL to get connected with Qlikview Server. CALS are taken up with QlikView Server and tied up with the server serial number.
By this option, we can see a number of tables and related associations.
We can use ODBC, OLEDB, or SAP connectors as a kind of data connection.
We can load data from ODBC, OLEDB, or SAP connectors with the help of the select statement, and we can load files like Excel, Word, etc. by using the table syntax.
We use flat files, Excel files, QVDs, etc. as data.
QlikView is the Business Intelligence tool used by the University of St Andrews. With QlikView, data from different university systems are combined and presented in a single dashboard in an easy and understandable way.
QlikView dashboards at the University of St Andrews are built on the following principles:
As the name suggests, QlikView is a combination of ‘quick’ and ‘click,’ and its features make it intuitive and easy to use. Users can visualize data, search in multiple datasets, create ad-hoc reports, and view patterns and trends in data that may not be visible in other reports.
QlikView 11 brings new levels of capabilities and manageability to the QlikView Business Discovery platform. In this release, it has focused its investments on five value propositions:
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Business users can quickly gain new insights when analyzing their information in QlikView, with its new comparative analysis options. QlikView app developers can now create multiple selection states in a QlikView app; they can create graphs, tables, or sheets based on different selection sets.
QlikView 11 delivers mobile functionality for Apple iOS and Android tablets and smartphones. QlikView supports Android tablets when the following conditions are met:
Currently, HTML5 web apps support only Apple and Android handhelds because BlackBerry devices are older that do not fully support HTML5 (and many of them are having non-touch screens). QlikView doesn’t have a web-based solution for them as of now.
New optional settings within QlikView Management Console enable administrators to more effectively audit user interactions. Administrators can now audit QlikView usage not only at the system level (the entire QlikView Server) but down to the document level as well.
The key difference is in terms of the database used. While SAS is useful in the case of metadata and SPSS is good for analysis; QlikView offers quite a simple visualization that matches MS Excel filtering.
When comparing QlikView with the other two, it is the most user-friendly and the fastest in terms of generating diverse dashboards/templates.
In terms of calculations, advanced statistics options are limited in QlikView. For market research and analysis, SPSS has direct facility algorithms.
With the new annotations collaboration object, QlikView users can engage in threaded discussions with the QlikView content. A user can create notes associated with any QlikView object. Other users can then add their own commentary to create a threaded discussion.
Users can capture snapshots of their selections and include them in the discussion so that others can get back to the same place in the analysis when reviewing notes and comments. Also, QlikView captures the state of the object (current selections), as well as knows who has made each note and comment and when and how a decision was made.
QlikView offers the following features:
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Currently, I am doing QlikView course. This questions and answers will help me a lot when I am going to start facing the interview. Thanks to the intellipaat team.
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Really nice work and good questions. thanks for sharing, Please update with more server and publisher questions.
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