Basic Visualizations

What are the essential views you can use in Qlik?


This  is the pain page of the company / department, which allows the visualization of most important informationMost of the time it does NOT need a scroll to explain “how are we doing?”, the essential can be grasped at a glance.

The dashboards of Qlik can be compared, in terms of functionality, with the dashboard of an aircraft (both provide essential data for getting to your destination in optimal safety and efficiency).

The common dashboards usually focus on comparative percentage indicators between an indicator (measure) calculated for a recent period and a relevant reference (previous or targeted), but are often combined with absolute values, beyond percentages. In many cases, color codes are also used to highlight specific types of situations (generally red for negative impact and green for positive impact).

Below you will find possible visualizations options for a Dashboard:

Visualization elements from Dashboard pages

Gauge Presentations allow visualization of some essential numbers, type execution percentage as a general (usually compared to an earlier period or to a budgeted/ planned target). 

KPI presentations allow the visualization of some essential numbers, generally of the absolute value type, possibly with the visualization of the reference values ​​and with the signaling of the meaning and the positive or negative position of the variation towards the reference (references).


The Dashboard Overview can be completed with relevant additional details, related to the evolution of the indicators over time (using a line-chart), or other views (tops, pies, blockchart).

You can create a dedicated Dashboard for each department of an organization, but we recommend the generalizing approach, much more efficient. Additional navigation elements allow the analysis to be lowered to lower hierarchical levels.


LINE GRAPH (TIMELINE) – is a graphical visualization of the variation of one or more parameters over time. Qlik allows several types of analyzes of these line charts, including comparative analyzes of developments.

It is also possible to offer in parallel evolutions of several indicators over time presented in adjacent objects, or to build more evaluated timeline mechanisms.



Timeline analytics in dedicated pages allow you to visualize multiple time perspectives. Line Chart and sometimes Bar Chart or even Waterfall are usually used. The common perspectives include at least 3 graphs and 2 pivot type tabular presentations.

The classic Timeline chart allows the identification of the variation of a numerical indicator (measure) according to a specific time dimension, which continuously covers a time horizon.

Starting from the first graph presented, we usually derive a graph that highlights the evolution of the distribution over time of an indicator, with the breakdown by an important non-temporal dimension.

We recommend avoiding non-temporal dimensions with too many entities, in order to be able to highlight this information in an intelligible way.


The Timeline Analysis Chart with seasonality allows the identification of the variation of a numerical indicator (measured by a specific time dimension, superimposed over several years.

Adding pivotal and/ or even simple table layouts can help in many situations, but it is very important that the first visualization option to be the chart and then the breakdown tables.


The visualization of some tops (usually descending) allows you to identify the ranking and relative performance of each entity in the dimensional column (City) in relation to a particular measure (Sales Value, in RON).

When there are too many entities to be included in the top objects, there is the option to maximize the object to full screen. You can also use the scroll option inside the visualization object. In Qlik Sense there is also the thumbnail scroll option, highlighted above in the right side.


Usually, the TOP charts are combined with “pie charts” ….


… and/ or with block-chart or treeview.


Dynamic objects allow a larger number of analyzes to be encapsulated in a single object. With this approach, a single object can contain, simultaneously, tens, or hundreds, or even thousands of visualization variants for which the development time and cost in the interface could become huge.

For instance, even for a very simple Bar Chart object with Descending Tops, if it is defined to offer, at the user’s choice, directly in the interface, at the time of consuming the analysis.

any relevant non-temporal dimension (usually there are at least 5-6 such dimensions in less sophisticated companies, but it can also reach 20 or more, in the case of companies with high complexity.
any relevant measure in the context (usually again a few 4-5 measures can be quickly exceeded, but even here you can reach an impressive number, of the order of dozens of variants, relatively quickly).
if we talk about value analyzes, measured in money, often the analyzes are done in several currencies, at least in RON and EUR, again at the user’s choice, directly in the interface.

Putting these variants together, even in minimal variants, we obtain in a single object a set of options of 5 measures x 2 coins x 5 dimensions = 50 different variants of analysis (and this without considering any filtering option on a subset of data in the report generation).

Examples of common measures included in the circular option (with alternatives):

  • sale quantity
  • sale value at price list
  • discount value
  • net sale value
  • commercial margin
  • granted discount percentage
  • commercial margin percentage



All studies of the use of managerial analysis interfaces have shown that graphical visualization is more efficient than tabular representation in highlighting the essential factors of a business.

The explanation: The human mind contains a much more advanced image processor than its digital processor, which is applied in a more abstract plan.

For situations where the graphic objects cannot contain enough details, we recommend the use of mixed objects, in which the tables integrate graphic content into the table cells. Graphics, including MiniCharts and Trellis provide information at a digestible level still visually, not just numerically.


SCATTER CLOUD ANALYSIS is used to visualize the simultaneous spread of a set of 2-3-4 measures in the population of analyzed entities (1 dimension of analysis).

Such an analysis may highlight:

  • similar phenomena by grouping (clustering) the points,


  • the belonging of the points to certain curves that may suggest possible correlations between the analyzed measures,


  • the lack of population of certain areas of analysis may suggest phenomenological limitations.

Una dintre cele mai valoroase reprezentări economice de împrăștiere este cea în care pe axa orizontală este reprezentată vânzarea valorica, iar pe cea verticală marja procentuală. (În dreapta sus sunt găinile de aur !)

In the example above, you can dynamically choose, directly in the interface, for the horizontal, vertical, and perpendicular axes (disk size) from several represented measures. Staining can be associated with a 4th measure.


More details about waterfall visualization and factor analysis (also called cause-effect analysis) can be found here.


It is a graphical representation that helps you visually understand the cumulative effects of sets of positive and negative values, which change the results of important indicators.

In the next image you can visualize a combined presentation of the logic of factor analysis with the presentation of Waterfall, which highlights the way of how each factor brings:

  • a plus (green)
  • or a minus (red)

to the final result, the one to the right of the graph.



This kind of analysis can also be used as a GeoMarketing tool, which allows the identification of areas that are insufficiently exploited commercially or with operational problems. In the example below, you can choose from several measures represented: Sales, Sales per thousand inhabitants, Number of customers or Number of transactions or deliveries.

Zonal analyzes can be performed at any level for which there are data to substantiate the visualization.

Geo-spatial analyzes can also aim, going beyond the marketing sphere, moving towards operational analysis, visualizing the stocks available in each targeted area, possibly correlated with the sales volume in the same area, or even analyzing, per product, in areas where it was sold or in areas where it remained in stock.

Qlik geospatial analyzes also allow the overlapping of the above representations, or the addition of visual route information and/ or other quantitative or qualitative information valid for geographic point pairings.

In the above examples are presented a view by counties and another by locality (above the color intensity is associated with the variation of a measure, and below are 2 associated measures, one circle size, and one color intensity, respectively).


For most of the above objects there are also complex variants, in which the user can choose, on the spot, between several measures and several dimensions. 

This material aims to understand the basic concepts in the views offered by a BI solution, efficiency, time saving and accelerated analysis speed being immediate benefits.


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