A Sales Dashboard with Pentaho Ctools - it-novum ENG... · List of Abbreviations 3 1. Introduction...

A Sales Dashboard with Pentaho CtoolsVisualizing SAP Data with Open Source Solutions

Whitepaper:

it-novum.com

List of Abbreviations 3

1. Introduction 4

2. The Sales Dashboard 5

2.1 Pentaho Ctools 7

2.1.1 Ctools Community Dashboard Editor 8

2.1.2 CDA Community Data Access 9

2.1.3 CCC Community Chart Components 9

3. The Data: SAP IDES 10

4. Dashboard best practices 10

4.1 Always use complete and consistent, high-quality data 10

4.2 Only display required key performance indicators (KPIs) 11

4.3 Graphs and charts are the dashboard‘s main components. 11

4.4 Don‘t overtax your screen real estate 11

4.5 High information density 12

4.6 Simple presentation of diagrams 12

4.7 Making comparisons 13

4.8 Use a unified design concept 13

4.9 Rules for diagrams 13

4.10 Rules for text and tables 14

5. Implementing the sales dashboard 15

5.1 Building the dashboard 16

5.2 Performance 18

5.3 Order volume by sales organization 19

5.4 Order volume by division 21

5.5 Order volume by sales channel 22

5.6 Customer KPIs 24

5.7 Market share for sales organizations 25

6. Conclusion 26

Contents

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it-novum Whitepaper | A Sales Dashboard with Pentaho Ctools

List of AbbreviationsCDA Community Data Access

CDE Community Dashboard Edition

CDF Community Dashboard Framework

CRM Customer Relationship Management

CSS Cascading Style Sheets

C-tools Community tools

ETL Extract – Transform - Load

HTML Hypertext Markup Language

IDES International Demonstration and Education System

KPI Key Performance Indicator

OLAP Online Analytical Processing

PDI Pentaho Data Integration

PUC Pentaho User Console

XML Extensible Markup Language

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1. IntroductionManagers and other decision makers in sales need information in a highly aggregated form so

that they can make the right decisions. A sales dashboard displays sales and customer data in a

brief, but comprehensive form, so that changes can be quickly detected (e.g. for closing rates).

To achieve this, however, the data must be processed and arranged in a sensible way.

A dashboard is normally a browser-based application that represents company data in a highly

aggregated form. To ensure that data is always easy to read and interpret, visual elements such

as charts and graphs are used. Ideally, a dashboard is a tool that can be used on a daily basis, so

that users can quickly obtain an overview of the status of a division or the entire company.

In this white paper, we will describe how to build a professional and easy-to-understand dash-

board for a company sales department drawing on SAP data. In the process, we will be relying

on several open source technologies. For staging, ETL (Extract - Transform - Load) and data

warehousing, we will be using the Pentaho 5 business intelligence suite. Ctools (Community

Tools) are open source extensions from Pentaho designed to simplify the creation of data visua-

lizations. Ctools are very well suited for quickly and easily creating compelling dashboards.

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2. The Sales DashboardThe sales dashboard we will be creating will be used by both sales managers and the board

of the fictitious company SAP IDES (International Demonstration and Education System). In

creating our dashboard, we will be following best practice for visually processing and displaying

data.

ETL Prozess

SAP IDES Vertriebsdaten

Data Warehouse

Cube Vertrieb

CRM, externe DatenSAP IDES Einkaufsdaten, Logistikdaten

Pentaho 5.0 Business Analytics C-Tools

Pentaho 5.0 Schema Workbench

Pentaho 5.0 Data Integration

Microsoft SQL Server 2008

Sales Dashboard für die Geschäftsleitung und Sales Manager von SAP IDES

optional

Dashboard

Datenquelle

Building the dashboard

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The dashboard and its data sources are structured and designed of as follows: We will be using

SAP IDES sales data as our data source for the dashboard. This will cover data from the years

1997 to 2013 that was populated by SAP in the SAP training system. The dashboard can, of

course, be expanded through the inclusion of external data (e.g. from the CRM system). The data

will be loaded into the data warehouse using an ETL (extract - transform - load) process.

The ETL process will be implemented in Pentaho Data Integration, the data integration compo-

nent of the Pentaho platform. Microsoft SQL Server 2008 will be used to store the actual data

used in the data warehouse.

We will be carrying out our analyses on the data warehouse using a multi-dimensional cube.

Pentaho 5 (Mondrian) Schema Workbench will be used for this function.

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2.1 Pentaho CtoolsPentaho already contains a module for creating dashboards – Pentaho Dashboard Designer

– however, this tool can only create simple dashboards that do not comply with best practice

principles for data visualization (see Section 4). For this reason, as of Version 5, Pentaho now

contains plug-ins that are intended for creating professional data visualizations and dashboards

for business management. These plug-ins are called Ctools („Community Tools“) and are deve-

loped by the Portuguese company Webdetails, which was bought by Pentaho in 2013. These are

open source programs, i.e., the individual source code for each tool is open (not proprietary) and

can be modified, if desired.

These Ctools consist of several components, of which the following modules are important for

our purposes:

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2.1.1 Ctools Community Dashboard EditorThe Community Dashboard Editor is an editor in the Pentaho User Console (PUC). The CDE is

used to create dashboards that appear as an HTML page displayed in the Pentaho User Console.

The CDE uses the tools Community Dashboard Framework, Community Chart Component and

Community Data Access, which are explained below. It should be borne in mind that the CDE is

just the interface that accesses the other community tools. That is its only function. The figure

below shows the interaction between the four Ctools:

Zusammenspiel der verschiedenen Ansichten Layout, Component und Data Source (Quelle: Webdetails)

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2.1.2 CDA Community Data AccessIn the CDE, data sources are managed and maintained in the Data Source view. In this view, the

data is designed and set up in the same way that it will ultimately be used in the dashboard. The

Community Data Access (CDA) module was developed as an interface to the underlying databa-

se. CDA has the great advantage that it can combine various queries (e.g. MDX with SQL), while

also providing very good performance. In order to view the CDA files (tables), a CDA viewer is

automatically installed along with the Ctools within the Pentaho User Console.

The CDA file stores the database to be contacted, additional parameters, and the DataAccess

(query) in an XML file. The file is created automatically by entering this data in the CDE Data

Source view.

2.1.3 CCC Community Chart ComponentsTo shorten the dashboard implementation process, CDE uses a supplied library of diagrams: the

Community Chart Components (CCC). Instead of using jFreeChart and jFlashChart, they use the

Protovis open source library, which covers all types of visualizations. As a result, it is possible to

use standard charts in a fairly simple way – the CCC charts can be accessed through the compo-

nent view of the CDE. The CDE also contains another component that, using JavaScript, can be

used to directly access other Protovis diagrams.

Some functions must be programmed manually with JavaScript within the CDE components

view. These include among other things click actions, formatting of values / legends / axes for

charts, post / pre-executions, and interactions with other diagrams.

CCC supports pie charts, bar graphs, line charts, dot charts as well as heat grids, bullet graphs

and waterfalls, box plots, and treemaps.

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3. The Data: SAP IDESWe have chosen the SAP IDES training system as the data source for our sales dashboard. SAP

IDES is provided free of charge for training purposes by SAP.

The fictional company IDES is a corporate group divided into several smaller companies and four

core areas: industry, retail, banking and services. In our example, we will only be dealing with

the industrial sector and the sales locations Milan, Rotterdam, and Frankfurt.

4. Dashboard best practicesMany dashboards are poorly designed. They contain too much data or too many diagrams and,

although they look good, are simply indecipherable. However, creating a good, concise dash-

board is not difficult. We have, therefore, compiled these guidelines for ensuring that dashboard

users always have the most important information available at their fingertips.

4.1 Always use complete and consistent, high-quality data

The dashboard should always draw on complete and consistent data. It is, therefore, important

to ensure that consistency and completeness are achieved during the ETL process. The correct

data must be extracted from the source systems and, during the subsequent transformation,

be adapted for the intended use. Care must also be taken to ensure that a completely error-free

data storage process is put in place. High-quality data can only be achieved by having a well-

maintained data source system. If necessary, time must be invested in making sure that your

data has been completely and correctly maintained before undertaking the dashboard creation

process.

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4.2 Only display required key performance indicators (KPIs)

Before developing a dashboard, it makes sense to consult the future users of the dashboard

about their requirements and how they intend to use this tool.

It is they (and not the IT department) who need to work with the dashboard. It may also be

useful to ask divisional and corporate managers about overall company requirements, because

corporate needs often differ from the needs of the dashboard users themselves. A conversation

with someone at management level can also reveal important KPIs that others may not have

been aware of. However, once the dashboard is in place, it should only contain the required

data, otherwise users can quickly feel overwhelmed or will not find it helpful.

4.3 Graphs and charts are the dashboard‘s main components.

Dashboards should display information in an instantly comprehensible manner. Graphics and

diagrams provide a concise overview much faster than text. If you have to use a lot of text to exp-

lain a diagram, you have chosen the wrong diagram – choose a different type of object to convey

your message.

Any dimensions of a diagram that are not displayed (i.e. text and not objects) should be clearly

and precisely formulated and, as far as possible, not contain any redundancies. Filler words such

as „for“ or „the“ should be avoided. It is advisable to include text in the chart itself and not as

a legend. If a situation cannot be depicted in a diagram, use a table. But be careful: Use tables

sparingly! After all, you‘re not writing a report.

4.4 Don‘t overtax your screen real estateIf users cannot digest something easily at first glance, they assume it to be of secondary impor-

tance. To avoid this, dashboards should be positioned at the side of the screen wherever pos-

sible. Under no circumstances should the user have to scroll to get to other diagrams or charts

as this makes comparisons with previous data difficult, if not impossible. Data that belongs

together contextually must never be presented in a fragmented fashion. The goal of a dashboard

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is to enable users to visually assess and monitor the facts of a situation at a glance. Because a

single page is often not sufficient to represent all important business processes, an overview of

all data should be displayed in the first instance.

Using zoom (drill down) and filter options, the user can display more detailed data as required.

4.5 High information densityDepending on the size of monitor, a single screen page is not a lot of space. Screen real estate

should, therefore, be used as efficiently as possible. This can be achieved using a high degree of

information density. In other words, any logos, pictures and pixels that do not contain any data

should be scrupulously avoided. Should any screen space remain after all relevant information

has been displayed, this space should not be filled up with additional diagrams. Some diagram

and chart types offer a higher information density (scatter charts or bar graphs) than others (pie

charts and speedometers) and should be preferred.

4.6 Simple presentation of diagramsDashboards charts and diagrams should provide a lot of information clearly. Unnecessary

decorative elements should be avoided. And even if they do look impressive, 3D effects make it

difficult to read and understand the information being presented. The same applies to frames,

shadow effects, ledger lines, too many axis values, wallpapers and animations. All these should

be omitted. For bar charts – which, by the way, are one of the most effective types of charts – the

bar markings themselves are sufficient for outlining and identifying the various structures. Any

additional coloring of the bars is not necessary. Color should always be used sparingly in gene-

ral, whether in charts and diagrams or in the dashboard. There are two good reasons for this: On

the one hand, human beings can only sustainably distinguish six colors and on the other, there

is a danger that individual values will inadvertently be highlighted and thereby draw the user‘s

attention to false or irrelevant items. For these reasons, only color-code information that has a

particular importance. Using exaggerated details for quantitative values is also not useful. Be

sure to use abbreviations and round off large values (e.g. 3.5 million instead of 3.578000 million).

White space is useful for grouping related content and allows you to dispense with using lines.

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4.7 Making comparisonsThe main purpose of diagrams is to illustrate comparisons. For instance, a turnover of three

million euros for a company is, in and of itself, not very meaningful. Only once a comparison has

been drawn with the previous year, or perhaps with a target value of four million euros, does the

context of the data have any real meaning. By drilling down to less densely populated levels it

is possible to show the cause for a high or low turnover, for example, by breaking down revenue

into sales channels. The main point or points of a diagram should be recognizable at a glance

without the need for an underlying report. When working with a time series, at least the last six

months or four quarters should be displayed.

4.8 Use a unified design conceptIf you are going to use dashboards in your company, try to do so using a unified design concept.

Also, make sure that users can work with the dashboards in a way that works across all depart-

ments. This means ensuring all elements are standardized and comparable issues are presented

in a uniform way (e.g. all values from the previous year are always displayed as a blue filled

circle, etc.). Using a variety of charts or diagrams will only serve to confuse users. The colors and

fonts used in dashboards should also be standardized with a uniform and consistent use of sizes

and scaling.

4.9 Rules for diagramsThere are certain rules for creating diagrams that should be followed if you want your users to

derive the greatest benefit from your dashboards:

и If at all possible, begin the scaling of any diagram at 0. Exceptions can be made for very

large trend values in line charts. That being said, the trend being represented should not be

distorted, so that the actual message being communicated stays clearly in focus. As a rule,

any information displayed graphically should be directly proportional to numeric sizes being

displayed.

и Displaying both axes of a diagram is unnecessary in most cases. Instead, only the axis that

displays quantitative values should be displayed.

и Also, redundant text elements such as „euro“ should be avoided throughout your diagrams.

и Special emphasis options such as color, shading and borders should only be used for dia-

gram elements that require the user‘s particular attention (e.g. using a red font to highlight a

decline in revenue).

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и Units of time, such as days, weeks, months, quarters, or years should be indicated on the

X-axis of diagrams.

и Attributes such as customers, suppliers or products should be represented on the Y-axis of

bar graphs (e.g. Gantt charts). It is also recommend that the bars displayed in a bar graph be

sorted in some sort of order. Using a random order will result in important information being

overlooked.

и A diagram should not display more than six dimensions. Otherwise, at first glance, it ap-

pears too complex and thus overwhelming. The bullet graph is the diagram with the highest

number of dimensions that can be easily understood. These can offer a nominal value, an

actual value, a categorization in three dimensions (good, fair, poor), and a quantitative value

(turnover).

4.10 Rules for text and tablesWhen inserting text into dashboards, the following rules should be applied:

и Numerical values are always aligned to the right.

и Headings and text are centered or aligned to the left, depending on your preference.

и Only sans-serif fonts should be used.

и Compacted numbers should not be represented too precisely („3m euros“ or „€3m“ is suffici-

ent).

и Number and date formats should be used consistently.

и Dates should be written out completely, if there is sufficient space to do so.

и For quarterly financial information, the year should always be added, if possible.

и Only text that should immediately catch the user‘s attention should be in bold.

и Redundant text should be avoided.

и Text should always be placed as close as possible to the diagram to which it pertains.

и Always try to use a dark font on a light-colored background.

When inserting tables, the following rules should be followed:

и Tables should only be used if a diagram cannot adequately represent the facts of the situati-

on.

и Columns and rows in diagrams should be represented by white space. If white space is not

possible for some reason, fine lines or light fill colors should be used.

и Time series and hierarchies should always be presented in columns. The lowest hierarchical

level should be displayed in rows. This simplifies the summing up of information.

и Columns are arranged in the following order: first, the definition of KPIs, then the quantitati-

ve key performance indicator, and finally the cumulative or percentage value.

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5. Implementing the sales dashboardIn the course of this chapter, we will first analyze the sales data from SAP IDES and select the

data we require. We will then create a data warehouse using Pentaho 5. The data warehouse

will consist of a staging layer and a data warehouse layer. The latter layer will be built as a star

schema. In addition, we have implemented a multi-dimensional cube of the data warehouse

using the Pentaho Schema Workbench. Finally, the CDE will implement the dashboard according

to our design rules above.

The diagram depicts the complete implementation:

Designing the dashboard implementation

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The data storage locations (servers) are shown on the right side of the diagram with the left side

showing each corresponding step.

As the data sources, we are using the IDES SAP sales data, which is stored on the SAP server.

We have extracted the required SAP tables using Pentaho Data Integration (PDI). An exact copy

of the tables is stored on the server sql02. The database IDES_Staging is administered using

Microsoft SQL Server Management Studio 2008. Next, we converted the tables from IDES_Sta-

ging into the correct format with the help of PDI and reduced them to the required columns.

Then, in the same process segment, we built a star schema, which is also stored on sql02. Next,

in Pentaho Schema Workbench (Mondrian) we created a cube. The cube and the dashboards are

stored on the server bi03 and constitute the basis for the dashboard we are creating.

5.1 Building the dashboardIn this section, we will apply our best practice points from earlier in this document to create a

best practice-compliant dashboard with Ctools.

The screenshot below shows the main page of the strategic IDES sales dashboard. The dash-

board offers a choice for the desired year (top of dashboard). The top pane of the chart shows

the sales performance for the IDES group. The middle diagram area is the interactive part of the

dashboard. It contains several bullet graphs displaying information about order volumes accor-

ding to sales organization, division and distribution channel. There is also a button next to the

heading, which offers the ability to drill down on less aggregated layers. And finally, customer

KPIs and market shares are displayed at the bottom of the dashboard.

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We have chosen to mainly use diagrams for the IDES sales dashboard. The diagrams were crea-

ted in line with the rules previously described above and have been kept very simple. In creating

these, we have tried to make sure that every visualization provides a maximum of information

without any data being unnecessarily highlighted. Some items are presented in tables and also

conform to the rules for table and graph design. Also, the screen has not been unnecessarily

expanded.

Items showing a lower level of detail will not be displayed on the overview page. Rather, these

are implemented as pop-ups. The pop-ups allow users to drill down on the cube. In the pop-ups

themselves, further drill down options to lower levels of the hierarchy are possible. Through the

frequent use of bullet graphs, bar graphs / charts, and avoiding ornamentation, a high degree of

information density is achieved.

By using uniform fonts and colors on the dashboard as a whole, a uniform design concept has

also been achieved. The use of bullet points and bar graphs provides a comparison value for

nearly every key figure or value visualized.

The IDES sales dashboard homepage

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5.2 PerformanceThe screenshot provides a more detailed view of the upper part of the dashboard. It shows the

company‘s sales performance, which represents the most important area of the dashboard. For

this reason, it has been placed in the upper third of the diagram. To the left, the key indicators

for order volume, profit and costs are displayed. They break down as follows:

и Sales volume x sales price = sales value (order volume)

и Sales volume x variable unit costs = variable costs (costs)

и Net sales (order volume) - variable costs (costs) = profit margin (profit)

To improve the legibility of the dashboard, we have used the terms order volume, profit and

costs.

To the right, next to the text description of the figures, the year‘s activity is displayed in the form

of a sparkline. The sparkline has a mouse-over effect that displays the per-month value of the

selected bar.

In the middle of the Performance section we have placed three bullet graphs that show the

current and target values for the given indicator. The target value is calculated based on the pre-

vious year‘s figures (previous year x 1.2). In addition, the charts have the categorization values

good, average and poor. The darkest shade of gray indicates poor. With regard to costs, we have

placed these on the right side, because costs, in contrast to the other two KPIs, are classified as

poor when they are high.

In the right-hand section, the actual and target values of the bullet graph can be seen again in ta-

bular form. This enables the user to see the exact value at a glance. We have also added a trend

arrow and the growth rate to the table.

By using bullet graphs in conjunction with a sparkline, we can achieve an extremely high degree

of information density. The current value of the index is compared to the target value and cate-

gorized. Using the sparkline, it is possible to obtain a comparison of the individual months of the

year. The bullet graph, sparkline, and table were implemented according to our best practices.

The performance section of the dashboard

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5.3 Order volume by sales organizationThe order volume by sales organization is represented in the middle of the dashboard overview

using a bullet graph. The bullet graphs show the volume of orders for the different sales organi-

zations (1000 = DE FFM, 2400 = IT Milan, 2500 = NL Rotterdam). In the interests of saving space,

the internal SAP numbers for the sales organizations are shown and not the actual names of

the organizations themselves. By having a view of the various sales organizations – including

drill-down options – it is possible to check the internal performance of the company‘s different

employee groups. The next figure shows the bullet graphs:

In this example, the target value of the bullet graph is the previous year. For this reason, we have

chosen to visualize this as a blue circle rather than a vertical bar graph. This ensures uniformity

of notation. For both this and the following bullet graphs, we have chosen to dispense with any

categorization of the order volume. A button was placed next to the heading „Sales organizati-

on“. When clicked, this opens a pop-up, which can be seen in the next screenshot. The first dia-

gram displayed shows the order volume for the sales organizations over the course of the year.

The year‘s activity is shown as a line graph, so it is possible to track whether the sales patterns

of the various sales organizations have improved or gotten worse over the course of the year. By

clicking on a legend item, the selected sales organization will be hidden from view and the scale

of the diagram changed. Also, by selecting a line in the line chart, the bullet graph appears at the

bottom left. This shows the volume of orders for the various offices of the selected sales orga-

nization. To represent the desired target value, the previous year value is multiplied by 1.2 and

displayed as a bar in the chart.

Bullet Charts der Verkaufsorganisationen

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The bullet graphs for the sales offices can be clicked to display additional information. By cli-

cking on a sales office, it is possible to drill down on the corresponding sales groups. The sales

groups then appear in the bottom right corner in tabular form. The table can be sorted and

includes the KPIs order volume, costs and profit margin. Because this level of detail is so low, we

chose to display the information in tabular form.

We also ensured that we observed best practice in the design of the diagrams and the table. In

doing so, we were able to both expand on and maintain the uniform design concept.

The bullet graph in the pop-up shows the indicator as a gray bar, although this was implemented

as a black bar for the bullets in the Performance section. We opted for this deviation from the

design concept so that the values in the bullet graph „Sales offices“ would be more legible.

We included pop-ups for all the order volume bullet graphs in the central area of the dash-

board to comply with the fourth best practice „Don‘t overtax your screen real estate“. The main

dashboard provides an overview of the sales organization, distribution channel and division. In

addition, there are drill down options that the user can select, if desired, to achieve a lower level

of aggregation.

The sales organizations pop-up

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5.4 Order volume by divisionThe order volume by division is comparable with the order volume by sales organizations. Here,

however, the focus is placed on the products of the IDES group and not on employee perfor-

mance. By displaying order volume sorted by division, it is possible to identify top sellers or slow

movers. The design of the bullet graphs, which can be seen in the next figure, is analogous with

the previous graph, so this won‘t be described again.

As with the sales organization, we have also implemented a drill down option for Products so

that lower levels of aggregation can be achieved. As before, this information can be displayed

using the details button provided:

Bullet Graphen der Sparten

Pop-up for divisions

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When clicked, the pop-up initially shows a treemap of all products. We have opted for a treemap

here because, unlike with the sales organization information, it‘s not the amount of activity

across the year, but rather the volume of sales that is important. The different parts of the tree-

map are also clickable. By clicking on a division, a bar graph will open on the left, displaying the

product hierarchies for that division. The volume of orders will also be displayed here as a key

performance indicator. The screenshot shows the product hierarchy for the High Tech division.

Here, we can see that the top seller hierarchy for this division is monitors. By clicking on the bar,

the graph is extended to include the table on the right. The table shows the products in this hie-

rarchy. The level of detail for the table is so low that using a diagram here would be superfluous.

We will, however, have some large tables to deal with, which is why we have included a search

box as well as the ability to sort values and display the number of entries.

By combining the use of bullets, treemaps, bar charts and tables, we were able to realize a high

degree of information density. We decided to keep the design of the elements simple so that as

much information could be displayed as possible. In other words, the design concept has been

maintained. We have also added one more bar graph for displaying turnover: In line with our

best practices, it has been included in the bar chart and appears in a light gray.

5.5 Order volume by sales channelThe final breakdown of the order volume is shown in terms of sales channels. To this end, we

have placed the bullet graph to the left of the central dashboard area. The bullet graphs were

designed and developed in a similar manner to the previous two graphs. They represent the

view of the IDES Group customers, end customers, and resellers. The end customers use the

purchased product itself, while the resellers act as distributors:

Sales channel bullet graph

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The last interactive element of the dashboards is the volume of orders by sales channel. Here we

have also implemented a drill-down to a lower level of detail (a pop-up opens when you click on

the button. See screenshot). In contrast to the previous one, the contents of this pop-up are im-

mediately displayed in their entirety. Here we have a top 10 diagram of customers for each sales

channel, presented in the form of a bar graph.

The sales channel pop-up

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5.6 Customer KPIsThe lower left of the dashboard provides an overview of the various customer KPIs. Because we

are dealing with individual values, we chose to visualize information using a table. A dashboard

should always show comparisons, thus the previous year‘s growth will be displayed in the table

using a trend arrow:

There are always costs associated with any customer order. These include, among other things,

administrative and departmental staff costs. In most cases, these costs are independent of the

actual order amount. An exception here would be any sales personnel who work on a commis-

sion basis. For this reason, companies should always strive to keep the average order value as

high as possible.

Open orders are any orders that have not yet been invoiced. Consequently, non-invoiced orders

are SAP orders, for which no invoice has as yet been created. We have included this indicator

in the table, because it should be kept low so as not to interrupt the company‘s cash flow. The

number of new customers keeps the sales manager informed about the success of new customer

acquisitions.

As for following table design best practice, we have outlined the table with white space and

ensured that the columns have been kept in their correct order. We also followed best practice

for text formatting, ensuring this was applied throughout the dashboard: a sans serif font that,

for quantitative values, is right justified and highlighted in bold. This ensures that the user‘s

attention is drawn to the values themselves and not their description. We have also used red

(negative) and green (positive) trend arrows to display comparisons with the previous year.

Table with various customer KPIs

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5.7 Market share for sales organizationsThe last part of the dashboard displays three bar charts showing the absolute market share of

the sales organizations. The market share of the sales organizations is not maintained in the

IDES system. Because of this, we have also made an assumption here with respect to market

share. Just as with the customer satisfaction data in the previous table, the market share data

used here is purely fictitious. The market share and customer satisfaction data are saved in tab-

les in the IDES_DW database.

The following screenshot shows the three market share bar charts. The three sales organizations

deal with different markets, which is why a separate chart is used for each one. The companies

of the IDES Group have been highlighted in blue. The sum of the beams of each chart is 100%.

We used a uniform scale in designing the diagram. Also, only the Group‘s own companies are

highlighted in blue. However, it is also possible to compare IDES‘ own sales organizations with

other companies. By using bar charts, we have achieved a higher information density than we

would have if we had chosen to represent market share using pie charts.

Market share for the various sales organizations

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6. ConclusionDuring the implementation of the sales dashboard, it became clear that it is possible to use open

source tools such as Pentaho and Ctools to full satisfy the professional requirements for proces-

sing and visualizing company data. For us it was important to show that it is not so much the

functionality of the software, but rather the observance of a few universal rules for representing

and visualizing data that counts. By adhering to a few basic principles, an attractive dashboard

can be created with a reasonable amount of effort that fully meets the goal of supporting good

decision-making.

And as for the implementation of the sales dashboard, setting up the ETL process was achieved

without any difficulties using Pentaho 5. We were able to easily convert the data to a multi-di-

mensional star schema and, using the corresponding, scenario-appropriate hardware, store this

in the data warehouse. In creating the data warehouse and star schemas, we used the Kimball

theory, because it is a widely-used concept and also because Pentaho is partly built upon it.

For the data visualization, we followed the standard reference works for dashboard design and

data visualization, deriving ten best practices for dashboard design. These best practices are so

general in nature, they can be applied to any dashboard. In doing this, it was important that the

implementation of these design rules in creating our data visualizations should serve to high-

light and emphasize the dashboard. It was also important that information be effectively passed

to the user with the aim of supporting efficient decision-making.

We implemented the dashboard in Pentaho CDE, one of the Pentaho Ctools specifically used for

dashboard design. Thanks to its open source program code, CDE (like the other Ctools) provides

numerous enhancement and expansion options. In theory, any and all functions offering HTML,

CSS and JavaScript are achievable with CDE.

26

it-novum profile

Your contact person for Business Intelligence and Big Data: Stefan Müller Director Big Data Analytics

[email protected]

+49 (0) 661 103 942

Leading in Business Open Source solutions and consultingit-novum is the leading IT consultancy for Business Open Source in the German-speaking market. Founded in 2001

it-novum today is a subsidiary of the publicly-held KAP Beteiligungs-AG.

We operate with 85 employees from our main office in Fulda and branch offices in Düsseldorf, Dortmund, Vienna

and Zurich to serve large SME enterprises as well as big companies in the German-speaking markets.

it-novum is a certified SAP Business Partner and longtime accredited partner of a wide range of Open Source pro-

ducts. We mainly focus on the integration of Open Source with Closed Source and the development of combined

Open Source solutions and platforms.

Due to the ISO 9001 certification it-novum belongs to one of the few Open Source specialists who

can prove the business suitability of their solutions, proven by international quality standards.

More than 15 years of Open Source project experience ▶ Our portfolio contains a wide range of Open Source solutions within the applications and infrastructure area as

well as own product developments which are well-established in the market.

▶ As an IT consulting company with a profound technical know-how within the Business Open Source area we

differentiate ourselves from the big solution providers’ standard offerings. Because our solutions are not only

scalable and flexible but also integrate seamlessly in your existing IT infrastructure.

▶ We can assemle multidisciplinary project teams, consisting of engineers, consultants and business data proces-

sing specialists. Thus we combine business know-how with technological excellence to build sustainable business

processes.

▶ Our target is to provide you with a high-quality level of consulting during all project phases – from the analysis and

conception up to the implementation and support.

▶ As a decision-making basis prior to the project’s start we offer you a Proof-of-Concept. Through a real-case simula-

tion and a developed prototype you can decide on a new software without taking any risks. Moreover, you benefit

from:

и Security and predictability

и Clear project methodology

и Sensible calculation

it-novum GmbH GermanyHeadquarters Fulda: Edelzeller Straße 44 · 36043 FuldaPhone: +49 (0) 661 103-333Branches in Düsseldorf & Dortmund

it-novum branch SwitzerlandHotelstrasse 1 · 8058 ZurichPhone: +41 (0) 44 567 62 07

it-novum branch AustriaAusstellungsstraße 50 / Zugang C · 1020 ViennaPhone: +43 1 205 774 1041

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