Evaluating Self-Service BI and Analytics Tools for SMEs

Antonio Oliveira

and Jorge Bernardino

1,2 b

Polytechnic of Coimbra – ISEC, Rua Pedro Nunes, Quinta da Nora, 3030-199 Coimbra, Portugal

CISUC - Centre of Informatics and Systems of University of Coimbra, Pinhal de Marrocos, 3030-290 Coimbra, Portugal

Keywords: Self-Service Business Intelligence and Analytics, Business, Business Intelligence, Analytics, Metabase,

Pentaho Community, Power BI Free, QlikView, Tableau Public.

Abstract: In the vast Data Science domain, Business Intelligence (BI) and Data Analytics are two of the most relevant

topics nowadays. Regardless of the data type an end-user needs to work on, data visualization and/or analytics

can be a valuable support for a successful decision-making process in management. For that, free and open-

source business intelligence and analytics solutions are on the market as an indispensable opportunity for

companies to start benefiting from data analytics at no cost. In addition, that task has been currently eased by

a group of BI and Analytics tools named as “Self-service”, which is an Advanced Analytics topic and designed

to enable users with no IT background to perform analyses of data and find business opportunities themselves

with minimal or no assistance from IT technicians. Considering that, to help Small and Medium-sized

Enterprises (SMEs) decide on a free self-service data tool according to their needs, we compare in this paper,

on a functionality basis, 5 popular Self-Service BI and Analytics tools: Metabase, Pentaho Community, Power

BI Free, QlikView, and Tableau Public.

1 INTRODUCTION

Self-Service Analytics Software allows business

users to analyse data to find business opportunities

without an IT background. These technological

applications are an approach to advanced analytics.

They ensure that users can easily benefit a lot from

their business data without necessarily possessing

statistical or technological background. Many

organizations have recognized the importance of

Self-Service Analytics Software, as they have been

using these computer tools for their processes (Pat

Research, 2019b).

Self-service Analytics belongs to the Business

Intelligence (BI) field and empowers line-of-business

professionals to build reports and queries on their

own with minimal support from IT specialists.

Additionally, Self-Service Analytics is represented

by BI tools, which have a slight learning curve and

offer uncomplicated data access through basic

Analytics and simplified underlying data models

(Gartner, 2020).

https://orcid.org/0000-0002-0078-1033

https://orcid.org/0000-0001-9660-2011

There are many features that makes Self-Service

Analytics Software important to organizations, and

some of them are: Data Gathering, Filters,

Visualizations, Reporting, Collaboration, Data

Analysis, Dashboards, Predictive and Real-time

Analytics, high ease-of-use for lower-skilled users,

Integration of Data, Natural Language Processing,

and Security. All that naturally in addition to the

software capabilities designed for the high-skilled or

more technical users (Pat Research, 2019b).

The most visible benefits of the features

mentioned above are predictive power for project

future trends and events to plan as soon as possible

for their effects. Thus, it is possible to discover

business opportunities which stimulates insights that

are invisible in not-yet-analysed data. Additionally,

urgent issues can be addressed with help of real-time-

analysis, and easier access to data about customers, as

the business will possess and analyse the data of their

customers itself, with no need to wait for industry

reports or other third-party sources of data

(Bernardino, 2011).

The more end-users can do BI and Analytics on

their own by performing, for instance, drill-

Oliveira, A. and Bernardino, J.

Evaluating Self-Service BI and Analytics Tools for SMEs.

DOI: 10.5220/0009820400890097

In Proceedings of the 17th International Joint Conference on e-Business and Telecommunications (ICETE 2020) - Volume 3: ICE-B, pages 89-97

ISBN: 978-989-758-447-3

throughs/downs, customizable reports/ dashboards,

and ad-hoc calculations, the more decreases the IT

resource drain in the company freeing up then the IT

department for more strategic duties.

Self-Service BI and Analytics brings several

gains for companies (Greengard, 2015). Thus,

organizations can deal with decision-making by

empowering users with no IT skills to produce

valuable information through data science software.

Considering that, we have decided to search for the

most popular free and open-source Self-Service BI

and Analytics tools and evaluate them according to

criteria based on the available relevant features.

This work aims to make a comparative analysis of

existing functionalities in Self-Service BI and

Analytics solutions to help small and medium

enterprises adopt a software solution adequate to their

needs and budget. We also believe it is beneficial to

promote information about BI and Analytics

solutions, focusing on their great associated benefits.

The rest of this paper is organized as follows.

Section 2 contains Related Work. Section 3 describes

the five of most popular BI and Analytics tools.

Section 4 explains the Evaluation Criteria used in our

study. Section 5 presents a Comparative Analysis of

the tools. Finally, Section 6 presents the conclusions

and future work.

2 RELATED WORK

In 2016, McCafferty mentioned that through 2020,

according to the industry research, investment on

acquiring Self-service data tools would grow 2,5

faster than on traditional data tools, as those tools

were already helping significantly businesses adopt

the Do-it-yourself Analytics approach which enables

organizations to boost and improve the speed, ease-

of-use and quality of analytics efforts (McCafferty,

2016).

In 2015, Greengard concluded that over the last

decade Self-service BI and Analytics tools had

become a critical resource to help firms of all shapes

and sizes operate faster and smarter (Greengard,

2015).

3 ANALYTICS TOOLS

The initial idea of this work was to evaluate

preferably only open-source solutions rather than

proprietary ones. Then, we started by doing

exhaustive search on websites which list Self-Service

BI and Analytics solutions to build our top 5 tools for

evaluation. Curiously, that research revealed an

indeed reduced number of open source solutions. In

addition, almost all found open-source tools were not

recommended or well rated by distinguished research

companies such as Gartner or Predictive Analytics

Today, which base their reviews not only on customer

ratings but also on an unbiased methodology (Pat

Research, 2019a).

Considering the low number of found open-

source tools and to not evaluate only proprietary

solutions, we decided to build our top 5 solutions

including three most popular free but non-open

source solutions and two open-source ones, so that we

could check ourselves if there was no highly

competitive open-source alternatives. Thus, the

proprietary ones were Power BI Free, Qlik View and

Tableau Public. In addition, the open-source ones

were Metabase and Pentaho. The first one is free,

completely open source, referred as promising, and

has a good review on the Predictive Analytics

webpage (Pat Research, 2019c). The latter is highly

recommended by Gartner, but it is not totally free.

It is also worth highlighting that we could not

consider several of the various curated lists of top

Self-Service BI and Analytics found on the web.

Those lists tended to be of dubious value for self-

service solutions, as they indicated, for instance,

JavaScript libraries for adding interactive charts to a

website, what may not be of straightforward

implementation for end-users who need to visually

query data without having the specific IT skills.

In the following sections, we describe the main

characteristics of each solution. Besides that, major

advantages and limitations of each one are outlined.

3.1 Metabase

Metabase is a web-based, open-source visual query

and BI tool designed visualizations released in 2015

(Metabase, 2020b). It releases updates frequently and

is intended for companies of all sizes.

It is built and packaged as a Java jar file and can

be run anywhere if Java is available. It also provides

a binary Mac OS X application for installation or can

run on Docker (Metabase, 2020a). It is a server

application accessible to the entire company.

This platform is available under three types of

licences: Affero General Public License (AGPL),

which is free of costs, and other two versions,

Premium Embedding and Enterprise with acquisition

costs.

It addresses the vital, but less complex questions

that make up most day-to-day data analytics

ICE-B 2020 - 17th International Conference on e-Business

operations. In addition, it can organize information in

a central place and connects various interaction points

to perform data storytelling.

This software allows filter and/or group data,

without resorting to Structured Query Language

(SQL). Furthermore, it monitors questions created by

users to provide insights on the available data. These

questions can produce graphs and charts, and these

visualizable results can be saved and organized in

dashboards (Santos et al., 2019).

We can see in Figure 3 that the platform has a

clean user interface, where it is shown a screen related

to a feature which suggests some automated

explorations for newly connected data.

Figure 1: Metabase User Interface. (Source: https://www.

metabase.com/docs/latest/users-guide/images/x-rays/x-

rays-browse.png).

The most expensive license includes features such

as white labelled embedding, row level permissions,

and auditing tools. Following we have some strengths

and weaknesses of it (Pat Research, 2019c) (Do,

2018).

Advantages:

 Rich dashboards with auto refresh and full

screen;

 Clean user interface;

 Supports numerous standard data sources;

 Large choice of visualizations.

Limitations:

 A server is necessary to maintain the

infrastructure;

 Only Mac OS users can deploy it quickly

using a binary application;

 Limited variety of charts and settings;

 Weak permission control.

Metabase provides different ways to be deployed

anywhere, is constantly improving due a strong

community behind it for support and development.

3.2 Pentaho Community Edition

Pentaho is an open source suit of tools for Business

Analytics released in 2009 (Pentaho, 2015). It is one

of the first open source solutions of its type and it is

frequently updated. It runs on Windows, Linux or

Mac OS and is designed for companies of all sizes.

It provides analytics for several user roles, from

visual data analysis for business analysts to tailored

dashboards for executives. It features ad-hoc analysis

and visualization, data visualization, On-line

Analytical Processing (OLAP) services, custom

dashboard creation, data mining and report designer.

Furthermore, it supports multiple Big Data

integration/analytics and offers mobile business

analytics (Pentaho, 2013).

As can be seen in Figure 1, the platform has an

architecture divided into two main layers:

Presentation and ETL. The first one contains tools for

reporting, analyses, dashboards and process

management, whereas the ETL is designed for

Extraction, Load and Transformation of data.

Figure 2: Architecture of the Pentaho Open BA Suite.

(Source: https://pt.slideshare.net/nvvrajesh/pentaho-bi-

suite-overview-presentation/8?smtNoRedir=1.).

Pentaho has a community and an enterprise

version, which are free and paid, respectively. The

key differences are the free version does not allow

mobile features, interactive reporting, and dashboard

designer. Moreover, it restricts access to some more

advanced functionalities within the free available

features for data integration and big data [13]. A few

advantages and limitations of Pentaho are mentioned

next.

Evaluating Self-Service BI and Analytics Tools for SMEs

Advantages:

 Mature data access and data transformation

features;

 Reporting is fast due to in-memory caching

techniques;

 Easy integration with third party

applications, such as Google Maps;

 It runs on almost all platforms: Android,

iPhone, iPad, Mac, Web-based, Windows.

 Features regarding predictive analyses and

big data sources are present at no cost.

Limitations:

 The type of graphs and layouts proposed for

some diagrams and charts are limited and

partly outdated.

One of the key Pentaho’s differentiators is the

strength of being supported by a large community,

due to its strong open source software roots.

Moreover, its mobile data discovery functionality

ensures users are productive no matter where they are.

SMEs with lots of different types of data and big data

sources are highly recommended to use Pentaho.

3.3 Power BI Free

Power BI is a free desktop proprietary Microsoft

platform released in 2011 (Wikipedia, 2019). It works

in conjunction with a cloud application that makes

possible to publish reports throughout the business.

Power BI can only be installed on Windows OS and

is updated every month. It is intended for small to

midsize organizations.

It has connections to several data source types,

interactive/sharable reports and dashboards for web

or mobile, and real-time data. Furthermore, it has the

same rich visualizations and filters as the paid

version, such as auto-detect to find and create data

relationships between tables, Python support, and a

natural language query feature. Additionally, it is

possible to save, upload and publish reports to the

web with a storage limit of 10 GB per user

(Techtarget, 2020).

As can be seen in Figure 2, the platform works in

an architecture divided into three layers: Business

Analyst tools (Excel and Power BI designer),

Microsoft Cloud to host reports and datasets, and

visualization media, which includes computer web-

browsers and mobile devices.

Figure 3: Power BI Architecture Overview. (Source:

https://yodalearning.com/tutorials/power-bi-architecture-

power-bi-security/).

It is worth mentioning that its other two types of

license, Pro and Premium, which are not free. These

licenses allow the ability to collaborate reports with

other Power BI users, analyse data in Excel, direct

query, more advanced analytics features, and the use

of the Power BI Report Server (Microsoft, 2020a).

Advantages:

 Inexpensive to upgrade;

 Wide range of custom visualizations;

 Seamless integration with Excel;

 Fast learning curve for basic functionalities.

Limitations:

 Rigid about relationships between tables;

 Bulky user interface;

 Upload limit of 1GB per dataset;

 Need to learn several Microsoft interrelated

solutions to take full advantage of it;

 On-line report must be public to the Internet;

 A few options to configure visualizations;

 It uses DAX, a hard language to work with.

Power BI Free has available a huge number of

learning resources spread on the web. It has an active

community, over 70 numerous integrations and data

sources (Microsoft, 2020b). In addition, it is attached

to Microsoft, which is always investing resources into

it and working for new features and updates.

3.4 QlickView Free

QlikView is a robust proprietary desktop platform for

business discovery which offers a powerful free

version in terms of features. It was released in 2012

and is frequently updated (Qlik, 2020). Besides that,

it is suitable for companies of all sizes, allowing

installation only on Windows OS.

ICE-B 2020 - 17th International Conference on e-Business

This software is one of the major Tableau

platform competitors. Its free version has no

limitations in terms of time or functionality compared

with its paid edition.

It supports visual data discovery, reporting, ad-

hoc queries, dashboards, shareable reports, guided

model creation, mapping data, reporting and

scalability with data integration, various forms of data

presentation, and predictions with historical data.

As can be seen in Figure 4, the platform’s

architecture is based on three main components: QV

Server (provides functionality to the client and must

run on a Windows OS), Client (web browser or an

application shell that provides a container for the

client code), and a Web Server (http server for pages,

user authentication, and communication between QV

Server and Client).

Figure 4: QlikView Architecture. (Source:

https://help.qlik.com/en-US/qlikview/November2017/pdf/

Deploying%20QlikView.pdf).

However, the files/documents created by a free-

license user cannot be opened on another computer or

shared with a user who has a paid license.

Advantages:

 Fast user experience due to be a memory-

resident application;

 Transparent reporting and scalability with

data integration;

 Fast implementation.

Limitations:

 Need of macros, duplication, and

maintenance of the QlikView objects for

formatted report;

 It runs only on Windows OS;

 Reloading can take a significant amount of

time as it loads most data into the system

RAM.

Qlikview is excellent in visually analysing data

relationships. Its in-memory engine recognizes

patterns in data that we are not normally able to do it

by using SQL alone (Kumar, 2019).

3.5 Tableau Public

Tableau is one of the oldest and most famous “self-

service” analytics platforms on the market. It was first

released in 2010. It is not open source, but it has a

commercially free platform and releases updates

frequently.

It must be installed on Windows or Mac OS to be

used in conjunction with the web free version. It

allows anyone to analyse data, create and publish

interactive data visualizations in the cloud.

It offers many of the same powerful visualization

capabilities as its paid desktop and server versions. It

has a variety of analytical methods, inspection and

manipulation of data in a variety of ways and even

analysis template creation. Interactive and shareable

dashboards can be distributed, depicting trends,

changes and densities in graphs and charts. In

addition, it allows data mixing, real-time

collaboration and data-analyses.

Data Analyse is possible from sources such as

Excel sheets for geographical visualizations, Gantt

charts, tree maps and other templates. The free

version has a limitation of 15.000.000 data rows per

workbook (Tableau, 2016).

As can be seen in Figure 3, the platform’s

architecture is categorized into two main segments:

Tableau server and Tableau desktop. There is a server

application to receive, treat, analyse, transform and

publish data and the desktop one to send data. Besides

that, the web and mobile clients to visualize analytics

outputs.

However, it is possible only to connect to Excel

sheets, text file formats, statistical files, Google

sheets, and web data connectors, which must be

uploaded to the cloud.

Figure 5: Tableau Architecture. (Source: https://data-

flair.training/blogs/tableau-architecture/).

Evaluating Self-Service BI and Analytics Tools for SMEs

Advantages:

 Quick responsiveness;

 Extensive training resources available for

free on the Tableau Public site;

 Very intuitive user interface;

 Dashboards can be viewed on multiple

devices like tablet, mobile and laptops;

 Extensive community documentation.

Limitations:

 To keep workbooks private, a paid

subscription is required;

 Complex visualizations require time and

cost-intensive training.

Tableau Public is a very sophisticated and

advanced system. It surpasses other tools mostly in

data visualization. It provides an all-inclusive and

user-friendly data visualization experience (Tableau,

2020).

4 EVALUATION CRITERIA

First, we needed to create a list of essential

functionalities for a high-quality Self-Service BI and

Analytics solution. For that, we consulted the 15

Critical Capabilities of an Analytics and BI Platform

according to Gartner (Howson, Richardson, Sallam,

& Kronz, 2019).

However, we did not utilize criteria related to

Metadata Management, Scalability and Data Model

Complexity, Embedding of Analytic Content, and

Advanced Analytics for Citizen Data Scientists, once

they do not fit exactly the “Self-Service” concept

addressed in this paper, which relates mainly to basic

Analytics. Besides that, for the non-technical end-

users these capabilities will probably not weight when

they must decide themselves on a tool, considering

they require more than basic background in Analytics

to be properly explored.

Moreover, the functionalities/criteria list relates

to the capabilities recommended by Gartner, but it is

written in a way intended to be of more

straightforward understanding and reference. To

confirm the relevance of the chosen features, we also

checked the criteria list present on the Predictive

Analytics Today Research website (Pat Research,

2019b). We explain the selected features ahead.

As self-service analytics deals sometimes with

confidential data, Access Control and Security is an

essential feature through the implementation of user

permission levels.

Following we have Ad-hoc Reporting, which

allows reports to be created by end users by adding or

removing dimensions/expressions from the datasets.

Ad-hoc query is useful when end users need to create

queries on their own for questions that cannot be

solved by predefined queries. Cloud Services refers

the capability to perform data analysis using a cloud

version of the software.

When it comes to visualize data, the more we can

visualize data in different ways, the more data

visualization becomes interesting and attractive.

Thus, we chose the Data Visualization variety

feature.

Data Integration refers the capability to integrate

with several different data sources. The higher the

number of supported data sources, the better.

Dashboard Designer is the functionality for creation

of customized business dashboards from scratch.

Those panels will contain the graphs and charts

selected by the end-user.

Interactive visualization enables data

exploration manipulating chart images, colour,

brightness, size, shape and motion of visual objects in

BI dashboards.

Mobile capabilities are a great advantage, as by

making use of mobile devices capabilities, it is

possible to perform Data Analytics anywhere and

anytime, increasing consequently productivity.

Natural language queries are a trend and mean

that software can query data also by semantics and

natural language inputs.

OLAP stands for Online Analytical Processing. It

enables us to perform quick queries and calculations

from different measures/dimensions such as, sales

figures, budgets and quantities sold. That in different

degrees of detail and according to the end user needs.

Predictive Analytics ensures the tool can analyse

data and forecast trends and events.

Real-time Analytics is related to performing

analyses on data in real time, as data streams are

arriving.

Real-time collaboration allows team members

to share dashboards and reports not just for

visualization but also for edition.

Report customization allows the generation of

formatted and interactive reports. With Report

Scheduling we can schedule the generation and

distribution of reports.

5 COMPARATIVE ANALYSIS

Based on the technical specifications of the

Self-Service BI and Analytics platforms available on

ICE-B 2020 - 17th International Conference on e-Business

the market and analysed according to the criteria

defined in Section 4, we built a comparative table on

the availability of respective capabilities, taking into

account their characteristics.

The following table is intended as an aid to

selecting the most suitable “Self-Service” platform to

an organization, depending on its needs. It reveals

what each tool can perform and shows an option that

fits into the particularities of organizations. It is worth

mentioning that we focused on the free versions of

each tool. Thus, the paid capabilities are not checked

in the table.

Table 1: Functionalities considered to be essential for a BI

and Analytics solution.

Functionalities / Criteria

Self-Service BI and

Analytics Platforms

Pentaho

Power BI Free

Metabase

QlikView

Tableau Public

Access Control and

Security

    

Ad-hoc reporting

   

Ad-hoc query

   

Cloud Services



Data Visualization variety

 



 

Data Integration

 

Dashboard Designer

   

Interactive Visualization

   

Mobile capabilities



 

Natural Language Query



OLAP

 

Predictive Analytics

 

Real-time Analytics



Real-time Collaboration



Report customization

  

Report Scheduling

We can see in Table 1 that all tools are able to

deliver “Data Visualization” and “Access Control and

Security”. However, Security, depending on the

required data confidentiality degree, is compromised

for Power BI Free and Tableau Public, as all the

visualization works must be published and public to

the entire web. We should clarify that they remain

checked in Table 1 for the referred tools because the

access to the Self-service BI software and its original

workbooks remain restricted to the user who created

the project.

Pentaho is a consolidated open-source product on

the market. However, it lacks most free features when

compared to the other tools here under evaluation.

Power BI showed to be the most complete free

option, not offering just “Real-time collaboration”. In

addition, the “Real-time Analytics” feature refreshes

the data visualization only every 30 minutes.

Metabase revealed to be more for data

visualization and lacks many features, but the tool has

seamless connection to third party tools to

compensate those missing capabilities.

Qlikview also presents a very complete set of free

features and misses just “Cloud Services”, “Natural

Language Query”, “Real-time Analytics”, and “Real-

time Collaboration”.

Tableau Public lacks just in three free features.

Among them is “Report customization and

scheduling”, what causes surprise, as such

functionality, except for the scheduling feature, is

easily found at no cost in several other free tools.

All the solutions work at least in 8 different

languages, can connect to at least 11 types of data

sources, and none of them offers scheduling for the

Report Customization and Schedule functionality.

The cloud services offered by the free versions of

Power BI and Tableau are designed to allow mainly

visualizations of the work done locally on a desktop.

As for “Mobile capabilities”, Power BI Free offers

a mobile application for visualizations, while

QlikView and Tableau Public allow the same but just

through mobile web-browsers and the dashboard

and/or reports need some pre-configuration to be

displayed correctly on mobile devices.

From the tree tools with more functionalities

checked in Table 1, Power BI Free stands out in

features such as “Ad-hoc Reporting” and “Predictive

Analytics” due to its higher easy-of-use compared to

the other tools, being the only one to feature “Natural

Language Query” at no cost. Tableau is overall so

powerful as Power BI, but its user interface is less

intuitive. QlikView seems to be less “self-service”,

once it looks more traditional and technical than the

other two mentioned tools, being so naturally less

intuitive and requiring end users already more used to

Data Analytics.

6 CONCLUSIONS AND FUTURE

WORK

We can conclude Self-Service BI and Analytics tools

can cause a significant positive impact inside SMEs

by empowering line-of-business end users to take

important decisions based on queries and data

analyses made by themselves. Further, it also saves

time for the organization’s Information Technology

Evaluating Self-Service BI and Analytics Tools for SMEs

(IT) teams, who would have otherwise to still spend a

considerable length of time with basic Analytics for

the referred end users. Instead, these teams can focus

on other tasks that will permit the organization to

achieve more strategic goals.

The selection process of the best suited “Self-

Service” platform to an organization will depend on

many factors like the available financial, human and

material resources. However, the vision that the top

managers have to the organization will be also

essential for that, once the SMEs should understand

that the investment of time to learn how to use those

platforms means higher likelihood of new business

opportunities and profits, even if they have to pay for

training resources, consulting and licenses.

From our analysis, we conclude that Self-Service

BI and Analytics are gaining more and more space on

the market as they have evolved in features and

quality. From the 5 tools analysed, we cannot define

which one exactly occupy the first position in our top

5, because that also depends on an enterprise’s

requirements.

Considering just the number of free features, we

could conclude that Power BI Free, QlikView and

Tableau Public are ahead and have more to offer at no

cost for SMEs. However, if we had considered paid

capabilities, that tool ranking would naturally change,

as all tools, except for Metabase, would have nearly

all functionalities checked in our comparative table.

As future work, we intend to perform a

comparative analysis of other relevant Self-Service

BI and Analytics solutions to make available a wider

set of them for choice by the SMEs according to their

requirements. Additionally, an experimental

evaluation by watching them in production in a real

enterprise environment.

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