Improve Decision Making
with Self-Service Analytics

Empower your team with modern integrated reporting for faster and more informed decisions

Data Analytics for uninitiated

Business Intelligence and Data Analytics share a strong bond, although some key features differ. The primary difference is when the event under analysis occurs. The former describes past events, in other words, facts. Conversely, the latter focuses on what can happen in the future and predicts the events. From the early 90s, tech giants have developed solutions allowing businesses to improve decision-making using fact-based support systems [1]. Since then, the rise of the importance of data within the decision process of firms has never ended, and modern solutions exploit the power of the cloud to put enterprise technologies at the disposal of businesses of any size.

As the need for quick access to business intelligence has grown at an unprecedented pace, usability and consumability have become the Key Success Factors. Self-service Business Intelligence & Analytics can be defined as the set of facilities that enables Business users to rely more on their capabilities and less on IT organizations. That answers the increasing demand for data-driven business decisions needed to keep up with fast-changing requirements.

To serve business users, self-service analytics solutions need to reduce the technical skills and learning necessary to use them at the minimum level. Microsoft Power BI aims at fulfilling such a purpose. It offers a solution that steepens the learning curve while leveraging its similarities with Microsoft Excel and providing advanced enterprise features. This article describes the advantages for small and medium-sized enterprises (SMEs) of moving to modern self-service analytics tools – such as Power BI – and how to use them to increase profits via enhanced financial monitoring & controlling.

78% among business and technical professionals require faster time to value from BI and Analytics solutions

Self-service Analytics for SMEs

Driving and restraining forces behind widespread adoption

As the importance of data-driven decision-making is getting higher, the Data Analytics & Business Intelligence (BI) sectors, with market size of 24bn EUR in 2021, are expected to grow significantly at a CAGR of 8.7% until 2028 [2].

The professional services industry is the one that makes the most prominent use of business intelligence and analytics tools, followed by technology, retail, and financial services [3].  Indeed, as companies need more data-informed decisions to keep up with a fast-moving market, professional services firms need to provide data-driven advice to their clients. Furthermore, to help customers improve or manage their processes, professional services companies need to exploit all the available information to describe the current situation and forecast possible developments.

Although the need for BI & Analytics is well rooted in modern businesses, some factors still slow down their widespread adoption, especially among SMEs. They are the high cost connected with the development of centralized analytics solutions and the shortage of qualified experts. In such a context, it is unsurprising that self-service analytics is becoming popular among data consumers. Indeed, such products provide environments in which data and information can be discovered, accessed, explored, and shared quickly, at a low cost, and with basic analytical skills. Already in 2011, a survey conducted by The Data Warehousing Institute showed that among 587 business and technical professionals, 78% required “faster time to value from BI solutions” [4]. Nowadays, the expectation of users is even augmented by the seamless features provided by modern premium applications.

Top Industries using
Business Intelligence

Professional Services 34%
Technology 32%
Retail and CPG 11%
Financial Services 8%
Industrials & Chemicals 7.5%
Healthcare and Lifesciences 7.2%

Market Share by Industry
Source: Slintel [3]

Microsoft Power BI

An effortless transition to modern Analytics

Power BI is one of the leading Analytics and Business Intelligence software, with almost 13% of the market share as of September 2022 [3]. Although compelling, such a number is low considering that its free version is included in Microsoft Office 365, which has a global market share of 48.08% [4]. Moreover, given the spread and familiarity business users have with the Office suite, it may be expected for Power BI to own an even larger market share.

Furthermore, when it comes to self-service analysis and reporting solutions, comparison with MS Office Excel comes almost naturally. Excel is a great tool for calculating analytical measures, automating processes, and presenting data with excellent visualization capabilities. However, when it comes to BI, not being specifically designed to produce BI reports may be a downside for Excel. Power BI shares some functionalities with Excel, though it is specifically designed to meet state-of-the-art BI standards and requirements. The similarities between the two applications are found mostly in the import of the data and the general design of the user interface. On the contrary, the main differences are identifiable in Data Visualization, integration with Machine Learning suites, and Sharing Capabilities regarding input data and results.

Top 5 Business Intelligence
and Dashboard Technologies

Source: Slintel [3]

Modern Functionalities
supported by Power BI

Machine Learning

  • No-code Machine learning applications through Azure Machine Learning integration
  • AI-powered image recognition and text analytics
  • Automatic analysis data sets and find patterns with Quick Insights


  • Easy connection to data sources from the third party, like Microsoft, Azure, SQL Server, Oracle, Saleforce, etc.
  • Rapid integration with third-party applications via APIs
  • Distribution of reports and dashboards online or via Microsoft Teams with few clicks

Data Visualization

  • Rich and extensible set of visuals with endless customization capabilities
  • User-friendly no-code development via drag & drop

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Regarding Data Visualization, Power BI exploits a drag & drop system similar to the one available in Excel pivot tables. The graphically enhanced functionality helps users to pay greater attention to the positioning inside the canvas. To put it differently, Power BI comes with a canvas space and a rich set of visuals. Users can create graphs, dragging visuals and fields directly from a side pane and placing them wherever they want. Aside from the usual visual filters and slicers already available in Excel, Power BI offers the possibility not only to filter a single visual but to filter entire pages of reports by exploiting the dedicated pane. Furthermore, it is possible to lock filters in such a way that the end user cannot remove them. Besides the rich set of predefined visuals, Power BI has a store where more visuals can be found. Finally, when both default visuals and those available in the marketplace are not enough, it is possible to create new visuals or modify existing ones by leveraging popular programming languages such as Python or R.

Although Excel sharing capabilities have improved since its first release in 1987, it does not fully support a modern workspace. On the contrary, Power BI is designed to maximize shareability. It is based on the principles of ‘common input‘ and ‘shared output‘. The former refers to the fact that, unlike Excel, Power BI offers the possibility to leverage a shared repository in which a large amount of data can be loaded and presented through different reports. The latter refers to reports and dashboards being spread across the web or integrated into the organization’s collaboration infrastructure.


Power BI is cloud native and part of the Azure ecosystem. That allows the integration of a wide range of no-code Machine Learning applications. That, in combination with the abovementioned availability of large datasets, enables non-technical users to enhance the results of their analysis and gain deeper insights.

The following article of this series will point out how modern analytics tools, such as Power BI, facilitate the transition from spreadsheets to self-service BI and analytics. Indeed, Power BI grants a steeper learning curve for users familiar with the Office Suite while providing a wide range of advanced enterprise-level capabilities to small and medium-sized enterprises at an affordable cost.


[1] D. J. Power, „A Brief History of Decision Support Systems,“ 10 03 2007.
[2] Fortune Business Insights, “Business Intelligence (BI) Market Size, Share & COVID-19 Impact Analysis, By Component (Solution, and Services), By Deployment (Cloud, and On-Premise) By Enterprise Size (Large Enterprises, Small and Medium-Sized Enterprises (SMEs))[…], and Regional Forecast, 2021-2028” , 2021.
[3] Slintel, „Business Intelligence (BI),“  [Accessed on 2022].
[4] C. Imhoof and C. White, “SELF-SERVICE BUSINESS INTELLIGENCE – Empowering Users to Generate Insights,” 2011.


Related Services

The data services we offer are comprehensive in nature and cover a wide scope, however, as an elementary introduction, you can rely on us to provide the following solutions.

Data Analysis

We organize and examine data to create actionable intelligence.

Dashboard Design

The creation of visualization tools that allow data to be assessed efficiently and effectively.

Data Governance

We implement architectures and procedures that manage the full data lifecycle needs of a business.

Data Architecture

The integration of technologies to provide optimal end-to-end data management.

Calculation Engines for Finance

Whether for internal or regulatory purposes, we create the data gathering, calculation, and reporting processes.

About the Author

Francesco Di Cugno, Managing Director, Convolut GmbH
Francesco di Cugno
Managing Director
Francesco is a Technology Director with a proven track record in building customer-centric solutions using the latest technological innovations. He works with global organisations to realise their strategic vision and goals.