Discover how Business Intelligence can revolutionize your corporate strategy. Learn about the latest BI technologies, trends and best practices and use data to optimize your business decisions.
Business Intelligence (BI) has taken on a central role in day-to-day business. Companies of all sizes and from all sectors have recognized that data is not just a resource, but a decisive factor for business success. BI systems make it possible to gain valuable insights from a flood of data in order to make well-founded decisions and achieve strategic advantages.
With over 20 years of experience in more than 1000 software selection projects, BARC is your ideal partner for high decision-making reliability in software selection and strategic implementation of BI and analytics.
The rapid pace of technological progress and the associated constant change in the world of business intelligence make it difficult to keep an eye on everything. In order to give you a comprehensive and comprehensible understanding of the dynamics and scope of this essential business area, we draw on findings from BARC Scores, BARC Surveys and BARC Guides, which provide in-depth analyses and assessments in the field of Business Intelligence & Analytics. These resources are designed to identify the latest trends, tools and strategies in BI and analytics and provide you with the highest possible level of decision-making security when selecting software and strategically embedding Business Intelligence.
What is Business Intelligence?
The term Business Intelligence refers to technologies, applications and methods that are used to collect, integrate, analyze and present business data. The aim is to make better business decisions, enable a strategic market vision and thus improve the company’s performance. Whether through reports, analyses or dashboards, BI enables companies to gain valuable insights from their data.
This data is collected from internal systems and external sources, then processed, analyzed and presented, often in the form of reports, dashboards, infographics, charts and maps. These visualizations make complex data sets accessible and understandable, enabling users to identify trends, evaluate performance and make predictions.
The role of business intelligence has evolved over time. In the past, the focus was on providing information in the form of periodic reports. Today, BI is more dynamic and interactive, enabling real-time analysis and ad-hoc queries to provide quick answers to business questions. Natural Language Processing (NLP) enables a wider audience to easily access insights from data without knowledge of programming or query languages, and developments in artificial intelligence (AI) promise to accelerate this trend. Further technological advances in the areas of data management and analytics and, in particular, the continuing trend towards providing software in the cloud are also driving development.
Definition of terms: BI vs. analytics and related topics
Although business intelligence (BI), analytics and machine learning (ML) are often mentioned in the same breath, it is important to understand the differences and specific functions of each area. This separation of terms is crucial in order to be able to use the respective technologies and methods effectively in a business context.
Business Intelligence focuses primarily on the collection, integration and visual preparation of data. BI systems are used to provide current, historical and predictive views of business processes. They are primarily responsible for reporting, online analytical processing (OLAP), analytics and dashboards. The focus is on understanding the data and deriving insights that are relevant for business decisions.
Analytics goes one step further and includes more advanced statistical analyses. Analytics uses data, statistical algorithms and machine learning methods to identify patterns and correlations in large amounts of data that can be useful for future decisions and forecasts.
Machine learning, a branch of artificial intelligence, is often used in conjunction with BI to enable automated, data-driven decisions. It allows systems to learn from data and improve themselves without explicit programming. In the context of BI, machine learning can help to identify patterns in data and provide more precise forecasts.
The differences and overlaps between these areas are clearly highlighted in the various BARC Scores, which cover different technology areas. These assessments provide valuable insights into the respective strengths and application areas of BI, analytics and machine learning, which helps companies to use the respective technologies effectively for their specific needs.
Why business intelligence is indispensable right now
In an increasingly networked and data-driven world, the effective use of BI and analytics is no longer a “nice-to-have”, but indispensable. The way in which companies analyze and interpret their data can make the difference between success and failure. Whether you work in controlling, finance or sales, BI and analytics is your compass to guide you through the increasingly complex business landscape.
The advantages of BI become clear in case studies and BARC guides. These real-life examples show how companies have successfully implemented BI and provide valuable insights into the practical application of BI to achieve business goals.
TO WHAT EXTENT HAVE YOU ACHIEVED THE FOLLOWING BENEFITS WITH BI AND ANALYTICS? (N=1.179)
Current challenges in BI and analytics
In the modern business world, the challenges in BI and analytics can be as diverse as the data they analyze. From coping with the big data tsunami to ensuring data quality and integrating Self-Service Business Intelligence into the existing data warehouse, it is a constant juggling act. The rapid development in the BI and analytics landscape in particular can make it difficult to keep up.
Data quality and integration
One of the biggest obstacles in the field of business intelligence is ensuring data quality. Inaccurate or outdated data can lead to incorrect analyses and poor decisions. Another problem is the integration of different data sources. Companies collect data from a variety of sources such as CRM systems, financial software and external databases. The challenge is to standardize this heterogeneous data and obtain consistent, meaningful information from it. For example, inconsistent customer data from different systems can lead to confusing or misleading customer profiles.
Handling large amounts of data
With the exponential growth of data volumes, companies are faced with the challenge of managing and analyzing them effectively. Processing large amounts of data and gaining valuable insights from it requires advanced BI software and techniques. For example, companies that process millions of transactions every day need to be able to analyze this data quickly in order to make timely and relevant business decisions. This is where advanced analysis methods such as machine learning (ML) and artificial intelligence (AI) come into play, which can help to identify patterns and trends in large amounts of data.
You can find an overview and further information on the challenges, particularly when selecting BI and analytics software, here.
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Important segments and providers of business intelligence & analytics software
The BI and analytics market is rich in providers and products. Depending on your specific needs, you could choose an Enterprise BI and analytics Platform such as MicroStrategy ONE, IBM Cognos Analytics, SAP Business Objects BI, InformationBuilders ibi or Pyramid Analytics. These offer end-to-end support for a large number of use cases.
However, if you want more flexibility and ease of use, self-service software such as Tableau from Salesforce, Qlik Sisense, SAP Analytics Cloud or ThoughtSpot could be the right choice.
The major cloud providers also offer BI and analytics software that is integrated into the corresponding cloud offerings: Amazon AWS QuickSight, Looker from Google and Microsoft Power BI.
Further information on the individual tools can also be found in the BARC Reviews, which use a combination of analyst and user evaluations and survey results to comprehensively highlight the respective strengths and weaknesses.
BI and analytics trends, market developments and their significance
The BI and analytics world is constantly on the move. The trend is moving from on-premises to cloud to multi-cloud environments, with each model having its own advantages and disadvantages. Cloud-based BI and analytics software offers flexibility and facilitates access to data. It enables companies to reduce extensive internal IT infrastructures and access and analyze data in real time, leading to faster and more efficient business decisions.
Augmented analytics is driving the automation and improvement of data analysis, and the introduction of Generative AI promises to revolutionize the way we use BI and analytics, as AI algorithms can analyze large amounts of data faster and more accurately than traditional methods. For example, AI-supported BI systems can recognize patterns in customer purchasing behavior and make personalized product suggestions, which can lead to an improved customer experience and increased sales figures. Technologies such as Machine Learning and Natural Language Processing (NLP) enhance the capabilities of BI and analytics software by enabling complex analysis to be performed through intuitive, conversational interactions.
Newer trends such as data mesh and data fabric are concerned with interoperability and aim to integrate the traditionally opposing approaches of centralization and decentralization in organizational structures (mesh) and technological infrastructure (fabric) into the most efficient whole possible. Here in particular, it becomes clear time and again that there is no “one-size-fits-all” solution and that in some cases radical rethinking is required when adapting to the individual needs of a company.
What does this mean for you if you are preparing to establish or drive forward Business Intelligence in your company? Not only do you need to be aware of these developments, but you also need to be ready to integrate them into your BI and analytics strategy to stay up to date.
First of all, you should know exactly where you are, because only then you can plan the route to where you’re going. In very simplified terms, an initial assessment could look like this:
YOU STILL RELY HEAVILY ON EXCEL: It’s time to expand your BI and analytics. Consider switching to specialized BI software that gives you better access to your data and more in-depth analysis options.
YOU USE SELF-SERVICE SOFTWARE, BUT GOVERNANCE IS STILL LACKING: A central data warehouse on a cloud platform can be the answer. By implementing semantic models and centralized KPI definitions and dimensions, you can ensure data integrity while leveraging self-service BI.
YOU WANT TO MAKE GREATER USE OF PREDICTIVE ANALYTICS AND GENERATIVE AI: Education is the key. Invest in training and resources to bring your teams up to speed and look for BI and analytics software that supports these advanced capabilities.
It is crucial that you accurately assess your current position – i.e. your level of maturity in data analysis – before setting out on the path to new goals. A Maturity Assessment helps to identify gaps, prioritize investments and develop a roadmap for the further development of analysis functions.
“BARC advises companies as an independent third party and provides extensive information about the BI market. In particular, the classification of BI systems into different application classes helps to better assess the providers and their solutions.
According to the providers, there is a technological solution for everything, albeit a cumbersome one. We can rely on the independent opinion of BARC and will continue to rely on BARC’s expert advice in the future.”
Kurt Hanika Head of Controlling, Wewalka
How do you find the best BI and analytics software for your requirements?
When selecting software for business intelligence or analytics, companies should consider specific criteria such as data integration, security, reporting capabilities and customization options. It is important to choose software that is compatible with existing systems and meets the company’s specific analysis needs.
The selection process should include a thorough evaluation of available options, including a review of product information, customer references and independent assessments such as BARC scores. This helps to make an informed decision and select the best software for the company.
Further information on best practices for software selection can be found here.
Article overview
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Robert is Managing Director and Senior Analyst at BARC Austria. His areas of expertise are analytics, BI and CPM.
He supports companies in all industries in software selection as well as in the design and optimization of strategy, architecture and organization.
Robert has many years of experience managing analytics and BI projects, hands-on expertise with many BI tools on the front end as well as the back end, designing, coaching and implementing reporting, analytics and planning solutions with a focus on self-service BI, information design and advanced planning.
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