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Top Business Intelligence Trends 2023 | Sneak Peek

Let’s explore the landscape of Business Intelligence (BI) in 2023, focusing especially on the most significant trends that are in my opinion shaping the future of data analytics. In this article, I aim to provide a sneak peek of crucial aspects like:

  • fostering a data-driven culture,
  • enhancing data security,
  • embracing data storytelling,
  • optimizing the data stack,
  • and leveraging advanced technologies like augmented analytics and Explainable Artificial Intelligence (XAI).

Moreover, I will discuss emerging challenges and opportunities in the field. This is a shortened version of my previous article covering this subject in more detail. If you’d like to read the full article you can find it here: Top Business Intelligence Trends 2023 | Extended version


Trend 1: Data Governance, Data Literacy, and Data-Driven Culture

The first BI trend for 2023 focuses on the importance of data governance, data literacy, and a data-driven culture. These interconnected concepts are crucial to managing the volume and complexity of data available to businesses. Implementing these principles can lead to improved decision-making, competitive advantage and future-proofing your business. I could name a lot more benefits, like increased ROI, driving business success, building trust, reducing risk but let’s stop here.

Data governance, data literacy, and a data-driven culture are also essential in the face of increasing data privacy and security regulations. Organizations can benefit from robust data governance practices, a data-literate workforce, and a data-driven culture to ensure compliance and security while reaping the benefits of data-driven insights.

To implement these concepts in practice, organizations should focus on developing and implementing data governance policies, fostering a data-driven culture, establishing clear data ownership and accountability, promoting collaboration and communication, prioritizing key data needs and use cases, investing in technologies and tools, and continuously monitoring and improving processes.

Essential tools and technologies to support these efforts include BI and analytics platforms, data governance tools, data catalogs, data literacy tools, master data management tools, data quality tools, data lineage tools, and collaborative workspaces. For more details about specific tools for this trend you can look here: BI Trend 1. Data Governance / Data Literacy / Data-driven culture

Trend 2: Consolidation of the Data Stack

In recent years, organizations have faced growing and convoluted data stacks, leading to complex and inefficient infrastructure. The trend of consolidating the data stack in 2023 aims to improve cost efficiency and streamline operations. By optimizing data infrastructure, businesses can achieve a consistent and reliable view of data, ensuring quality and integrity. The benefits of this trend include reduced complexity, improved data quality, increased productivity, better collaboration, agility, adaptability, competitive advantage, and innovation and growth.

To achieve data stack consolidation, consider adopting a single integrated data platform, standardizing a common data architecture, reducing reliance on legacy systems, adopting best practices for data governance, balancing data virtualization and storage.

Some tools and technologies that can help consolidate the data stack include cloud-based data platforms like Microsoft Azure, Amazon Web Services (AWS), Google Cloud Platform, and Snowflake. Of course there a lot of useful features, but I personally always look for end-to-end lineage for root cause and impact analysis. Preferably automatically scanned. Here you can look into tools like Informatica’s Enterprise Data Catalog, Collibra Lineage, and Microsoft’s Purview. While fully automatic end-to-end data lineage is not always possible, sometimes it’s just a few manual steps that are needed to achieve that.

In conclusion, consolidating the data stack not only offers cost savings and improved productivity but also enables a more agile and responsive approach to changing business needs. This trend should be closely watched as it is likely to be a key enabler of innovation and growth in the years to come.

I’ve written more about this trend here: BI Trend 2. Consolidation of the Data Stack

Trend 3: Separate Semantic Layer

Traditional BI applications tend to couple data modeling and visualization, which makes updates and maintenance challenging. However, the Separate Semantic Layer approach is gaining traction, offering numerous benefits like easier maintenance, quick response to changing business needs.

Some strategies to implement a Separate Semantic Layer include defining the scope and requirements, choosing the right data modeling tool (pretty obvious, right). However, standardizing data definitions and naming conventions is the key part here.

I’ve yet to see a tool that fully implements the concept of a semantic layer, but you can look into dbt (Data Build Tool), Power BI Datamart, Looker, Tableau Prep, and Apache Superset. As the Separate Semantic Layer continues to evolve, expect to see further innovation and advancements in tools and approaches in the BI space.

If you’re interested in reading more about this trend you can it here: BI Trend 3. Separate Semantic Layer

Trend 4: Data Security

Data security is becoming increasingly important as organizations collect, process, and store more sensitive data. The need for robust security measures is heightened as remote work creates new vulnerabilities. To address this, companies are investing in advanced technologies, including encryption, access controls, and threat monitoring, while also complying with data privacy regulations like GDPR and CCPA.

Data tools are evolving to meet these demands, offering features such as data encryption, data masking and anonymization, compliance reporting, and automated data classification. Examples of data governance tools that support data security include Collibra, Informatica, Alation, Microsoft Purview.

As data security regulations grow worldwide, organizations must prioritize strong data governance practices to protect sensitive data and minimize risk. Data literacy among employees is crucial to ensure effective and compliant data usage, making these interconnected aspects of data strategy top priority. In my view Trend 4 (Data Security) is very closely related to Trend 1 (Data Governance, Data Literacy, and Data-Driven Culture) above.

Again, I’ve written a bit more about Data Security as a BI trend here: BI Trend 4. Data Security

Trend 5: Continuous integration / Continuous delivery (CI/CD) and automated testing for BI

As data-driven decision-making becomes crucial, it’s high time for the BI and analytics space to embrace continuous integration/continuous delivery (CI/CD) and automated testing. These practices help streamline the development of BI solutions, ensuring accurate and up-to-date data for better decision-making.

The most important benefits of CI/CD and automated testing for BI include:

  • Rapid iteration and delivery
  • Reduced risk of data inaccuracies
  • Better use of developers’ time for innovation

The slow adoption of CI/CD and automated testing in BI can be attributed to the historical separation of BI and software development processes, as well as the complexity of BI solutions. However, with recent advancements like Microsoft’s deployment pipelines for Power BI Service and more infrastructure as a code approaches, we can expect more organizations to adopt these practices in the coming years.

To find more about the implementations and tools for this trend you can look here: BI Trend 5. Continuous integration / Continuous delivery (CI/CD) and automated testing for BI

The world of business intelligence and analytics never stays still, and the trends shaping how organizations use data to drive success are always evolving. Let’s take a look at some notable trends currently on the rise (If you want a more comprehensive list, you can check the full version of this article here: Top Business Intelligence Trends 2023 | Extended version):

Trends on the Rise

  • Data Storytelling

Data storytelling is all about using data and visualizations to create a persuasive and engaging narrative. Gone are the days when data scientists alone were responsible for presenting analytics results. Today, data storytelling plays a crucial role in organizations, as it simplifies complex information and captivates a broader audience.

  • Augmented Analytics and XAI

The future of augmented analytics could be shaped by pre-trained Large Language Models (LLMs) in natural language processing (NLP) and tools like chatGPT. The emerging concept of prompt engineering might just give this trend the push it needs. I wrote the original version of this article before the GPT-3.5 and GPT-4 models were released, so I was cautiously optimistic and predicted that their impact wouldn’t be significant this year. It appears that I was mistaken. The advance of AI, or rather (as I prefer to narrow it down) Large Language Models’ s progressing at full steam!

Trends on the Decline

While we’ve discussed exciting BI trends, some trends are losing steam, according to the BARC survey and my opinion. The snapshot below shows a decline in the importance of specific BI trends from 2019 to 2023.



I wanted to mention one specific trend where I still see a significant discrepancy between marketing focus and reality.

Self-Service BI and Data Preparation by Business Users: A Dream vs. Reality

Self-Service BI is all about democratizing data analysis, allowing business users to create their own reports, visualizations, and dashboards. While it sounds great in theory and is highly marketed, it’s not always the most practical solution.

Data-mature organizations have specialized teams for building data and visualization layers. It’s not fully in the hands of business users, because self-service analytics can lead to data silos, inconsistencies and hidden data factories. So, while it’s important to promote data democratization and literacy, we must also acknowledge the limitations of Self-Service BI.

Some suppliers are beginning to notice this shift, focusing on trends like embedded analytics, CI/CD, and Semantic Layer to provide more flexibility to BI developers. The key takeaway? Striking the right balance between self-service and centralization, governance, and data quality is crucial for organizations.

Embracing the Future of Business Intelligence: A 2023 Outlook

As we wrap up our exploration of the top Business Intelligence (BI) trends for 2023, it’s evident we are navigating an exhilarating era. With a mix of emerging trends and technologies, we’re witnessing the creation of new pathways and the evolution of established ones. Some once-popular trends may be losing ground, but others are gaining increased significance.

It’s going to be intriguing to see how these trends shape the BI and analytics landscape. Keep in mind that these are just my opinions, and I could be proven wrong. However, one thing is certain – the world of BI is continuously changing. Our responsibility is to stay ahead of the curve and embrace the transformations on the horizon.

Contributed By:


Marek K. Zieliński

Chief Technology Officer and Co-Founder, 10 Senses

Marek is a co-founder of 10 Senses, a company focused on advanced analytics solutions including AI and process mining. With over 10 years of experience in data-related fields, Marek specializes in data engineering, data visualization, ML/AI, and process analytics, and actively shares his expertise through conferences, meetings, and training sessions.


10 Senses

10 Senses is a Warsaw-based team specialising in data science, AI and process mining. We support companies in their daily data-related tasks. Our team has broad experience in advanced analytics and dealing with business challenges using cutting-edge technology.

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