2024 was a defining milestone for Qlik, as highlighted in our previous review by our Business Intelligence Lead and Managing Partner, Phuoc Tran Minh, in early 2025. Strategic goals were met, and the integration of Talend solidified Qlik’s position as the market’s most robust data integration platform.

But what lies ahead? 2025 and the beginning of 2026 have marked a fundamental shift in the ecosystem: moving from passive reporting to active, “agentic” analytics. Here are the key innovations shaping the daily operations of Qlik users right now.

1. From Assistant to Agent: The Rise of Agentic AI

If 2024 was the year of experimenting with Generative AI, 2025 was the breakthrough year for Agentic AI. Qlik no longer simply answers questions; it takes action.

These new AI agents execute complex sequences of tasks autonomously. They can detect an anomaly in sales data, analyse the root cause by comparing multiple data sources, and automatically generate a proposal for next steps – all without the user needing to build a query. Qlik Answers is pivotal here, integrating unstructured data (contracts, manuals, PDFs) into the analysis to ensure a true 360-degree view of the organisation.

2. Qlik Trust Score™: AI is Only as Good as Its Data

The biggest barrier to AI adoption is a lack of confidence as we know at GOODIN. Qlik addresses this with the Qlik Trust Score for AI, which automatically scores the reliability of data. As businesses build their own custom models on top of Qlik, the Trust Score ensures that AI does not draw conclusions based on flawed or outdated information. It is the “green light” management needs for automated, defendable decision-making.

3. The February 2026 Breakthrough: The Qlik MCP Server

The most significant update in early 2026 is the general availability of the Qlik MCP (Model Context Protocol) Server. This is a game-changer for AI Interoperability.

Rather than locking your data inside a single platform, MCP acts as a universal “USB-C port” for AI. It allows third-party assistants – such as Anthropic Claude, Microsoft Copilot, or your own internal LLMs – to securely “reach into” Qlik’s engine. This means your external AI tools can use Qlik’s governed measures and logic to provide answers that are actually accurate and grounded in your business reality. Here is more info!

“Qlik has gone so far beyond visualisations and dashboards: it has become the trusted intelligence layer for your entire enterprise AI ecosystem.”

Says Phuoc Tran Minh

4. Next-Level Integration: The Open Lakehouse

The Qlik-Talend merger has matured into a seamless Open Lakehouse architecture. In 2026, there is a massive emphasis on real-time data movement across Snowflake, Databricks, and AWS. Native support for the Apache Iceberg format allows enterprises to store vast quantities of data cost-effectively while avoiding vendor lock-in. Data quality is now managed by AI-assisted tools that rectify errors automatically as data moves through your pipelines.

5. User Experience: Beyond the Dashboard

Analytics visualisation has undergone a significant makeover to drive operations, not just viewing: Write-back Capabilities: Users can now modify or input data directly from a Qlik sheet back into source systems (like CRMs or ERPs). Discovery Agents: New “always-on” agents monitor your metrics 24/7 and proactively alert you to meaningful trends or anomalies before you even open a dashboard.

Conversational Interface: Interacting with data through natural language is now the standard. The dashboard has evolved from a primary interface into a supporting visual for deeper context.

Towards Autonomous Analytics

At GOODIN, we have followed Qlik’s journey closely, and the direction is clear: analytics is shifting from the “rear-view mirror” to real-time operational guidance. The Qlik MCP capabilities added in late February 2026 represent a “safe harbour” moment – providing a standardised, governed way to connect any AI tool to your most valuable data.

“The innovations of 2025–2026 represent a new era where data is a company’s most active asset. Agentic capabilities are already delivering massive value to end-users by automating the “boring” parts of data analysis and focusing on what matters: action.”

says Mikko Kuusela.

Is your organisation ready to leverage Qlik’s latest Agentic and MCP capabilities? At GOODIN, we help you translate technology into measurable business value and can train your entire organisation to make use of data and AI.

Reach out to our CEO Jarmo Rajala or Mikko Kuusela, Petri Viljanen, or Siru Saaristo. We are happy to help you find better ways to get the most out of your data and AI!

Our Business Development Lead Mikko Kuusela has worked in analytics for nearly three decades. This is the story of what he learned – and why one question stayed with him the entire journey.

Mikko has a habit of saying that his career has become more technical than he ever imagined as a young economics student.
But perhaps that’s exactly why he has held so firmly to one core idea. The most important job of technology is not to look complex. Its job is to help people succeed.

Where it all began

The year is 1997. Mikko starts his career at BasWare, working with budgeting and forecasting systems. Oracle consulting follows, then reporting, then business. Early on, a conviction takes shape that never changes:

The best solutions do not emerge on technology’s terms. They emerge when technology genuinely serves the business – with people at the centre.
In 2005, Mikko returns to BasWare and encounters QlikView. It changes his thinking. It is no longer just about reporting, but about analytics: the opportunity to understand the business more deeply, to spot patterns, to make better decisions.

#Qlik technology has been part of his career ever since. Around 20 years in total, more than 15 of them with Qlik directly.

The question that never went away

Alongside everything he learned, one thing kept nagging at Mikko. What if data entry could live in the same interface?
If viewing, analysing, and updating information could all happen in one place, a solution like that would serve the business in an entirely different way. No separate Excel files. No system-hopping. No unnecessary intermediate steps.

It’s a question he has heard from clients over the years countless times, too.

The answer arrived six months ago.

About six months ago, Mikko came across #Inphinity. He was immediately excited.

Inphinity enables data entry directly within Qlik – in the same interface where data is also analysed. No more separate processes, no more separate systems. One environment, one whole.

The concrete impact was visible quickly. In a client project, key metrics from around 50 companies were brought together into a single Qlik environment. Data entry, review, and utilisation – all in one place. It worked.

Why this matters – from a data empathy perspective

At GOODIN, we talk about data empathy. It simply means that data and solutions are not built for systems – they are built for people. Understanding users’ day-to-day reality and understanding what stories the data tells. Understanding the genuine needs of the business. Building something people will actually use.

When the process feels natural, users trust the data. When users trust the data, the organisation makes better decisions.
That is exactly what Inphinity delivers – and exactly what Mikko’s story is about.

30 years in analytics creates a certain level of #DataEmpathy

“The job of technology is not to look complex. It’s job is to help people succeed.” — Mikko Kuusela, GOODIN

#GoodIn #DataEmpathy #Qlik #Inphinity #Analytics #PeopleOverProcesses

So Why Bother with Data Utilisation Design?

You can think of data as this treasure trove of insights just waiting to help you make your next big move. It is not just about having loads of data as data that is not used is a waste of money; it is about knowing what to do with it and actually utilising it. But naturally if you have not thought about the why’s, what’s or how’s that can be hard. So we collected a list to help you on the way. Here is why you should care about data utilisation design:

• Make Smarter Decisions: When you base your decisions on what the data is telling you, it is like having a crystal ball kind of. It means you are making moves based on what is actually happening, not just gut feelings. And the best scenario is of course to combine the data with you gut feeling as that should not be undervalued either as it is usually data that comes from experience.
• Stay Agile: Markets move fast, and data helps you keep up. You will see the trends as they are happening, so you can steer your team in the right direction without missing a beat.
• Spot Risks and Opportunities: It is like having a map and a flashlight in a dark cave to put it in a simple analogy. Data helps you see where the pitfalls are and where the gold is hidden.
• Keep Your Customers Happy: By understanding what your customers are into, you can tailor what you do to match their expectations. It is a win-win – they get what they want, and you get their loyalty.
• Drive Innovation: Data is POTENTIALLY a goldmine of insights that can spark new ideas. It is all about finding better ways to do things, making your business stand out and the knowledge of market trends, opportunities, cross-level cooperation and so forth are human-led but when backed up by data the delivery can really help you jump over several hurdles.

The importance of data utilisation design for business leaders cannot be hence overstated. It is a critical competency that enables leaders to navigate the complexities of the digital age with confidence and foresight.

In the journey towards data-driven excellence, the role of leaders is not just to manage data but to inspire a culture where data is a strategic asset, driving every decision, every innovation, and every success together with the human aspect that lead the change.

Here is a To-Do List for you to think about when wanting to get started:

Here are the first few steps to take that’ll set you on the right path:

1. Set Clear Goals: Decide what you want to achieve with your data and and your people. It could be improving customer satisfaction, boosting sales, or streamlining operations. Having clear objectives will help you focus on the data that matters and help your people understand how to utilise it.
2. Get to Know Your Data: Take a moment to understand what data you already have, where it is coming from, and how it is being used and if it is not being used, why? It is about getting the lay of the land before you start digging deeper.
3. Build a Data-Savvy Team: Surround yourself with people who get excited about data! If your team can understand and use data effectively, you are already halfway there. There are several methods and services available to enable change with for instance GOODIN and Splended designed data learning sprint to get everyone up to speed.
4. Invest in the Right Tools: There is no shortage of tools out there to help you collect, analyse, and visualise data. Find the ones that fit your goals and your budget. It is about making your life easier, not more complicated.
5. Start Small and Scale Up: You do not have to build the full picture in one go. Rome wasn’t built in one day either. Start with a small project or area where data can make a difference, learn from it, and then gradually expand your data initiatives.

We are also happy to help to get you going so just be in touch!

Generative AI has emerged as a transformative force, impacting all facets of an organization and influencing existing tools and solutions. While it enhances efficiency, Generative AI introduces new requirements for data structures, security protocols, and corporate governance within organizations. Despite its capabilities, it’s crucial to note that Generative AI doesn’t assume responsibility for decisions and actions; that remains the responsibility of human operators.

To realize the full Return on Existing Investments (ROIe), organizations must ensure that users maximize the utilization of these tools and solutions. While significant investments are made in technology, equal attention should be given to nurturing the skills of the teams, the potential generators of profit. It is imperative to monitor how users leverage these investments actively. The real value lies not just in the technology itself but in how effectively it is utilized by individuals within the organization.

Data Empathy – a Holistic Approach

When investing in new technology, organizations must concentrate on three primary areas. The principal impetus for any investment typically originates from business needs and potential benefits. The technology team plays a pivotal role in narrowing down and selecting appropriate technologies for the identified requirements. In theory, collaboration between business and technology teams can yield flawless reporting systems and dashboards. However, the recurring challenge lies in the third crucial area – the organization.

The diagram above illustrates the common areas for any organization and their interdependencies. In Data & BI projects, collaboration between Business and Data & Tech teams is typical. However, the ultimate success is contingent upon whether people use the solutions, find them easily applicable in their roles, and whether the business demands their usage, all of which require continuous monitoring.

To achieve Return on Existing Investments (ROIe), it is crucial to identify user needs through Work Design. Understanding the information required for everyday tasks, assessing data skills and literacy, and providing targeted training and coaching are vital. Leadership, management systems, and organizational culture play pivotal roles in achieving ROIe, impacting the human element significantly. Without an organizational emphasis on data use, investments may not yield expected results.

The path to realizing the full return on existing investments involves focusing on the organization and its people, embracing Data Empathy.

Decision Dimensions – Aligning People, Processes and Data

Management Information Systems are 90% people said my professor in 90’s. Today we have so much new and existing tech that we might not remember this truth. We are blinded by expanding number of technologies and solutions and often users are not able to keep up with the pace of development. Introducing new systems alone is insufficient; attention must be directed towards role design. This entails understanding how work aligns with the new system, necessitating changes to fully realize the benefits of the investment.

Aligning People, Processes and Data. People within an organization occupy specific roles, belong to teams, and engage in processes where decisions take place. To enhance data utilization and identify gaps in both people’s capabilities and data availability, an understanding of work design is essential. Mapping out a user’s typical day, identifying decisions tied to processes, and determining data requirements for those decisions are critical. Data presentation should align with actionable intelligence requirements, meeting the demands of users and fostering motivation for increased data utilization. Importantly, it’s essential to identify the role of GenAI/LLM solutions in the user’s daily workflow, not just focusing on technical solutions.

In conversations with numerous leaders and data & BI professionals, it’s surprising how little attention organizations have given to their people. While many have heavily invested in Cloud Data Platforms, AI solutions, and BI fronts, acknowledging that people are the biggest challenge in reaping the full benefits of these investments, very few have taken tangible steps to bridge the gap between people and data.

Now it is time to do just that.

The missing link? Data literacy.

At GOODIN we have observed firsthand the transformative impact of nurturing data literacy within an organisations, particularly from a data governance perspective.

Data Literacy: The Foundation of Data Governance

Data governance is not just about managing data; it’s about managing the people who interact with that data. It is about creating an environment where data is not just available but is also understood, trusted, and effectively used. This is where data literacy comes into play. By educating employees across all levels of the organisation in the language of data, we empower them to make informed decisions, recognise the value of data assets, and adhere to governance protocols. 

Bridging the Data Knowledge Gap

The journey towards data literacy starts with recognising that different roles require different levels of understanding. For instance, your marketing team does not need to know how to run complex data models, but they should understand how to interpret data insights relevant to their campaigns. Tailored training and workshops can bridge these knowledge gaps, ensuring that each team member has the right tools and understanding to leverage data effectively.

Fostering a Data-Centric Culture

When people understand data, they respect it. This respect is critical for effective data governance. A data-literate workforce is more likely to recognise the importance of data quality, privacy, and security. They become active participants in maintaining the integrity of data, rather than passive users or reactive receivers that actually do not use the data available.

Moreover, as data literacy spreads, it cultivates a data-centric culture where decisions are made on a foundation of solid data – in conjunction with gut feelings, a type of internal and experience based ‘data’ that should not be underestimated either.

The Role of Leadership in Data Literacy

Leadership plays a pivotal role in this cultural shift. By championing data literacy and setting an example, leaders can drive the message that data is a valuable asset worthy of investment.

This is not just about allocating budget for training programs; it is about embedding data literacy into the fabric of the organisation’s ethos and this is where leadership has a central role.

The journey towards effective data utilisation is twofold: it’s about having the right technology and about ensuring your people are equipped and enabled to use it. Data literacy is not just a skill; it’s an essential component of a robust data governance framework. 

Data is in the end about telling stories and as telling stories is embedded in people, transforming an organisation’s culture increasingly towards one of storytellers helps also the development of data literacy as empathy is the superpower humans have and applying it to data creates the most wonderful stories!

Oh but How do I Get Going?

Imagine setting your sights on a luminous northern star – a vivid, inspiring vision of where you aspire to be say in, for instance, three years from now. With this beacon guiding your way, you take measured, thoughtful steps, one after the other, steadily building a future rich with empowerment and enlightened by data. Each stride forward is a meaningful progression, a step closer to a culture where data literacy enhances every decision, enriches every strategy, and elevates your organisation to new heights of innovation and insight.

Embarking on the path to foster data literacy within your organisation is a voyage of transformation and growth, not a race to an immediate finish line.  

We are of course happy to help you along your journey – please – just get in touch!

Picture this: a business leader, with a sprinkle of data curiosity, and a data wizzard, with a dash of business intuition, come together. They stand in front of a whiteboard, their ideas flowing and merging. It is in these moments that the real magic unfolds, beautifully blending “what can be done” with “what the business truly needs.”

Now, business leaders are the maestros of understanding market dynamics, the ever-evolving customer behaviour, and those subtle strategic moves that steer your company forward. You have that innate sense of “what is needed” – whether it is identifying market voids, understanding customer pain points, or sniffing out the next big innovation. And while you appreciate the might of data, its finer intricacies might sometimes feel a tad out of reach. You also may have design-thinking experts in your fold, bringing about the out-of-the-box and customer-centric approach.

And here is where the data champions step in. In our world that thrives on data, these professionals are not just number-crunchers. They’re storytellers, pattern-detectives, and visionaries. They hold the keys to “what’s possible” using their vast knowledge of analytics and algorithms. But without the bigger business picture, sometimes their solutions can feel like they are missing a piece of the puzzle. Together we can patch the gap between Business and Data. We learn the language of the other competence and we strive to understand and cooperate.

So, when these worlds collide – say, over a casual whiteboard session – something truly special emerges. The creative business leader lays down a challenge, and our data guru counters with data-driven solutions. By working hand in hand in an ideal world they sculpt ideas and solutions that might’ve seemed impossible in isolation and create solutions that resemble pieces of art.

This harmonious dance of insights and strategy opens avenues for groundbreaking products, smoother operations, and delightful customer experiences. It is a kind of alchemy – a magic rooted deep in teamwork, mutual respect, and combined expertise and the understanding of each others competence as well as the understanding of your own limits.

To wrap things up, merging business smarts with data insights is not just a nice-to-have—it is a game-changer in our dynamic, data-rich era. When we encourage this heartwarming meeting of minds, we are not just connecting dots; we are drawing the roadmap to future innovation where also the enablement of the utilisation of data in organisations is at the core.

And as the brilliant W. Edwards Deming once said:

“Without data, you’re just another person with an opinion.”

But remember, data without context is like a book without a storyline and data that is not available or easy to use is not valuable, so make sure your data is useful and your people know how to utilise it.

Let’s always aim for the best of both worlds!

Business Intelligence (BI) has emerged as a cornerstone for organisations, providing tools and techniques to turn raw data into actionable insights. Something GOODIN’s Jarmo Rajala has been consulting on for two decades.

But what is the real-life impact of data and BI on decision-making, and how can AI enhance this process? This is the high-level topic of The AI MIXER GOODIN is hosting together with Nieve and Fusion Ecosystem this week.

GOODIN’s very own Atte Ailio has been on the implementation side leading processes of tech and BI investments for 20 years and has a clear idea of the issues related to actually getting people to get involved.

From a company perspective here are probably the corner stones of why leveraging BI and AI is important in the future:

1. Informed Decision-Making: The impact of data and BI on decision-making is profound. By analysing historical data and current trends, organisations can make informed choices about strategy, resource allocation, and operations at large and in detail. Real-life benefits include cost savings, improved efficiency, and better customer as well as staff experiences.
2. Predictive Analytics: AI plays a pivotal role in BI by enabling predictive analytics. Machine learning algorithms can forecast future trends and outcomes based on historical data. This empowers businesses to proactively address challenges and seize opportunities, leading to more confident decision-making. And as change is the only certain constant, having some predictive analytics to help you with your decisions is pretty invaluable.
3. Personalised Experiences: Data and BI are instrumental in understanding customer behaviour. AI-driven personalisation takes this a step further by tailoring experiences, products, and services to individual preferences. The impact is seen in increased customer satisfaction, loyalty, and revenue. And this does not always have to mean massive investments as we learned at the Google Cloud Summit.
4. Risk Management: Businesses can use data and BI to identify potential risks and vulnerabilities. AI algorithms can continuously monitor data streams and alert decision-makers to emerging threats. This proactive approach can mitigate financial losses and protect a company’s reputation.
5. Resource Optimisation: AI, when integrated with BI, can optimise resource allocation. Whether it’s managing inventory, workforce scheduling, or marketing budgets, AI-driven recommendations help organisations allocate resources efficiently and cost-effectively.
6. Real-time Insights: In a fast-paced world, real-time insights are invaluable. AI-driven BI systems can process data streams in real time, allowing businesses to respond to changing conditions instantly. This agility is vital in industries such as finance, e-commerce, and healthcare to name but a few.

And last but most definitely not the least:

Improved Quality of Life: The impact of data, BI, and AI is not limited to business alone. In healthcare, for example, these technologies facilitate early disease detection, leading to better patient outcomes. In sustainability questions data is vital.

As a concrete example of this is for instance the enhancing the quality of life on a personal level when thinking of the commute to home or work when Data and AI is utilised in urban planning. With the help of them it is possible to effectively optimise traffic flows hence reducing for instance commute times.

The available technologies empower organisations to make informed choices, optimise resources, and deliver personalised experiences. When combined with AI, the benefits are multiplied, enabling predictive analytics, real-time insights, and risk management.

The Learnings?

The synergy of data, BI, and AI is transforming industries. To remain competitive businesses must embrace this data & AI revolution BUT NEVER forget about the human in the middle.

Want to talk with us some more?

Atte Ailio, Jarmo Rajala, and Kira Sjöberg, each possessing distinct expertise, united to shape a transformative path for data. The aim: to rewrite the rules of data utilisation, introducing a new era of people-driven business intelligence and data wisdom.

Conception of a Bold Vision

Atte, a business-savvy BI expert with a knack for identifying industry trends, had noticed a gap in this during his extensive career in different industries working in finance lead roles. While data-driven decisions were written in the strategy, the disconnect between data and the human element remained evident. Recognising this opportunity, Atte had imagined a place that would empower organisations to unlock the potential of their data while placing people at the heart of decision-making.

The Analytical Maven

Jarmo, a seasoned expert in business intelligence technologies, had witnessed firsthand the untapped potential within the use of data even with the leading technologies that he previously worked with. 

Jarmo was driven by a passion to empower businesses with actionable insights derived from data analysis but remained frustrated over the course of 25 years when the data often remained unutilised. Recognising Atte’s vision as a catalyst for change, he became intrigued by the idea of merging technology with human-centric principles.

Designing the Human Experience

Enters Kira, a design thinking and organisational psychology enthusiast that had in her work struggled with the gap that existed between the potential of data and how people could utilise it – if they only were enabled and empowered by organisations to do so.

With an understanding of how people interact with technology and organisations, Kira was captivated by the possibility of bringing design thinking and psychology to the forefront of data utilisation- creating data literate cultures for organisations. She saw an opportunity to create an environment where data-driven decisions were not only intelligent, but also aligned with the needs and aspirations of individuals enabling a data-driven future. 

The Convergence

The trio’s paths converged through fate when Riikka Uimonen from Fusion Ecosystem connected them and a shared purpose was born. Discussions over coffee turned into a series of brainstorming sessions that fueled their collective vision around this recognised pain point in the market. The decision to embark on this journey was made, and their complementary skills formed a foundation for the venture.

Crafting the Solution

Months of tireless collaboration followed. Atte’s knack for business structures, Jarmo’s analytical rigor and tech knowledge, and Kira’s design thinking prowess blended seamlessly. 

They envisioned a company that would not only help with technical data questions, but also enable organisations to understand the psychology behind decisions people make. This fusion of technology, business intelligence, design thinking, and organisational psychology gave birth to a solution that placed individuals at the forefront of data transformation – with the aim to bridge the gap between Business and IT.

From Idea to Reality

The team navigated the intricacies of technological development, fine-tuned user experiences through iterative design, and integrated principles of organisational psychology and the question of how to concretely create a change. Along the way, they engaged industry experts, conducted extensive research, and even sought feedback from potential customers to understand the true use cases and gaps in the market that no-one else filled.

Empowering a Paradigm Shift with GOODIN

The vision is that organisations will marvel at the way data could in the future be harnessed to not only drive profits, but also foster innovation and elevate the human experience, especially when AI and automation is involved.

As GOODIN is part of Fusion Ecosystem – an alliance of 30+ digital development companies accelerated by Reaktor – this vision is possible as the ecosystem enables access to the best possible expertise within the digital realm. 

GOODIN’s core is in helping you enable your data – be it BI, AI and IoT – to create a business advantage for your organisation. 

For this to be possible hard data must be paired with soft empathy – the superpower of humans. Only then can you empower good insights.

The Dream: A Transformation towards a Positive Change with Data Wisdom

What Atte, Jarmo and Kira hope for is that this collaborative journey will come full circle. The dream is that this venture not only transforms data utilisation, but also inspires a paradigm shift in how organisations approach decision-making to create a business advantage. 

The unison of GOODIN showcases how diverse expertise, a shared purpose, and a people-driven approach could reshape industries and create a lasting legacy of positive data-driven change on many levels in businesses.

GOODIN is a dream workplace for people who share the vision of how data is utilised in companies and want to build business intelligence solutions that are used and create actual value for organisations across industries.

#GOODIN #Dataempathy

Data empathy is a term within data science and research and it is also known as empathetic data analysis. The term refers to the practice of approaching data analysis with a deep understanding and consideration of the human experiences and emotions that the data represents. 

It involves recognizing that behind every data point or statistic, there are real people, stories, and contexts that contribute to the information being presented. Data empathy encourages analysts to go beyond the numbers and charts.

Data empathy is at the core of GOODIN and helps you to do with your business data.

• Human Stories: Each data point can be linked to a human story. Data empathy encourages researchers to uncover and share these stories to provide a more comprehensive and relatable perspective on the data.
• Bias and Representation: Data can carry biases due to various reasons, including the way it was collected or the inherent biases within the systems that generated it. Data empathy involves acknowledging these biases and working to address them.
• Ethical Considerations: Empathetic data analysis involves ethical considerations about how the data was obtained, used, and shared. Researchers should ensure that privacy and confidentiality are respected and that the data’s impact on individuals and communities is taken into account.
• Inclusivity: Practicing data empathy requires an inclusive approach to data collection, ensuring that the data collected represents a diverse range of perspectives and experiences.
• Understanding Context: Data points often don’t exist in isolation. They are influenced by various factors such as social, cultural, economic, and personal contexts. Data empathy involves taking the time to understand the broader context in which the data was generated.
• Respecting Privacy: Data empathy emphasizes the importance of respecting individuals’ privacy when working with personal or sensitive data. An empathetic approach ensures that individuals are not harmed or negatively affected by the use of their data.
• Avoiding Dehumanization: In large datasets, it’s easy to lose sight of the fact that each data point represents a person or a group of people. Data empathy helps prevent the dehumanization of individuals by keeping the human aspect at the forefront.
• Storytelling: Data empathy often involves telling stories that incorporate data to convey information in a way that resonates emotionally with the audience and in a business context makes the data work for the organisation.

By practicing data empathy, analysts and researchers can create more accurate, meaningful, and impactful insights that consider both the quantitative aspects of data and the qualitative human experiences behind it.

Data is – afterall – People Business.