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Data storytelling: an end-to-end
concept overview with examples
July 1, 2025
Data storytelling combines data, narrative, and visuals to help make complex insights more accessible to stakeholders, enabling them to discover trends in data, make informed decisions, and take actions that drive significant business results.
With solid experience in data visualization services, Itransition helps businesses adopt a data storytelling approach to build tailored data narratives and make sure the insights are easily understood and grasped by all stakeholders.
Key elements of data storytelling
Data storytelling comprises three main components that help turn raw data into meaningful, actionable insights.
Data
Data, both structured and unstructured, serves as a foundation for generating insights and creating data stories. Real-world data can be collected from internal systems (CRM, ERP, web analytics, marketing automation, and HR tools, corporate databases, and data warehouses) and external data sources (social media, reports, financial market data, and publicly available benchmarks).
Narrative
The narrative involves a clear explanation of what the data means in a structured manner. The narrative should be based on actual data and have several fundamental elements, such as a beginning, middle, end, and a clear objective or message. It should also have a “hero” or characters who are key players and stakeholders of the story, such as the target audience, customers, or teammates.
Visuals
Visual representations include charts, graphs, diagrams, infographics, or videos that help users present textual information in a more engaging way and spot trends that are not evident in spreadsheet rows and columns or text.
Core capabilities of tools for data storytelling
Data integration
In order to create a detailed story, software solutions for data storytelling should be able to access all relevant data within the organization. To ensure it, they should provide native data source connectors and APIs or support data virtualization. Software enabling data storytelling should also offer built-in ETL (extract, transform, load) capabilities, as well as schema mapping and real-time synchronization to supply users with clean data, facilitating accurate analysis and, ultimately, the creation of more reliable data stories.
Data visualization
In order to create a detailed story, software solutions for data storytelling should be able to access all relevant data within the organization. To ensure it, they should provide native data source connectors and APIs or support data virtualization. Software enabling data storytelling should also offer built-in ETL (extract, transform, load) capabilities, as well as schema mapping and real-time synchronization to supply users with clean data, facilitating accurate analysis and, ultimately, the creation of more reliable data stories.
By integrating machine learning, natural language processing, and automation, tools supporting data storytelling streamline data collection, analysis, and querying for non-technical users. Thanks to augmented analytics, users can ask questions and get answers about data in human language. Additionally, the tool can provide suggestions and predictions based on the identified correlations in data, continuously improving result accuracy as more data is processed and learned from.
Collaboration
Tools that facilitate the creation of data stories enable cross-functional collaboration with features such as shared environments or workspaces, links to provide others with access to reports or dashboards, shareable snapshots, and the ability to embed reports into collaboration tools, presentations, or websites. Depending on the access level, these features allow team members to view and edit data stories, discuss reports in real time, and leave comments, facilitating the decision-making process and team alignment.
Data security & compliance
As data becomes more accessible to broader groups of users, tools enabling data storytelling should protect data privacy and comply with relevant data security laws, such as GDPR or HIPAA. Data security features to look for include row-level and object-level security, role-based permission controls, data encryption at rest and in transit, data masking, data anonymization, activity logs, and multi-factor user authentication.
Simplify complex data analysis through powerful data storytelling
Best tools for enabling data storytelling
Data storytelling can be facilitated through dedicated data visualization tools, full-fledged BI platforms, and programming languages. Here are the most popular BI and data visualization platforms that have comprehensive capabilities for building data stories and are named as Leaders, according to the recent Gartner Magic Quadrant.
Power BI
Power BI is a business intelligence tool with extensive data visualization and storytelling capabilities for creating compelling stories with data. Specifically, the platform offers an intuitive interface, prebuilt report templates, AI capabilities, and natural language Q&A to facilitate the exploration of patterns, opportunities, and anomalies in the data.
- Out-of-the-box visuals, including charts, decomposition trees, and maps
- An extensive library of customizable visuals, including interactive SVG graphs, visuals with custom logic, and advanced visuals for statistical analysis
- Interactive capabilities, such as drill-down, drill-through, zoom, pan, tooltips, filters, and highlighting
- AI-powered capabilities, including automated data analysis, anomaly detection and explanation, generation of narrative summaries, and support for natural language
- Interactive report tooltips to add visual elements to report pages
- Flexible customization of report structure and navigation
- Autogenerated quick reports
- Native integration with Teams, allowing users to directly attach reports and scorecards to the meeting invite, open and present reports from the calendar, and send a summary with the key results
- Built-in accessibility features, such as keyboard navigation, screen-reader compatibility, and high contrast color mode
- Can be accessed through a web browser on a PC and/or tablet and through a mobile app
Tableau
Tableau is a business intelligence platform, providing a wide range of visualization and customization options. The company also puts strong emphasis on integrating AI to simplify data analysis and insight generation.
- Ready-to-use, customizable dashboard templates
- Auto-generation of plain-language explanations for data
- Forecasting and predictive modeling
- Geospatial visualization for location-based insights
- The ability to embed images, logos, and icons into visuals
- Unified tooltips, providing context to reports
- LOD expressions to perform complex, granular calculations across different levels of detail within their data
- Drill-down, zoom, pan, and metric muting capabilities to focus the analysis on specific data points
- Advanced analytics and predictions with R, Python, and Einstein Discovery
- Slack integration for real-time collaboration on data
- Year-over-year (YoY) growth and custom date comparisons
- Alerts for concerning data trends
Looker Studio
Looker Studio is a business intelligence solution that enables self-service data analysis and the creation of data stories, providing rich visualization options and more than 800 connectors for instant access to the needed data.
- Drag-and-drop interface with snap-to-grid design
- Customizable dashboards and visuals, including charts, maps, and treemaps
- Pre-built report templates
- Report embedding into any web page or intranet
- Chart styling capabilities, including colors, line styles, bar labels, and borders
- Filters, drill actions, and sorting capabilities
- Field descriptions in tooltips for additional context about the data
- Scheduled report deliveries
- Integration with Gemini to ask questions about data, perform calculations, and import content into Google Slides presentations using natural language
Qlik Sense
Qlik Sense represents a robust business intelligence and analytics platform with interactive visualizations, capabilities for self-service data preparation and analysis, and a dedicated data storytelling feature. Qlik provides intelligent and in-context commentary for the data analytics visuals, creating a complete data story to help users draw insights from the data and generate reports.
- Versatile interactive and customizable visuals, including charts, box plots, histograms, and treemaps
- Storytelling snapshots capture
- Contextual annotations to include more information about the snapshot
- Bookmarks for quick access to the live data
- Slide-based story creation with drag-and-drop controls
- Design tools, including text titles, descriptions, visual effects, and shapes
- AI-powered dashboards, generating answers and predictions
- Natural language support
- Automated insight generation
- Alerts triggered by changes in the data
10x
increase in data processing speed
Pharmaceutical data analytics suite
Our experts redeveloped a BI platform and delivered standalone KPI management, data management, and data visualization apps. These solutions enable the client to explore data, visualize market and sales metrics, and build product launch, demographic, and sales reports within minutes using interactive features.
31%
growth in lead-to-opportunity conversion
BI solution for case study coverage analysis
Itransition’s BI team developed an analytical suite for evaluating case study coverage. The solution includes a case study scoring system, an expertise scoring system, and dynamic dashboards for users and administrators. It allows users to determine case study coverage across numerous industries, technologies, and solutions, providing visual clues indicating well-covered areas and areas needing improvement.
90x
reduction in data upload time
BI for incident management
Itransition’s experts delivered a customizable BI solution for collecting, analyzing, and visualizing incident data, equipped with graphs, charts, diagrams, and a geolocation map. The system processes and displays both historical and current data, visualizes trends in different locations, and provides monitoring tools to help users track business-specific parameters, derive incident data insights, and build data stories on this basis.
2-fold
speedup in project deliver
Power BI implementation & employee training
Itransition’s specialists helped a client streamline the data analysis process by implementing a business intelligence tool and performing comprehensive user training. Our specialists also designed easily digestible reports that can be exported, printed, and displayed on big screens, as well as created an analytics module with interactive features that enable ad performance exploratory analysis.
Benefits of data storytelling
Accelerated decision-making
Data storytelling makes data analyses more readily understandable, helping users make decisions faster without spending hours deciphering complex figures.
Higher confidence in decisions
Data storytelling allows for the predictability of business decisions, making users more confident in the outcomes of their choices and actions.
Improved access to critical insights
By drawing attention to key data points and enabling users to understand all the data, a good data story diminishes the chances of missing critical trends or patterns.
Facilitated cross-team collaboration
By presenting data insights in a language adapted to non-technical users, data storytelling enables different teams and departments to cooperate more effectively, exchange key insights, and work toward common goals without relying on data analysts or data scientists.
Data democratization
Storytelling with data entails making complex information more accessible to a broader range of employees to enable them to make data-driven decisions and learn how to interpret data, relationships, and patterns themselves, improving their analytical skills.
Data storytelling challenges
Challenge | Solution | |
|---|---|---|
Data silos |
Data produced by different departments often remains isolated from the rest of the organization, hindering
the creation of comprehensive data stories.
| Bringing together data from disparate sources requires a centralized data repository, such as a data warehouse, data lake, or lakehouse. However, if you want to access data without physically moving it, consider utilizing data integration approaches like federated querying. Additionally, implementing an enterprise service bus (ESB) can help connect systems and enable seamless data exchange. |
Data inconsistency |
Relying on several data sources and analytics tools often leads to data inconsistency as teams can use
different terminology to define the same notion, causing confusion and errors during the development of a
data story.
| Introduce a comprehensive data governance and quality management framework, enforcing consistent policies, processes, and tools for managing data. For example, establish uniform data formats, naming conventions, and units of measurement, such as currency, weight, and length, for diverse teams, create data glossaries with the preferred definitions, and utilize data quality tools to cleanse incorrect, duplicate, and outdated data. |
Lack of employee buy-in |
Employees can oppose the need to create data stories, seeing it as an unnecessary step and an added burden
when they can simply analyze and visualize data as usual.
| Nurture a data-driven culture within your company, showcasing the benefits of data storytelling and encouraging data storytelling advocates to share their tips on using data insights for building data stories. Gather user feedback on the proposed data storytelling procedures and offer support and mentorship to eliminate roadblocks during data story generation. |
Adopt a data storytelling approach risk-free
Data storytelling best practices
Focus on the target audience
When choosing software to enable data storytelling capabilities, consider its end users and their level of data literacy. Engage business users right at the planning stage and identify their expectations, pain points, and needs to select the tool that will deliver the required functionality.
Add context to the data story
Effective data storytelling relies on using context to see what impacts the given metric. To ensure this capability, look for tools that provide features such as annotations, event overlays, combo charts, and benchmarking to add contextual explanations to the datasets.
Provide an easy way to share stories
Choose the right data visualization tools that feature comprehensive collaboration capabilities, such as shared dashboards where different stakeholders can access and explore data in real time or automated delivery of reports via email for users to get updated data at a predefined time.
Ensure ongoing employee training
Help employees develop data storytelling skills, including data visualization, effective presentation, and narrative creation, by providing access to dedicated courses, webinars, and books and conducting in-house training sessions tailored to specific user roles.
Data storytelling market insights
Data visualization solutions market trends
Scheme title: The growth of the global market for data visualization tools
Data
source: The Business Research
| The data visualization tools market is expected to be valued at $30.7 billion by 2032 | |
|---|---|
| The global market for data visualization tools is expected to grow at a compound annual growth rate (CAGR) of 11.3% | |
| In 2025, the global market for data lenses — visualizations of data — is projected to reach $50 billion | |
| The data lens (data visualization) market is expected to develop at a CAGR of 15% between 2025 and 2033 |
Scheme title: The adoption of data visualization tools by region
Data source: AMA Research
Cloud
On-Premises
Scheme title: Data visualization applications market by deployment type
Data source: Market Research Future
Scheme title: Data visualization market growth across regions
Data source: Mordor Intelligence
Scheme title: The largest and fastest-growing data visualization markets
Data source:
SkyQuest Technology Consulting
The impact of storytelling
| Stories are retained in people’s memories longer than raw statistics, with the impact of a story fading by only 32% over the course of a day, compared to statistics that are forgotten by 73% | |
|---|---|
| When presented with raw data, people only remember 5–10% of the information; however, when stories are used to convey the same information, retention increases to 65%–70% | |
| 93% of people surveyed agree that data storytelling helps make decisions that drive revenue | |
| Information presented in a narrative format is 22 times more memorable than facts |
Scheme title: The benefits of using data storytelling
Data source: SurveyCTO
Adoption of data visualization & storytelling
| Over the last five years, searches for “data storytelling” have increased by about 111% | |
|---|---|
| Search volume for “data democratization” has increased by 117% in the last five years | |
| 46% of people surveyed use charts or graphs to present their data analysis results | |
| 37% of respondents indicated a lack of storytelling skills as one of the major hurdles to creating data stories | |
| 73% of high-performing businesses strongly agree that data visualization tools help gain strategic insights from big data |
Already using
Planning to use in next 12 months
Convert complex data sets into engaging formats, such as images or videos
To create a Data Lineage Visualization
Turning complex data analysis into comprehensible narratives
Data democratization
Scheme title: Organizations’ efforts to enhance data visualization and democratization processes with AI
Data source: Capgemini
Get started on data storytelling with Itransition
Itransition’s services for enabling data storytelling
Data visualization
Itransition experts develop and implement proprietary and platform-based data visualization solutions that enable data storytelling, customizing them to the needs and requirements of clients. We meticulously analyze business needs, suggest the most fitting solution, choose the optimal tech stack, and deliver data visualization solutions for diverse users, from data science teams to business users and C-suite managers. If required, we provide user training services to help the team master the implemented tool.
BI implementation
For those who need to centralize data for managing it in one place and implement robust analytical and visualization capabilities, we offer end-to-end BI implementation services. We both develop BI solutions from the ground up and customize off-the-shelf BI platforms, provide user training, and ensure the system works smoothly post-implementation to allow the team to extract deeper insights and create rich stories.
Data management
Itransition’s team offers end-to-end data management services, creating and deploying an all-encompassing data management environment and separate solutions for data storage, integration, and visualization. Starting from data audit and preparation, we design and roll out robust data architectures and develop comprehensive data governance and metadata management frameworks to ensure data quality, data availability, and compliance with industry standards.
FAQs
Data storytelling is the process of creating compelling narratives using the power of data and visuals to inform the audience, facilitate better decisions, and drive change. It can be used for analyzing marketing campaigns, customer behavior, and sales performance, allowing users to focus on what matters for the business and providing tools to support their arguments.
Data visualization is a powerful tool that conveys information through charts, graphs, diagrams, and maps. Data storytelling is a broader term that denotes using visuals to support a narrative developed based on the collected data.
To upskill your team, encourage them to enroll in courses devoted to data storytelling or those that cover the fundamentals of data analysis, cleaning, visualization, and presentation. Fund learning programs on specific tools like Microsoft or Tableau, organize workshops, purchase specialized books and learning materials, and invite third-party specialists to conduct user training.
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