Wie können Sie Datenvisualisierung nutzen, um Ihre berufliche Reputation aufzubauen?

My perspective on defining goals for data visualizations is centered on clarity and audience alignment. Whether aiming for a career in data analysis, consulting, or journalism, or seeking clients as a freelancer, it's crucial to articulate specific objectives. Tailoring visualizations to meet audience expectations fosters engagement and impact. Whether establishing thought leadership or pursuing influencer status, strategic alignment with the audience's needs and interests is key.

Leverage data visualization to enhance your professional reputation by creating clear, compelling visuals that simplify complex information. Demonstrate expertise through sophisticated analyses and showcase decision support capabilities. Utilize interactive tools for engagement, maintain a consistent branding style, and share visualizations on relevant platforms. Collaborate with peers, document your process, and stay current with trends to exhibit adaptability. These practices position you as an expert, fostering recognition and credibility in your field.

Without data visualization, I don't think I'd be as far along in my data career as I am. I say this because my competitive advantage as an analyst has always been the ability to concisely communicate what the data is telling stakeholders. By leveraging my creativity in dashboard formatting and simple but robust dataviz tiles, I've been able to differentiate myself as a subject matter expert to the exec level and c-suite of the companies I've worked for. Furthermore, data visualization and storytelling couples nicely with end user trainings on a given BI tool. Once you master the art of communicating data, you can also communicate how to use the tools and enable the business to self-serve.

Data visualization is more than presenting charts. It's a platform to narrate the story discovered while analysing the data. It involves understanding your audience and the business context, weaving together information in an organised manner to construct a compelling narrative. Selecting the correct charts/graphics is a critical element as they should succinctly convey information while maintaining a coherent storyline. Furthermore collaboration can best help to achieve a refined outcome resulting from collective understanding & consensus. This approach helps in informed decision-making while showcasing our business acumen, analytical thinking, collaborative approach & storytelling skills, thus contributing to our professional reputation.

Data is the new oil. Data visualization and storytelling are essential skills across professional levels and industries. These skills transform complex data into a comprehensible format that fuels informed decision-making, enhancing personal growth and credibility. For senior management, they facilitate clear communication of strategic insights. Across sectors, they ease understanding of various metrics and uncover growth opportunities. With an advancing data-driven economy, mastering these skills paves the way for career enhancement and drives organizational growth. Thus, honing data visualization and storytelling skills can catalyze career enhancement while driving organizational growth, making them indispensable for every professional.

- When you create a data visualisation, do not just show it to your data colleagues. Show it to non-data people and ask them what they think it shows. If they cannot tell you what the main takeaway from your visualisation is, then it's not a good visualisation. Most people are non-data people and they are the ultimate judges of whether the other visualisation is good. - Data visualisations are far more about quality than quantity. Spending 20 thinking about and crafting one visualisation is far better than spending one hour each on 20 visualisations. Sometimes we see a visualisation and we think "Woah! That's cool!". You want to create those visualisations.

Leveraging data visualization to enhance portfolio requires clear articulation of objective of the project, understanding of target audience and the impact of visualization on the viewers. The another most important aspect of data visualization is present the story in the visual ways. An each and every chart should tells a story with full potential to engage the audience.

In my view, a strong portfolio is key for a data visualization professional. Choose your best work, detail your tools and insights, and use platforms like Tableau or GitHub Pages. It should reflect your personal brand and constantly evolve with your growth.

Develop a comprehensive portfolio showcasing a diverse range of data visualizations. Include projects that demonstrate your proficiency with different tools, your ability to tackle various data challenges, and your creativity in presenting insights. A robust portfolio serves as a visual testament to your skills and expertise.

Building a compelling data visualization portfolio is crucial in showcasing my proficiency, creativity, and experience. It serves as a dynamic digital resume and personal brand, allowing me to exhibit diverse projects organized coherently. Utilizing platforms like Tableau Public or GitHub Pages enhances accessibility. The portfolio should feature a concise introduction, project descriptions with employed tools/methods, and highlight key insights. By presenting a well-structured and engaging showcase of my work, I aim to convey my expertise in translating complex data into meaningful visual stories.

Sharing your portfolio is crucial for gaining visibility and networking in the data visualization field. Utilize platforms like LinkedIn, Twitter, and Instagram to showcase your work with engaging captions and relevant hashtags. Joining online communities such as Reddit and Kaggle allows for feedback and interaction with peers. Participate in challenges like Makeover Monday and Viz for Social Good to demonstrate your skills and contribute to meaningful projects. This proactive approach not only builds your online presence but also establishes you as a valuable member of the data visualization community.

I have been sharing my data visualizations on LinkedIn for a few years. I have been building my personal brand and showing my aesthetic this way. I get to build a community of people who value my work.

Actively share your data visualizations across relevant platforms. Utilize professional networks, social media, and specialized communities to showcase your work. Regularly contribute to discussions, providing insights into your visualization process, methodologies, and the stories behind your data. Sharing fosters visibility and positions you as an active contributor to the field.

Sharing your work on Tableau Public provides an excellent opportunity to showcase your skills on a prominent data visualization platform. Proficiency in creating dashboards using Tableau is a valuable skill set that enhances your professional appeal. By consistently sharing your visualizations on Tableau Public, you can document your growth and expertise over time. Engaging in challenges like Makeover Monday or Workout Wednesday further demonstrates your commitment to continuous improvement and innovation in the field of data visualization.

Once you've curated a compelling portfolio, the next step is to showcase your work to a broader audience. Leverage the power of social media platforms like LinkedIn, Twitter, or Instagram to share your data visualizations. Craft engaging captions, utilize relevant hashtags, and include links directing viewers to your comprehensive portfolio. Active participation in online communities such as Reddit, Medium, or Kaggle offers an excellent avenue to publish your visualizations, receive constructive feedback, and engage with fellow data enthusiasts. Elevate your presence by taking part in data visualization challenges like Makeover Monday, Storytelling with Data, or Viz for Social Good.

One thing I've found helpful in using data visualization to build a professional reputation is to actively network with others in the field. One time at work, I reached out to a data visualization expert whose work I admired, asking for feedback on my own portfolio. This led to a mentorship that not only honed my skills but also introduced me to a broader community of professionals. Networking isn't just about sharing your work; it's about creating meaningful connections that can offer guidance, collaboration opportunities, and expose you to new perspectives and techniques.

Participation and engaging with data communities, both online and offline is a great way to build a professional reputation. If your BI tool of choice is Tableau then you can use the #datafam to find the community on social media( LinkedIn and Twitter). Share your work and ask for feedback from the community. There are many community initiatives like Workout Wednesday and Back 2 Viz Basics which have weekly or bi-weekly challenges in which you can take part and establish your presence in the community.

Networking is an essential step in any industry. Data visualization should be how well you can convey the story, KPI, alerts to everyone who is using it. Networking with individuals doing the same gives you clarification as you can take feedback on a real time basis. There are highly active communities online where you can discuss any scenario as well as there are COE teams at organization levels.

Engage in networking within the data visualization community. Connect with professionals, participate in forums, and attend industry events. Establishing relationships with peers, mentors, and potential collaborators not only expands your network but also enhances your credibility within the field.

Networking in the realm of data visualization is essential for professional growth. Engage in both online and offline events, attending webinars, workshops, and conferences to glean insights from experts. Actively participate in meetups to exchange ideas and create connections within the community. Don't hesitate to initiate contact with admired individuals or potential collaborators through email or social media, seeking advice or feedback. Offering assistance and sharing expertise not only fosters goodwill but also establishes you as a valuable contributor, enhancing your professional reputation in the dynamic field of data visualization.

Good points, but some additional consideration: Keep learning: Data visualization is a constantly evolving field, so you should always keep learning new techniques, tools, and trends. Be ethical: Data visualization is not only an art, but also a responsibility. You should always be ethical and honest in your data visualization practice, and avoid misleading, manipulating, or misrepresenting your data.

Stellt Euch mal Folgendes vor: In der wöchentlichen Besprechung werden wie immer die Excel-Tabellen geöffnet und einzelne Zahlen besprochen. Du aber hast eine gut abgestimmte Grafik mitgebracht und Dir eine gute Story dazu überlegt! Statt durch Zahlen zu scrollen und sich zu fragen, ob die Formeln richtig sind, hast Du die Zahlen in ein Power BI gesteckt, sie gecheckt und einen gut gestaltetes Diagramm erstellt. Du wirst offene Münder und viele Gedanken (warum ist das mir nicht eingefallen) von Deinen Kollegen bekommen.

Reconciliation is an important part of data visualisation. It supports in accuracy of reports and in compliance matters both internal and external.

If you want to get started with data visualization, feel free to get a copy of Tableau Public! Tableau Public is free for the public (as it's name implies) and start experimenting with publicly available datasets!

Being curious about the recent trends in DV market is helpful to gauge what’s hot and what not. You don’t want to pick a tool that no one uses now or create yesteryear visualisation that hardly anyone cares about today. Keep pace with the market. Data visualisation market is flooded with tools at present. It’s important to learn some of those but at the same time learn to create visualisation using Python, R or even on excel. Not everyone uses tools all the time and it’s usually a good idea to be tools agnostic sometimes. The core concepts of DV remain the same. Coming to tools, don’t just stick to one tool and try to learn multiple tools as it will present multiple options. It would also help you understand pros and cons of the tool.