Veja como você pode alternar entre o marketing digital e as carreiras de análise de dados.

Digital marketing and data analyst are some what similar that we analyse the data and according to the data we work on it so it will be easy to you to understand and work on data analysis.

Pivoting from a digital marketing to a data analysis career involves leveraging your existing skills while acquiring new ones. Here's a brief roadmap: 1. Skill Enhancement: Learn data analysis tools and languages such as Excel, SQL, Python, and R. 2. Education: Consider enrolling in courses or certifications in data analytics or data science. 3. Practical Experience: Work on projects or internships to gain hands-on experience. 4. Leverage Marketing Knowledge: Use your understanding of consumer behavior and marketing metrics to analyze data trends and insights. 5. Networking: Connect with professionals in the data analysis field through networking events, online forums, and LinkedIn.

Find the common skills between digital marketing and data analysis, then work on filling in the gaps you need to learn to make data analysis your job. Also, as you do this work on leveraging your network and building on to it in the data analysis space so that you can actually get a job later.

Build a Portfolio Hands-on Projects: Undertake personal or freelance projects that involve data analysis. Showcase your ability to collect, clean, analyze, and visualize data to demonstrate practical skills. Include Results: Highlight outcomes or insights derived from your projects to illustrate your impact and proficiency in data-driven decision-making.

Evaluar las habilidades de marketing digital y cómo se pueden transferir al análisis de datos es un paso crucial para una transición exitosa. Si ya has trabajado con análisis web, métricas de redes sociales o pruebas A/B, tienes una base sólida en la interpretación de datos y la medición del rendimiento. Reconocer tu experiencia en la optimización de campañas y la comprensión del comportamiento del consumidor es relevante y puede traducirse en competencia en el análisis de datos. Esta autoevaluación te ayudará a identificar las áreas en las que necesitas desarrollar más habilidades para cerrar cualquier brecha existente.

Must learn the tools that will be helpful for you to data analysis similar to what we use as Google analytics so learn analysis told so that you can be effective in it.

To transition to data analysis, expand your toolkit beyond marketing platforms. Learn SQL for database management and Python or R for data manipulation and statistical analysis. Start with basics like data cleaning and simple visualizations. Use free online resources and practice with marketing-related datasets to leverage your existing knowledge. Focus on understanding core concepts rather than immediate mastery. Tackle increasingly complex projects as you gain confidence. Remember, many analysts learn on the job, so a solid foundation and eagerness to learn are often enough to begin your career shift.

Je suis tout à fait d'accord avec l'importance de diversifier ses compétences en analyse de données. Lors de mon parcours professionnel, l'apprentissage de SQL et de Python a considérablement élargi ma capacité à gérer des projets complexes . Ces outils sont devenus indispensables pour extraire des insights significatifs des grandes bases de données. En outre, se familiariser avec ces technologies non seulement enrichit votre CV, mais aussi renforce une approche analytique rigoureuse, essentielle pour toute prise de décision basée sur les données.

Back to basics Start learning basic principle of the data analysis so that it will be very helpful for you to get used to it.

Embracing a data analysis career from digital marketing requires grasping key data science principles. Begin with descriptive and inferential statistics to interpret data effectively. Understanding probability will also enhance your analytical skills. Get comfortable with data types, cleaning techniques, and visualization tools. Online courses and tutorials are invaluable for gaining practical skills. Equipping yourself with these fundamentals will enable you to transition smoothly and leverage your marketing background to uncover deep insights and drive data-driven decisions.

Je suis tout à fait d'accord avec le contenu de l'article. La maîtrise des bases des statistiques et de la science des données est essentielle pour interpréter correctement les ensembles de données . L'analyse statistique permet de transformer des données brutes en informations exploitables. Cela dit, il est aussi crucial de bien comprendre le processus de nettoyage des données ; des données mal nettoyées peuvent conduire à des conclusions erronées. L’utilisation efficace des outils de visualisation aide à communiquer les résultats de manière claire et persuasive. Les cours en ligne sont en effet d'excellentes ressources pour acquérir ces compétences.

Je suis tout à fait d'accord avec l'importance de l'expérience pratique en analyse de données . Intégrer les techniques de data analytics dans le marketing numérique peut offrir d'énormes avantages. Dans ma propre expérience, utiliser SQL pour explorer les bases de données clients m'a permis d'identifier des segments de marché spécifiques et d’optimiser les campagnes publicitaires. C’est un excellent moyen de transformer des données brutes en informations exploitables. En plus, entreprendre des projets indépendants ou bénévoles est une excellente idée pour solidifier ces compétences—cela montre aussi aux employeurs potentiels votre engagement et votre expertise.

Network wisely and connect with the particular person that are very interested in or working in data analysis so that they will be very helpful for you to learn.

In transitioning from digital marketing to data analysis, leveraging hands-on experience is crucial. Begin by integrating data analysis techniques into your current role. Utilize SQL to extract customer insights from databases or apply statistical methods to assess campaign performance. Additionally, pursue freelance projects or volunteer opportunities to practice these skills in practical settings. This real-world experience will enhance your expertise and enrich your portfolio, making you a stronger candidate for data analysis roles. By combining your marketing background with data proficiency, you can create a unique value proposition in your new career.

Esse tipo de transição é bem comum, mas vale muito a pena se conectar com quem já tá na área. Procure pessoas da área e participe de discussões em plataformas como GitHub. Mete a cara em hackathons para montar um portfólio legal e expandir sua rede. Outros eventos e workshops também valem a pena. E LEMBRE-SE, NETWORKING É TROCA: ajude os outros e compartilhe o que você sabe para fortalecer suas conexões e abrir novos caminhos na carreira.