Que faites-vous si vos compétences en analyse de données peuvent aider à créer un changement positif dans la société ?
Les compétences en analyse de données sont comme un couteau suisse pour le monde moderne : polyvalentes, puissantes et capables de faire une réelle différence. Si vous possédez ces compétences, vous vous demandez peut-être comment elles peuvent être mises à profit au profit de la société. Dans un monde inondé de données, votre capacité à interpréter et à analyser les informations est inestimable, non seulement dans les affaires ou la science, mais aussi pour créer un impact sociétal. En comprenant les tendances, en identifiant les problèmes et en éclairant les politiques, votre expertise peut être le catalyseur d’un changement positif. Que ce soit par le biais de la santé publique, de l’éducation ou de la protection de l’environnement, les possibilités de contribuer sont vastes et significatives.
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Alex SouzaGenerative AI | Analista de Dados | Ciência de Dados | Mentor em Dados | Professor | MTAC
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Manish Kumar, PMPDemand Planning Manager | Demand Forecasting | Supply Chain | Supply Chain Analytics | R | Python | SQL | UNIX | PMP® |…
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Akhil KhungerQA Financial Modeling Specialist IEEE Senior Member
Votre parcours pour avoir un impact sociétal commence par l’identification des domaines qui nécessitent une attention particulière. Regardez autour de vous dans votre communauté ou considérez les problèmes mondiaux qui résonnent avec vous. Est-ce l’éducation, la santé publique ou peut-être la conservation de l’environnement ? L’analyse des données peut révéler des modèles cachés et des inefficacités. En analysant les résultats scolaires, vous pourriez trouver des moyens d’améliorer les méthodes d’apprentissage. En santé publique, votre analyse pourrait révéler des corrélations entre les épidémies et les facteurs socio-économiques. Les données environnementales peuvent mettre en évidence les effets de la pollution sur les écosystèmes. L’identification de ces besoins est la première étape pour faire une différence tangible.
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I discovered that my abilities went beyond business during my customer churn analysis project. After analyzing trends, I found that in underprivileged communities, customer satisfaction and churn rates were correlated. This realization gave rise to a project that will enhance service accessibility while utilizing data analysis for the benefit of society as a whole.
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There are many impactful ways to apply your data analysis skills, especially in the healthcare field. One example use case can be identifying and addressing health disparities. Examining health data broken down by demographics like race, income, and geography can reveal inequities in access to care, treatment, and outcomes. These insights can guide targeted interventions and resource allocation to underserved communities. For instance, an analysis could show certain neighborhoods lack access to primary care physicians or pharmacies.
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If your data analysis reveals insights that can create a positive impact in society, consider the following steps: 1. Identify the need: Pinpoint specific social issues or challenges that your analysis can help address. 2. Share findings: Present your results to relevant stakeholders, organizations, or communities who can benefit from the insights. 3. Collaborate: Work with experts, policymakers, or advocates to develop solutions tailored to the identified needs. 4. Develop recommendations: Provide data-driven suggestions for addressing the identified needs. 5. Support evidence-based decision-making: In Areas like : - Education - Healthcare - Environmental sustainability - Social justice - Community development
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Organizations or funders typically hire impact consultants or practitioners to navigate this complex landscape. These experts would then develop a logic model or theory of change, establish relevant metrics, and devise a plan for collecting data. They would then search for suitable surveys that align with their specific needs and expertise, whether online or offline. Finally, depending on the required dynamism, they would summarize the survey results using tools like PowerBI, Tableau, or other similar business intelligence platforms.
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As a Statistical Officer in Pakistan, I leverage my data analysis skills to drive positive change across various sectors, benefiting our nation and the global statistics community. By uncovering critical insights in healthcare, education, and environmental data, I help identify areas for intervention and promote equity. Presenting findings clearly ensures actionable understanding and informed decision-making. My role empowers me to contribute to a more informed, fair, and just society, enhancing Pakistan's development and supporting global statistical advancements.
Une fois qu’un besoin est identifié, l’étape suivante consiste à recueillir des données pertinentes. Cela peut impliquer la collecte de nouvelles données par le biais d’enquêtes ou d’expériences, ou l’exploitation de bases de données existantes. Assurez-vous que vos données sont exactes, fiables et représentatives de la population ou du phénomène que vous étudiez. Cette étape nécessite une planification méticuleuse pour éviter les biais qui pourraient fausser votre analyse. N’oubliez pas que la qualité de vos données est à la base de la crédibilité de vos informations, alors donnez la priorité à l’intégrité des données et aux pratiques de collecte éthiques.
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Identify the exact requirements before starting gathering data to make sure gather right source of data After requirements are defined, gather as much relevant data is possible including multiple sources. Test the data early enough to make sure it is complete else need to gather from more sources.
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After working on my customer churn analysis project, I saw that I could use my skills to meet more needs in society. I collected data from various sources and discovered relationships between socioeconomic factors and churn rates. This caused initiatives to provide targeted support to underprivileged populations, indicating the power of data analysis to effect positive change outside of the business world.
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Collect relevant, reliable data from diverse sources while ensuring privacy. Leverage public datasets as well as ethnographic methods to gain deeper insights. Document data sources and methodologies for transparency and reproducibility.
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𝗖𝗼𝗹𝗹𝗲𝗰𝘁 𝘁𝗵𝗲 𝗥𝗶𝗴𝗵𝘁 𝗗𝗮𝘁𝗮: After figuring out what you need to fix, the next step is to get the right data. You might need to create surveys or do experiments to collect new information, or you can use data that already exists. 𝗕𝗲 𝗖𝗮𝗿𝗲𝗳𝘂𝗹 𝗮𝗻𝗱 𝗧𝗵𝗼𝗿𝗼𝘂𝗴𝗵: Make sure your data is good—that means it’s accurate, reliable, and really shows what’s going on. Plan carefully so your data isn’t biased, which could mess up your results. 𝗦𝘁𝗮𝘆 𝗛𝗼𝗻𝗲𝘀𝘁: Always gather data in a fair and ethical way. The better your data, the more people will trust what you find out.
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One thing I found helpful is to collect relevant data related to the issue you've chosen. This might involve gathering existing data sets, conducting surveys, or setting up data collection systems.
Avec vos données en main, plongez dans l’analyse. Utilisez des méthodes statistiques et des outils de visualisation des données pour explorer l’information. Recherchez les tendances, les corrélations et les valeurs aberrantes. Il ne s’agit pas seulement de faire des calculs ; il s’agit de raconter une histoire qui peut inspirer l’action. Votre analyse doit conduire à des informations exploitables qui répondent aux besoins que vous avez identifiés. Cela pourrait signifier développer des modèles prédictifs de la propagation des maladies ou identifier les facteurs clés qui contribuent à la réussite scolaire.
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I discovered that my abilities went beyond business during my customer churn analysis project. I found trends connecting socioeconomic factors and turnover when I thoroughly analyzed the data. Inspired by that, I created churn prediction models that allow for focused interventions to assist customers who are at risk. It's evidence that the analysis of data can lead to constructive social change.
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Apply appropriate analytical techniques to uncover patterns and root causes. Validate findings through rigorous testing and cross-examination. Visualize data effectively to communicate insights clearly to stakeholders.
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𝗔𝗻𝗮𝗹𝘆𝘇𝗲 𝘁𝗵𝗲 𝗗𝗮𝘁𝗮: Now that you've gathered your data, start analyzing it using tools for statistics and visualization. Look for patterns, trends, and anything unusual. 𝗧𝗲𝗹𝗹 𝗮 𝗦𝘁𝗼𝗿𝘆: Your analysis isn't just about numbers; it's about crafting a story that inspires action. This should lead to clear, actionable insights. 𝗗𝗿𝗶𝘃𝗲 𝗥𝗲𝗮𝗹 𝗖𝗵𝗮𝗻𝗴𝗲: Your work should lead to clear steps that can be taken to solve the problems you find. This isn't just about data; it's about driving real change. Your insights might mean figuring out ways to stop diseases from spreading or finding out what helps students do better in school. Each insight is a potential solution, and each solution is a step towards a better world.
Il est essentiel de communiquer vos conclusions aux parties prenantes. Il peut s’agir de décideurs, de dirigeants communautaires ou du grand public, c’est-à-dire de toute personne qui peut aider à mettre en œuvre le changement en fonction de votre analyse. Présentez vos données de manière accessible, en utilisant des visuels clairs et en évitant le jargon. Interagissez avec votre public, écoutez ses commentaires et soyez prêt à expliquer les implications de vos données. Votre objectif est de construire un pont entre votre analyse et ceux qui peuvent agir en conséquence.
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Alex Souza
Generative AI | Analista de Dados | Ciência de Dados | Mentor em Dados | Professor | MTAC
Involve relevant stakeholders, including community members, policymakers, non-profit organizations, and other key players, in the data analysis process. Collaborate with them to ensure that your analysis aligns with their needs and priorities.
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Show any trends from the data to business/ stakeholders before starting using them. Make sure that the data is relevant to the stakeholders. At each step of analysis show results through proper channels like ppt, tableau etc to stakeholders so they can provide meaningful inputs.
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𝗦𝗵𝗮𝗿𝗲 𝗬𝗼𝘂𝗿 𝗙𝗶𝗻𝗱𝗶𝗻𝗴𝘀: It’s important to talk about your results with people who can make changes, like leaders or the community. 𝗠𝗮𝗸𝗲 𝗜𝘁 𝗦𝗶𝗺𝗽𝗹𝗲: Use easy visuals and simple words to show what you found. 𝗟𝗶𝘀𝘁𝗲𝗻 𝗮𝗻𝗱 𝗘𝘅𝗽𝗹𝗮𝗶𝗻: Talk with others about your results, listen to their ideas, and explain what the data shows.
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Sharing the findings from data analysis helps in decision making to solve societal problems. One way to make data relevant to society is to disseminate findings to the relevant stakeholders and actors (political leaderships, community leaders, traditional authorities, project beneficiaries, etc). This could be done by simplifying findings into non-technical language and easy to read and understand mode. Several mediums including community fora, social media, in-depth discussions are appropriate to share findings with intended stakeholders and actors.
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Consult subject matter experts, policymakers, and affected communities. Build coalitions and facilitate collaborative problem-solving. Address concerns and incorporate diverse perspectives into proposed solutions.
Traduire les informations basées sur les données en solutions concrètes est là où le caoutchouc rencontre la route. Travaillez avec les parties prenantes pour développer des stratégies qui tirent parti de vos résultats. Cela peut impliquer de concevoir des interventions ciblées, d’éclairer les changements de politique ou d’orienter l’allocation des ressources. La mise en œuvre nécessite un effort de collaboration et souvent une approche multidisciplinaire. Soyez adaptable et prêt à affiner vos stratégies en fonction des commentaires et des résultats.
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𝗣𝘂𝘁 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀 𝗶𝗻𝘁𝗼 𝗔𝗰𝘁𝗶𝗼𝗻: It is crucial to turn your data insights into real solutions. Work with stakeholders to create plans that use your findings. 𝗖𝗿𝗲𝗮𝘁𝗲 𝗖𝗵𝗮𝗻𝗴𝗲: You might need to start new programs, help change policies, or decide where to focus resources. 𝗪𝗼𝗿𝗸 𝗧𝗼𝗴𝗲𝘁𝗵𝗲𝗿: It takes teamwork and often input from different areas. Be flexible and ready to improve your plans based on what you learn from trying them out.
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Focus on translating insights into real-world solutions: 1. Collaborate with stakeholders to 𝗱𝗲𝘃𝗲𝗹𝗼𝗽 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗲𝘀 that 𝗹𝗲𝘃𝗲𝗿𝗮𝗴𝗲 your data-driven 𝗳𝗶𝗻𝗱𝗶𝗻𝗴𝘀. 2. Design targeted interventions, inform policy changes, or 𝗴𝘂𝗶𝗱𝗲 𝗿𝗲𝘀𝗼𝘂𝗿𝗰𝗲 𝗮𝗹𝗹𝗼𝗰𝗮𝘁𝗶𝗼𝗻 based on your analysis. 3. Take a 𝗺𝘂𝗹𝘁𝗶𝗱𝗶𝘀𝗰𝗶𝗽𝗹𝗶𝗻𝗮𝗿𝘆 𝗮𝗽𝗽𝗿𝗼𝗮𝗰𝗵, working with experts from various fields to ensure comprehensive solutions. 4. 𝗕𝗲 𝗮𝗱𝗮𝗽𝘁𝗮𝗯𝗹𝗲 𝗮𝗻𝗱 𝗼𝗽𝗲𝗻 𝘁𝗼 𝗿𝗲𝗳𝗶𝗻𝗶𝗻𝗴 your strategies based on real-world results. By bridging the gap between data insights and practical implementation, you can harness the power of data analysis to drive meaningful, sustainable improvements in society.
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Develop actionable, evidence-based strategies aligned with identified needs. Pilot solutions on a smaller scale and monitor their effectiveness. Scale up successful interventions through policy changes or wider adoption.
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L’analyse de données peut guider le développement et la mise en œuvre de solutions en prédisant les résultats, en optimisant l’allocation des ressources et en évaluant la faisabilité de différentes interventions. Cela garantit que les solutions sont basées non seulement sur des modèles théoriques mais aussi sur des applications pratiques.
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1. Turn data into real solutions by responding to the needs defined at the beginning. 2. Disseminate the action plan to stakeholders in order to receive feedback and improvements. 3. Implementation and follow-up of the action plan by the interested parties.
Enfin, évaluez l’impact de vos efforts. Le suivi et l’évaluation sont essentiels pour comprendre l’efficacité des solutions que vous avez contribué à mettre en œuvre. Utilisez une analyse de données supplémentaire pour mesurer les résultats par rapport aux objectifs que vous vous êtes fixés. Cette étape ne consiste pas seulement à valider votre travail ; c’est une opportunité d’apprentissage et de croissance. En évaluant votre impact, vous pouvez identifier les meilleures pratiques et les domaines à améliorer, ouvrant la voie à de futures initiatives qui peuvent profiter encore plus à la société.
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It is very important to monitor your models regularly based on predefined timeline. Necessary KPI metrics should be added. It is important to spend some time on deciding right metrics. As too loose standards could lead to false comfort whereas too strict standards could lead to unnecessary analysis in the model. Also it is important to have multiple KPI to check variety of statistics and cover majority of cases
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Establish KPIs to Track: To use your data analysis skills for positive societal impact, it's critical to assess and monitor the outcomes of your work. Measuring results is key to understanding the effectiveness of the data-driven solutions you've helped implement and to continuously improve your approach. Collaborate with partner organizations to define clear metrics upfront for evaluating success. Identify key performance indicators (KPIs) that align with the social change objectives. For example, if addressing education inequity, KPIs could include graduation rates, test scores, or college admissions for underserved student populations.
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Establish clear metrics to evaluate the efficacy of implemented solutions. Continually collect feedback from stakeholders and beneficiaries. Refine approaches based on real-world results and evolving circumstances.
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Il est essentiel de surveiller l’impact de toute initiative à l’aide de l’analyse de données. Cela implique la mise en place d’indicateurs de performance clés (KPIs) et leur suivi continu à travers les données. Les ajustements peuvent être effectués en temps réel basés sur des retours orientés par les données, améliorant ainsi l’efficacité des initiatives.
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As they say, Impact where it matters. If the analysis is solving a problem and creating a positive outcome for society. The amount of learning and satisfaction it provides is unmatched.
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Utilize your data analysis skills to identify social issues and their underlying causes. Collaborate with experts in relevant fields to design data-driven solutions and advocate for change. Leverage your expertise to influence policies and initiatives that address societal challenges. Additionally, consider sharing your knowledge through publications and presentations to inspire others to use their skills for positive change.
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Think about how you can use forecasting or machine learning to predict future outcomes for the betterment of society. Can you solve any "wicked problems" with your skills? Ensure that you research the topic and in your storytelling, explain how your analysis confirms or rejects past hypotheses. What are the real world applications of your work?
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Il est important de prendre en compte les implications éthiques, la confidentialité des données et l’inclusivité des processus d’analyse de données. Assurer que les données ne renforcent pas les biais existants et que les normes de confidentialité sont respectées est crucial pour maintenir la confiance et bénéficier véritablement à la société.