This is the second course in the Google Data Analytics Certificate. These courses will equip you with the skills needed to apply to introductory-level data analyst jobs. You’ll build on your understanding of the topics that were introduced in the first Google Data Analytics Certificate course. The material will help you learn how to ask effective questions to make data-driven decisions, while connecting with stakeholders’ needs. Current Google data analysts will continue to instruct and provide you with hands-on ways to accomplish common data analyst tasks with the best tools and resources.


Pregunta para tomar decisiones basadas en datos
Este curso es parte de Certificado profesional de Análisis de datos de Google

Instructor: Google Career Certificates
Instructor principal
631.239 ya inscrito
Curso
(23,485 reseñas)
Experiencia recomendada
Qué aprenderás
Explain how each step of the problem-solving road map contributes to common analysis scenarios.
Discuss the use of data in the decision-making process.
Demonstrate the use of spreadsheets to complete basic tasks of the data analyst including entering and organizing data.
Describe the key ideas associated with structured thinking.
Habilidades que obtendrás
- Categoría: Spreadsheet
- Categoría: Questioning
- Categoría: Decision-Making
- Categoría: Problem Solving
- Categoría: Data Analysis
Detalles a tener en cuenta

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20 cuestionarios, 5 evaluaciones
Curso
(23,485 reseñas)
Experiencia recomendada
Adquiere experiencia en Ciencia de Datos
- Aprende nuevos conceptos de la mano de expertos del sector
- Adquiere conocimientos básicos sobre un tema o una herramienta
- Desarrolla habilidades relevantes para el trabajo mediante proyectos prácticos
- Obtén un certificado profesional para compartir de Google

Hay 4 módulos en este curso
To do the job of a data analyst, you need to ask questions and problem-solve. In this part of the course, you’ll check out some common analysis challenges and how analysts address them. You'll also learn about effective questioning techniques that can help guide your analysis.
Qué incluye
8 videos8 lecturas6 cuestionarios
In analytics, data drives decision-making. In this part of the course, you’ll explore data of all kinds and its impact on real-life choices and strategies. You’ll also learn how to share your data through reports and dashboards.
Qué incluye
6 videos6 lecturas4 cuestionarios
Spreadsheets are a very important data analytics tool. In this part of the course, you will learn about how data analysts use spreadsheets in their work every day. You will also explore why structured thinking helps analysts better understand problems and come up with solutions.
Qué incluye
9 videos8 lecturas7 cuestionarios
Successful data analysts learn to balance needs and expectations. In this part of the course, you’ll learn strategies for managing stakeholder expectations while establishing clear communication with your team.
Qué incluye
15 videos6 lecturas3 cuestionarios
Instructor

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Revisado el 23 de jun. de 2022
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Data is a group of facts that can take many different forms, such as numbers, pictures, words, videos, observations, and more. We use and create data everyday, like when we stream a show or song or post on social media.
Data analytics is the collection, transformation, and organization of these facts to draw conclusions, make predictions, and drive informed decision-making.
The amount of data created each day is tremendous. Any time you use your phone, look up something online, stream music, shop with a credit card, post on social media, or use GPS to map a route, you’re creating data. Companies must continually adjust their products, services, tools, and business strategies to meet consumer demand and react to emerging trends. Because of this, data analyst roles are in demand and competitively paid.
Data analysts make sense of data and numbers to help organizations make better business decisions. They prepare, process, analyze, and visualize data, discovering patterns and trends and answering key questions along the way. Their work empowers their wider team to make better business decisions.
You will learn the skill set required for becoming a junior or associate data analyst in the Google Data Analytics Certificate. Data analysts know how to ask the right question; prepare, process, and analyze data for key insights; effectively share their findings with stakeholders; and provide data-driven recommendations for thoughtful action.
You’ll learn these job-ready skills in our certificate program through interactive content (discussion prompts, quizzes, and activities) in under six months, with under 10 hours of flexible study a week. Along the way, you'll work through a curriculum designed with input from top employers and industry leaders, like Tableau, Accenture, and Deloitte. You’ll even have the opportunity to complete a case study that you can share with potential employers to showcase your new skill set.
After you’ve graduated from the program, you’ll have access to career resources and be connected directly with employers hiring for open entry-level roles in data analytics.
No prior experience with spreadsheets or data analytics is required. All you need is high-school level math and a curiosity about how things work.
You don't need to be a math all-star to succeed in this certificate. You need to be curious and open to learning with numbers (the language of data analysts). Being a strong data analyst is more than just math, it's about asking the right questions, finding the best sources to answer your questions effectively, and illustrating your findings clearly in visualizations.
You'll learn to use analysis tools and platforms such as spreadsheets (Google Sheets or Microsoft Excel), SQL, presentation tools (Powerpoint or Google Slides), Tableau, RStudio, and Kaggle.
Learners can self-select which platform they want to use throughout the program: Google Sheets or Microsoft Excel. It’s up to the learner’s preference, and all activities throughout the syllabus can be performed on either platform.
We highly recommend completing the courses in the order presented because the content in each course builds on information from earlier lessons.