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Un día empezó todo…
Todo es nuevo por aquí por WordPress
Así que vamos a usar columnas.
Para ver dónde nos lleva esto.

Ever felt like the world is just a giant pile of numbers waiting to be organized? 🧐 That’s exactly how I felt before clicking «Start» on the Google Data Analytics Professional Certificate…
Ever felt like the world is just a giant pile of numbers waiting to be organized? 🧐 That’s exactly how I felt before clicking «Start» on the Google Data Analytics Professional Certificate. Today, I’m breaking down my experience with Module 1: Foundations: Data, Data, Everywhere. Let’s dive in! 🌊
We live in a world where every click, purchase, and heartbeat generates data. But data without analysis is just noise. 📢 Through this course, I’m learning how to turn that noise into insights that actually solve problems. Whether it’s optimizing a business or even planning a home renovation project 🏡, the power of a technical mindset is real.
Module 1 is all about the «Foundations.» Here are the three concepts that totally changed my perspective this week:
To help fellow students, I’ve put together a quick guide to some of the trickiest questions from the Introducing Data Analytics and Analytical Thinking assessment. Understanding the logic is the key to passing!
Q: Which statements correctly describe data and data analysis?
✅ Answers: Data is a collection of facts; One goal of analysis is to make predictions; Collecting data is part of the process.
💡 Why: Remember that «Data Analytics» is the broad science, while «Data Analysis» is the specific process of collecting and organizing those facts to look into the future.
Q: Data science involves using _____ data to create new ways of modeling?
✅ Answer: Raw.
💡 Why: Data scientists often work with «raw» or unrefined data to build entirely new ways of understanding the unknown.
Q: What does a «Technical Mindset» involve?
✅ Answer: Breaking down complex elements into smaller pieces.
💡 Why: It’s all about logic. If a problem is too big, an analyst breaks it into bite-sized, manageable steps.
Q: What is a «Gap Analysis»?
✅ Answer: Evaluating the current state of a process to identify future improvements.
💡 Why: If a pet shelter wants more donations, they look at where they are now (current) vs. where they want to be (future) to find the «gap.»
Q: What is the «Root Cause»?
✅ Answer: Why a problem occurs.
💡 Why: We aren’t looking for the symptoms; we want the fundamental reason the issue started in the first place.
The journey has just begun. I’ve just wrapped up the first big challenge and am moving into the Data Life Cycle (Plan, Capture, Manage, Analyze, Archive, and Destroy). My goal? To master the tools—from SQL to R—and eventually build a killer capstone project.
Are you also taking the Google Data Analytics course? Or maybe you’re thinking about a career pivot? Let’s connect in the comments! 👇
#DataAnalytics #GoogleCertificate #ContinuousLearning #DataScience #CareerPivot #TechMindset #StudyGuide #GoogleDataAnalyticsAnswers 💻🔥
Welcome back to my learning diary! As I work toward my Google Data Analytics Professional Certificate and prepare for my Cambridge B2 exam, I am documenting every step. Today, I am diving into the «Data Ecosystem»—the invisible world where data lives, breathes, and helps us make smarter choices. 📊
Did you know that data analysis isn’t a modern invention? It is rooted in statistics, which goes back as far as Ancient Egypt.
A data ecosystem is a collection of interacting elements that produce, manage, store, and share data. Think of it like a biological ecosystem, but for information!
The three main pillars are:
Data-driven decision-making means using facts to guide business strategy. Instead of guessing, organizations use data to solve problems like low employee retention or improving brand recognition.
Pro Tip: Always involve Subject Matter Experts (SMEs). These are people familiar with the business problem who can help identify inconsistencies and validate your findings.
Data analysts are like detectives; both follow clues and collect evidence to find the truth.
To wrap up Part 3, remember that the Google Data Analysis Process follows six clear steps: Ask, Prepare, Process, Analyze, Share, and Act. Whether you are analyzing taxi ride demand or helping a retail store predict purchases, these fundamentals will keep you on track!
In this series of posts, I will document my journey through the Google Data Analytics Professional Certificate on Coursera. I was fortunate to receive a scholarship from Google, and I decided to take the course in English to improve both my data analytics skills and my English writing while preparing for the Cambridge B2 exam. My goal is to create a learning diary where I summarize the most important concepts from each lesson, reflect on what I learn, and gradually build a personal knowledge base about data analysis, analytical thinking, and real-world applications of data
The first video introduces the importance of data in today’s world. Many industries such as e-commerce, healthcare, finance, marketing, and technology rely heavily on data to improve their processes, identify opportunities, develop new products, and make better decisions. Data can be understood as a collection of facts, including numbers, images, words, measurements, observations, or videos. Data analysis is the process of collecting, transforming, and organizing this information in order to draw conclusions and support informed decision-making.
The lesson also emphasizes that data is everywhere. Every time we search online, stream music, use GPS, read product reviews, shop online, or post something on social media, we are both using and creating data. The amount of data generated globally is enormous. For example, Google processes more than 40,000 searches per second, which represents billions of searches every day. Because of this massive amount of information, organizations increasingly depend on data analysts to interpret data and help guide strategic decisions.
The course also introduces the main stages of the data analysis process: 1) Ask 2) Prepare 3) Process 4) Analyze 5) Share 6) Act
These steps form the framework that will guide the entire certificate program.
Several Google professionals appear in the video to explain different aspects of data analytics and share their experience working in the industry:
Later in the course, other instructors will guide each stage of the analytics process.
Something that surprised me
The number of industries where data analysts can contribute. Data analytics is useful in many fields such as healthcare, finance, marketing, technology, and e-commerce.
Something I already knew
The idea that data is everywhere. The analytical process also reminds me of the DAFO (SWOT) analysis framework, where structured steps help analyze a situation and make better decisions.
Something new I learned
I learned how many different teams work at Google and how data plays a role in many areas such as engineering, research, cloud computing, and education.
I decided to take the Google Data Analytics Professional Certificate after receiving a scholarship from Google. Data is becoming increasingly important in almost every industry, and I wanted to better understand how organizations use data to make decisions and solve real-world problems.
Another reason I chose this course is that I want to improve my professional skills while also practicing my English. Since I am preparing for the Cambridge B2 exam, I decided to complete the entire course in English and document my learning process through this blog.
By writing about each lesson, I hope to reinforce what I learn, improve my technical vocabulary, and build a personal record of my progress in data analytics. Over time, this learning diary will also become a small portfolio that shows how my understanding of data analysis develops step by step.
Heading (H2)
Introduction
Heading (H2)
What is Data Analytics?
Heading (H2)
The Data Analysis Process
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My Personal Notes
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What I Learned in This Lesson
Watched: 16/07 @ Lunch time at SkyShowtime
🕵️ Mobland 1×01: Where Loyalty Ends and Blood Begins 🔥
Welcome to the gritty underworld of Mobland, where power is currency and trust is always in short supply. Episode 1 kicks off with a bang—literally. In a city ruled by shadows, we meet Vincent, a man torn between family ties and criminal ambition. When a botched deal lights the fuse, alliances crumble and enemies rise.
This explosive premiere sets the tone for a season drenched in danger, betrayal, and street justice. Whether you’re here for the mob drama, the sharp dialogue, or the slow-burn tension, Mobland doesn’t disappoint.
📺 Catch up now and dive deep into the chaos—Mobland 1×01 is just the beginning.
Main scenes of the Mobland 1×01:
Dogans and Lazaros meeting: The initial tense negotiation for peace.
Eddie Harrigan’s return home: The aftermath of the stabbing and the family’s cover-up.
Harry at the hospital with Hughie: Harry intimidating Hughie to change his story.
Harry and the coffin discussion: A brief, more mundane interlude.
Jan’s distress over Tommy: Jan’s worry about their son’s disappearance.
Richie’s call to Kevin: Richie’s enraged threats after finding out Tommy was with Eddie.
Harry and Gina’s study session: A moment of normalcy and family interaction.
Harry’s apology to Jan: Harry attempting to make amends for their argument.
Conrad’s meeting with Harry and the «stick or twist» decision: The planned ambush at the gym and Conrad’s ultimate decision to let Richie live.
Conrad’s family meeting and the fentanyl plan: Conrad outlining his new business venture and testing Archie’s loyalty.
Here is the complete and corrected breakdown of the scenes from «Mobland 1×01» with their corresponding timestamps, covering the entire chapter from start to finish.
Además de seguir el curso, voy a ir anotando y poniendo en práctica todo lo que vemos.
La web es: https://boluda.com/curso/seo/1-introduccion-y-conceptos-basicos-de-seo/
Concepos básicos de SEO:
Indexar vs. rankear:
De todas las webs que están «Indexadas» – rankeea las mejores.
SERP: Search Engine Results Page – la página que muestra los enlaces.
Intentción de busqueda: navegacional (para a ir a un web conocida, buscas eldiario . es en lugar de ir a la web, transaccional (compra) o informacional (busqueda información)
Keyword / palabras claves
Longtail: apellidos a la keyword. cuanto más cola tiene una palabra clave, menor es la competencia.
SEO off page –> fuera de nuestra web ( sobre todo, linkbuilding : generación de enlaces)
SEO on page –> va a ANTES del seo off page.
ORDEN DEL CURSO:
SEO on page: Indexación: qué podemos hacer para que google entienda mejor nuestra página. Cuando indexar o no nuestra página, para hacerla interesante para google.
Contenido
SEO off page: Link building
Experiencia de usuario: rankbrain: premia a las webs que hacen que no reboten los usuarios.
FACTORES más importantes de posicionamiento: 1. Enlaces. 2. On page (se refiere a la parte más técnica de la web, lo que pasa dentro). 3. RankBrain: cómo responde + OTROS MUCHOS ( google cuenta hasta 200, aunque no sé sabe cuales son)