From the course: Complete Guide to AI and Data Science for SQL: From Beginner to Advanced

Comparing data roles - SQL Tutorial

From the course: Complete Guide to AI and Data Science for SQL: From Beginner to Advanced

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Comparing data roles

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- [Instructor] What's up, my AI peeps? So in the last video, you took a look at how data evolved over time to what it is today. Now, you're about to meet some of the heroes of the data world, data scientists, data analysts, and data engineers. Let's explore who they are and what they do. Meet the data scientist, where you're an expert in using machine learning and statistics to make predictions and address critical questions. What's remarkable is your versatility. You can work with various data types, from numbers to text, unlocking valuable insights. Like a skilled predictor, you illuminate the path forward in our data-rich world. To become a data scientist, you need a powerful toolkit of skills. These include machine learning and deep learning. You'll develop expertise in teaching computers to learn from data. Data mining. You acquire the knack for extracting valuable information from extensive data sets. Statistical skills. This is where you harness the ability to use numbers effectively to drive meaningful insights. Data optimization. You'll be tasked with building efficient data systems for well-organized information. And soft skills. Effective communication and teamwork are essential for your collaborative success. Now, meet the data analyst, the ultimate trend spotter. You're like a detective in the world of data, uncovering exciting patterns and trends. You have a special knack for connecting the dots within data, much like a detective solving intricate cases. You use your analytical skills to extract valuable insights, revealing the stories hidden in the numbers. To become a skilled data analyst, you'll need these essential skills. SQL and database knowledge. You'll be expected to speak the language of databases proficiently to retrieve and manipulate data effectively. Reporting and data visualization. You'll need to excel at presenting data in compelling, easy to understand visual formats, allowing you to communicate your findings effectively. Data warehousing. Understanding how to store and manipulate large volumes of data efficiently is essential, as it underpins your ability to work with substantial data sets and conduct in-depth analysis. Last but not least, meet the data engineer, where you're the architect of the data world. Similar to how an architect designs, constructs, and maintains buildings, you build, test, and maintain systems that support data and its applications. You work on organizing and managing data effectively. By collaborating with other teams, data engineers help organizations make better decisions using data. To become a skilled data engineer, you need these vital skills. Data warehousing and ETL. You'll learn how to create systems that move data between different sources. This involves extracting data, transforming it into a usable format, and loading it into a data warehouse or other storage systems. Data architecture. You'll develop the ability to design the blueprint for how data is stored, organized and accessed. This includes understanding database structures, data models, and data schemas. Pipeline and scripting. You'll gain expertise in building efficient processes, often referred to as pipelines, to handle large amounts of data. This involves writing scripts or using tools to automate the movement and transformation of data, and there you have it, the heroes of the data world, data scientists, data analysts, and data engineers, each with their own unique skills that play a vital role working together to unlock the power of data, and guess what? You're an important member of this data hero team. Embrace your data journey, and the possibilities are limitless. So let's keep learning, and let's continue this exciting adventure together. Up next, you'll zero in on the role of data scientist and take a closer look at the skills you need to excel in this position. Get ready, get set, and let's go. I'll see you in the next video.

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