Are you looking for insightful and helpful YouTube channels to improve your knowledge of data engineering, data science, python, big data, machine learning, aws, data, programming, and cloud computing? Look no further. In this post, we've rounded up the top YouTube channels to help you stay up to date and get the foundation you need to excel in these areas. Keep reading to find out our picks and how they can benefit you!
Data engineering: Top Youtube Channels
Databricks' YouTube channel provides educational videos that focus on data engineering, data science, machine learning, and Apache Spark. They cover topics such as Delta Lake, Spark Summit, Data Lakehouse, Data + AI Summit, and Data AI Summit. The channel's content is perfect for anyone who wants to learn more about data engineering, data science, and data processing.
Data Council is a YouTube channel dedicated to providing educational and informative videos about data engineering, machine learning, computer vision, data science, data analysis, deep learning, data engineer, data analytics and big data. The channel covers topics such as data engineering, machine learning, computer vision, data science, data analysis, deep learning, data engineer, data analytics and big data, allowing viewers to gain valuable insight and knowledge from the specialists in these fields. The videos are designed to help viewers learn about the latest trends and technologies in the data engineering field, making for an interesting and informative viewing experience.
Data Engineering YouTube channel offers the latest insights and tutorials about the vast world of data engineering and big data analytics. The channel covers topics like cloud computing, mobile computing, web applications and programming languages such as Java Tamil, Python Tamil, AWS Tamil and Cloud Computing Tamil. They provide reliable information and practical advice on the technologies and best practices needed to help businesses become more data-driven.
Seattle Data Guy
The Seattle Data Guy YouTube channel is a great resource for aspiring data engineers and scientists looking to increase their knowledge in data engineering, big data, coding, and SQL. It offers comprehensive and detailed tutorials on how to become a data engineer, prepare for data engineering interviews, and learn data science, as well as helpful advice on learning coding and using Python. With the Seattle Data Guy, viewers can explore the exciting world of data engineering and data science.
Kahan Data Solutions
Kahan Data Solutions is a YouTube channel dedicated to helping audience members learn about data engineering, cloud computing, data warehouse, data engineering, data tutorials, power bi, SQL server, big data, analysis services, and integration services. They provide informative tutorials and how-to's on all things data related, from setting up databases to extracting valuable insights from data sets. Whether you are just beginning to learn about data or a seasoned data analyst, Kahan Data Solutions is a great resource.
Data with Zach
Data with Zach is a YouTube channel providing educational content on data engineering, technology, and lifestyle topics. It offers educational videos and materials that help viewers acquire the knowledge and skills needed to tackle data engineering projects. The content is presented in a fun and interactive way, making it a worthwhile and enjoyable learning experience. With weekly videos and a variety of topics, Data with Zach is a great resource for anyone looking to expand their knowledge and gain an understanding of the data engineering space.
DataEng Uncomplicated is a YouTube channel dedicated to helping its audience understand and use data engineering, data integration tools, and data ETL. It provides educational FME software and FME tutorials, along with guidance on serverless architecture, transformer guides, FME training, FME how-to guides, and FME desktop. This channel's content is useful for both beginners and advanced users in need of guidance.
Darshil Parmar's YouTube channel is a great source for those who want to learn about data engineering. You can find content related to topics such as AWS Certification, AWS SAA, how to get a tech job, data books, technical podcast and learn data engineering as well as content related to interview preparation. There is something to be found for everyone interested in data engineering.
E-Learning Bridge YouTube channel is a resource for aspiring data engineers. It offers comprehensive tutorials and insights into acquiring the essential big data engineer skills, a roadmap to becoming a data engineer, and data engineer salaries in tech giants such as Google, Amazon, and FAANG. It is a must-watch for anyone looking to get into the data engineering field.
Karthik's Show YouTube channel provides an in-depth look into data engineering, offering viewers knowledge and tips on topics ranging from data architecture to data analysis. The content is presented in an accessible, entertaining format, making it the perfect resource for students and professionals alike.
Snowflake Inc.'s YouTube channel covers topics related to data engineering, cloud analytics, cloud data warehousing, and business intelligence. It highlights Snowflake's advanced data cloud technologies, the use of its snowflake computing system for data science and data apps, its data sharing and exchange capabilities, and more. It's a great resource for anyone wanting to learn more about the company's cloud-based data and analytics solutions.
Codebasics is a YouTube channel that provides programming tutorials for data engineering, julia programming, python for data science, machine learning python, python, git, github, coding, and jupyter. It covers a wide range of topics to help viewers master coding and keep up to date with the latest developments in programming. It is an invaluable resource for novice and experienced coders alike.
Andreas Kretz's YouTube channel is a great resource for anyone looking to learn about data engineering. He covers topics such as data science, big data, Apache Hadoop, Apache Spark, Apache Kafka and offers insights on how to become a data engineer. He explains complex concepts in an easy to understand way and offers tutorials to help viewers get started.
Tirendaz AI is a YouTube channel devoted to data engineering, machine learning, deep learning, and artificial intelligence. They provide tutorials on popular Python libraries, such as pandas, data science, data analysis, data engineering, deep learning with tensorflow, and scikit learn. The tutorials are aimed to help viewers learn key concepts and tools to develop and deploy data-driven applications.
Prepfully is a YouTube channel dedicated to helping viewers prepare for job interviews. It covers a wide range of topics, including data engineering, mock interviews, software engineer interviews, and product manager interviews. Additionally, the channel also covers interviews for data scientists, engineering managers, and UX researchers. With this comprehensive approach to job interview preparation, Prepfully is a great resource for anyone looking to land their dream job.
AIEngineering is a YouTube channel that focuses on data engineering, data science, machine learning, Apache Spark, AI, ML, and Cloud. It provides practical tutorials and tips on building data engineering systems and creating data science and AI-based applications. The channel offers resources to help web developers, software engineers, and DevOps professionals stay on top of the emerging AI trends. It covers topics such as explainable AI, automated machine learning, cloud infrastructure, and DevOps best practices. AIEngineering is the go-to source for those looking to stay ahead of the curve in the ever-evolving world of technology.
Jash Radia's YouTube channel covers topics related to data engineering, tech productivity and Google interviews, providing valuable advice and information to aspiring data engineers in India. He delves deep into topics such as mastering interview skills and becoming a successful data engineer with the help of concise and practical tutorials.
Karolina Sowinska's YouTube channel provides helpful content on data engineering and jobs in tech, giving viewers insight into launching a career in tech. She also explores technology, lifestyle, self-improvement and productivity. Her videos offer valuable tips for viewers interested in taking the first steps in their tech career.
Anuj Syal's YouTube channel provides viewers with a unique blend of data engineering tutorials, lifestyle advice, and up-to-date knowledge on the latest technology trends. With a wide range of content covering a variety of topics, Anuj Syal is the perfect resource for anyone looking to learn more about tech and the modern digital environment.
Skills Needed For Data Engineering
Data engineering is an increasingly important role for data analysts, providing the skills necessary to make data-driven decisions quickly. As the role of data analysts continues to grow in complexity and importance, so too does the need for data engineers, and their ability to design, build and support systems for data storage, processing and reporting.
- Data engineering requires a variety of skills to be effective, including the ability to understand business needs and the technical implementation, then create solutions based on that data. Data engineers need to be well-versed in a variety of software development languages and techniques, such as SQL, Python and other programming languages, along with the ability to build complex systems. They also need to understand and be able to use multiple databases and data structures, as well as have experience with different technologies such as Hadoop and Spark.
- In addition to their technical skills, data engineers must have a working knowledge of other data disciplines such as analytics and visualization, so they can effectively communicate with those teams. The ability to understand data design and the best communication tools for reporting and visualizing data is also important for data engineers. Strong communication is key for a successful data engineering team, as it ensures that everyone understands the complexities and nuances of a data set. Data engineers also need to stay up-to-date on the latest technologies and trends, staying abreast of the evolution of data storage, processing and reporting. This helps to ensure that data engineering teams remain productive and on the cutting edge.
Ultimately, understanding the technical and business aspects of data engineering — and having the right skill set to match — is necessary for any organization to achieve its data-driven goals. By understanding the needs and skills needed for each project, data engineers are able to maximize their impact and success for the company. In many ways, data engineering is the driving force behind any successful data-driven operation, and having a team of skilled data engineers is the key to success.
Utilizing Data Engineering Tools to Streamline Analytics
Data engineering is a powerful tool to use when it comes to streamlining analytics. It is a great way to gain an understanding of extremely large and complex data sets, which is essential for data-driven decision making. From understanding the performance of a business to unlocking insights about customers, data engineering can help process and analyze data with ease.
- Data engineering comes with a whole host of tools that streamline the analytics process. These tools automate many of the tedious tasks that go into designing, building, and maintaining analytics systems. For example, a data engineering platform might include a visual interface to make the process of defining data schemas and queries easier. Visualization tools also help to make the data more digestible for non-technical audiences.
- Data engineering tools are also great for creating automated analytics workflows. These workflows can help ensure that the right data is collected, the right insights are gathered, and the right decisions are made. This has many advantages, such as quicker reaction times to changes in the market or customer behavior, improved customer experience, and better decision-making capabilities. Data engineering is an invaluable resource when it comes to streamlining analytics, and it’s one that businesses should use to their advantage.
Overall, data engineering tools are useful for streamlining the analytics process. They can help make the data more manageable, help non-technical audiences better understand the data, and help automate workflows to create more accurate insights. By taking advantage of data engineering tools, businesses can make the most of their data and gain an invaluable advantage in the market.
Common Tools and Technologies Used in Data Engineering
Data engineering is a branch of data science that is focused on the effects of the large amount of data that is generated and the methods and techniques used to optimize data pipelines and storage, transform and move data, designing databases, and creating data warehouses. Common tools and technologies used in data engineering range from Hadoop, Apache Spark, and Tableau, to ETL and SQL.
- Hadoop is an open-source platform for structuring, storing, and processing large data sets. This platform is vital for making sense of this data and often used for data science projects and predictive modeling.
- Apache Spark is a distributed computing system that is used to analyze large-scale data sets. It can also be used as a general purpose cluster computing platform.
- Tableau is a software platform for creating interactive data visualizations and reports. The platform leverages drag and drop features, making it a great tool for data exploration.
- ETL (Extract, Transform, Load) is an important process for data engineering. It involves extracting data from one source (i.e., a web API), transforming it into a format that is easier to work with and finally, loading it into a data warehouse, often a relational database.
- SQL (Structured Query Language) is another commonly used tool in data engineering and is used to query, update, and manage data in a database. SQL is an integral tool for data engineers as it allows them to efficiently retrieve, manipulate, and store data.
These common tools and technologies are all essential for data engineering and provide the necessary functionality for data engineers to efficiently work with large amounts of data. By leveraging these tools, data engineers are able to effectively and efficiently analyze and manipulate data in order to achieve desired results.