Introduction to Data Engineering
With practical experience in platform architecture and data querying, this course offers a basic understanding of data engineering, covering important ideas, tools, and career pathways.
Description for Introduction to Data Engineering
Features of the Course:
Overview of Data Engineering and Its Functions: Acquire knowledge of the foundational principles of data engineering and explore the functions of Data Engineers, Data Scientists, and Data Analysts within the data ecosystem.
Data Ecosystem and Repositories: Study data structures, file formats, data sources, and examine various data repositories, including RDBMS, NoSQL databases, data warehouses, data marts, data lakes, and data lakehouses.
Processing and Integration of Big Data: Acquaint yourself with significant data tools such as Apache Hadoop and Spark, and comprehend ETL, ELT, data pipelines, and data integration.
Practical Experience and Professional Development: Engage in practical laboratories, execute querying operations, and acquire insights about data engineering career trajectories from seasoned individuals in the industry.
Level: Beginner
Certification Degree:Yes
Languages the Course is Available:22
Offered by: On Coursera provided by IBM
Duration: 3 hours (approximately)
Schedule: Flexible
Pricing for Introduction to Data Engineering
Use Cases for Introduction to Data Engineering
FAQs for Introduction to Data Engineering
Reviews for Introduction to Data Engineering
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for Introduction to Data Engineering
CensusGPT is an AI tool that simplifies access to census data, offering tabular data and visual representations in response to user queries. It targets economists, researchers, and individuals interested in demographic analysis, leveraging the TextSQL framework for seamless interaction with datasets.
The AI data analysis tool offers real-time insights and collaboration, integrated with security features, although users may face limitations with complex inquiries and integration requirements.
NovaceneAI streamlines the organization of unstructured text data with AI algorithms, offering dedicated cloud hosting, adaptability across sectors, and robust data privacy measures.
Coginiti's AI-Assisted SQL Development boosts SQL development efficiency with instant query assistance and optimization, alongside on-demand learning resources, while facing integration restrictions and an initial learning curve.
Posit offers a comprehensive platform with enterprise solutions, cloud applications, community resources, and deployment solutions to enhance productivity in data science teams.
Accio.ai is an AI data exploration tool that centralizes data warehouses, dynamically generates SQL queries, ensures data consistency, and provides an intuitive interface for data exploration, enhancing comprehension and efficiency in data analysis.
AskYourDatabase facilitates conversational interactions with SQL and NoSQL databases, offering insights, visualization, and analysis features, with support for major databases and integrations like ChatGPT and Excel.
Vanna.ai, an open-source Python-based AI SQL agent, swiftly generates complex SQL queries, supporting various databases and integration options for efficient database operations and insights extraction.
NLSQL is an AI utility that offers an intuitive text interface and NLP SQL API for personnel to make data-driven decisions, with real-time access to critical healthcare data and instant results.
Avanti is a Chrome extension that enhances data analyst work with Metabase, offering features such as SQL query generation, formatting, and intelligent AI capabilities, with a focus on data security and complimentary trial access during development.
Featured Tools
Discover the process of identifying machine learning model types, training and deploying predictive models using Azure Machine Learning's automated capabilities, developing regression, classification, and clustering models with Azure Machine Learning Designer, and deploying models seamlessly without scripting.
Understand AI, its applications, concepts, ethical concerns, and receive expert career guidance.
Learn to implement and apply unsupervised learning techniques, focusing on clustering and dimension reduction algorithms, in a business environment.
Leverage AI to create and optimize growth marketing strategies, enhance consumer engagement, and drive business expansion and sales.
Master the process of exploratory data analysis, train AutoML models with Vertex AI and BigQuery ML, optimize models using performance metrics and loss functions, and generate scalable datasets for training and evaluation.