Data Lake, Lakehouse, Data Warehouse Fundamentals in 60 mins
Data Lake, Lakehouse, Data Warehouse Fundamentals in 60 mins, available at $19.99, has an average rating of 4.55, with 29 lectures, 10 quizzes, based on 28 reviews, and has 7961 subscribers.
You will learn about Fundamentals about Data Lake, Data Lakehouse, Data Warehouse and consideration when using them in Data Science Solutions Basics about Data Fabric and Data Mesh and mapping them to Data Science use case General Challenges in building data science solutions using infrastructure products. Absolute fundamentals of computer science mapped to infrastructure products to understand cloud computing costs. Jargon and buzz words free precise mapping of fundamentals to data technology products. Course does NOT provide any step by step API based tutorials for any product or tool. This course is ideal for individuals who are Technical leaders adopting cloud in domain driven organizations or Executives seeking a big picture understanding of the cloud tranformation challenges of Data Science Adoption or Architectes and Solution Architects seeking pivots for explanining solutions to non technical audience or Infrastructure Engineers seeking a clear mapping between costs and fundamental infrastructure or Software professionals curious to explore the data landscape for career growth It is particularly useful for Technical leaders adopting cloud in domain driven organizations or Executives seeking a big picture understanding of the cloud tranformation challenges of Data Science Adoption or Architectes and Solution Architects seeking pivots for explanining solutions to non technical audience or Infrastructure Engineers seeking a clear mapping between costs and fundamental infrastructure or Software professionals curious to explore the data landscape for career growth.
Enroll now: Data Lake, Lakehouse, Data Warehouse Fundamentals in 60 mins
Summary
Title: Data Lake, Lakehouse, Data Warehouse Fundamentals in 60 mins
Price: $19.99
Average Rating: 4.55
Number of Lectures: 29
Number of Quizzes: 10
Number of Published Lectures: 29
Number of Published Quizzes: 10
Number of Curriculum Items: 40
Number of Published Curriculum Objects: 40
Number of Practice Tests: 1
Number of Published Practice Tests: 1
Original Price: $19.99
Quality Status: approved
Status: Live
What You Will Learn
- Fundamentals about Data Lake, Data Lakehouse, Data Warehouse and consideration when using them in Data Science Solutions
- Basics about Data Fabric and Data Mesh and mapping them to Data Science use case
- General Challenges in building data science solutions using infrastructure products.
- Absolute fundamentals of computer science mapped to infrastructure products to understand cloud computing costs.
- Jargon and buzz words free precise mapping of fundamentals to data technology products.
- Course does NOT provide any step by step API based tutorials for any product or tool.
Who Should Attend
- Technical leaders adopting cloud in domain driven organizations
- Executives seeking a big picture understanding of the cloud tranformation challenges of Data Science Adoption
- Architectes and Solution Architects seeking pivots for explanining solutions to non technical audience
- Infrastructure Engineers seeking a clear mapping between costs and fundamental infrastructure
- Software professionals curious to explore the data landscape for career growth
Target Audiences
- Technical leaders adopting cloud in domain driven organizations
- Executives seeking a big picture understanding of the cloud tranformation challenges of Data Science Adoption
- Architectes and Solution Architects seeking pivots for explanining solutions to non technical audience
- Infrastructure Engineers seeking a clear mapping between costs and fundamental infrastructure
- Software professionals curious to explore the data landscape for career growth
In today’s data-driven world, data architecture and data science have emerged as transformative forces, empowering organizations to harness the power of information for unparalleled insights, innovation, and competitive advantage. This fundamentals course provides a structured yet flexible learning experience, equipping you with the essential knowledge and skills to excel in these highly sought-after domains.
The course takes a breadth-first approach, introducing learners to the evolving landscape. It does not contain any deep dives with specific APIs! Data architecture has no silver bullets, so please don’t expect one from the course as well.
Unravel the Fundamentals of Data Architecture
Delve into the intricacies of data architecture, the cornerstone of effective data management and utilization. Gain a functional understanding of data tools like data lake, and data lakehouse, and methods like data fabric, and data mesh, enabling you to design and implement robust data architectures that align with organizational goals.
Cost Optimization mindset
Learn to map everything to absolute fundamentals to keep a check on infrastructure costs. Understand the value of choosing optimal solutions from the long-term perspective. Master the art of questioning the new products from a value creation perspective instead of doing a resume-driven development.
Navigate the Complexities of Hybrid Cloud Management
As organizations embrace hybrid cloud environments, managing the diverse landscapes of cloud and on-premises infrastructure becomes increasingly complex. This course equips you with the basic strategies and ideas to navigate these complexities effectively.
Address the Challenges of Hiring and Retaining Data Science Talent
In the face of a global shortage of skilled data science professionals, attracting and retaining top talent is a critical challenge for organizations. This course delves into data science talent acquisition dynamics, providing practical strategies to identify, attract, and nurture top talent. Learn to create a data-driven culture that values continuous learning and innovation, fostering an environment where data scientists thrive and contribute to organizational success.
Overcome the Pitfalls of Outsourcing for Digital Transformation
While outsourcing can be a valuable tool for digital transformation initiatives, it also presents unique challenges. This course equips you with the knowledge and strategies to navigate these challenges effectively.
Key takeaways:
-
Master the fundamentals of data architecture necessary to build a robust solution for any use case, including data science.
-
Learn the need for strategies for hybrid cloud management, optimizing network performance, implementing unified security policies, and leveraging cloud-based backup and disaster recovery solutions.
-
Understand the various permutations of infrastructure tools for cloud offerings and services.
-
A fundamentals-driven framework to tackle the constantly changing cloud ecosystem.
Questions Fundamentals-driven framework can answer better:
-
What will be the complexity involved in moving from a Snowflake data warehouse to a Databricks data lakehouse?
-
How will the cloud costs increase over the next 5 years if moving from an on-premise HDFS to an AWS data lake?
-
What to buy and what to build when considering a data platform for an enterprise?
-
Is cloud-based data storage always cheap or does it introduce additional cost centers?
-
What is the difference between data fabric and data mesh?
-
When is the data management platform ready for prescriptive analytics?
-
Why is cost calculation for the cloud complex?
-
Does Kubernetes solve all problems around infrastructure management?
-
Why knowing only Python is not enough for building data science solutions?
-
What is cloud storage and why it is crucial in modern solutions?
Who should take this course:
-
Technical leaders shaping the digital transformation for domain-driven enterprise
-
Architects and solution architects seek a more straightforward vocabulary to communicate with nontechnical leaders.
-
Aspiring data architects seeking to establish a strong foundation in data architecture principles and practices
-
Data scientists seeking to enhance their skills and stay up-to-date with the latest advancements in architecture
-
IT professionals involved in data management, data governance, and cloud computing
-
Business professionals seeking to understand the impact of data architecture and data science on their organizations
Course Curriculum
Chapter 1: Introduction
Lecture 1: Introduction
Chapter 2: Fundamentals to get started from scratch with the Data management ecosystems
Lecture 1: From Atoms to Cloud Computing
Lecture 2: Demystifying Databases: A precise functional guide for Decision-Makers
Lecture 3: Demystifying Structured, Semi-Structured, and Unstructured Data in Modern Cloud
Lecture 4: Navigating the Data Landscape: Understanding Data Preparation or ETL Methods
Lecture 5: Navigating the Analytics Landscape: From Descriptive to Prescriptive Analytics
Lecture 6: Navigating the Cloud Landscape: IaaS, PaaS, SaaS from ownership perspective
Chapter 3: Data Tools Landscape : Data Warehouse, Data Lake, Data LakeHouse
Lecture 1: Data Warehousing: Unveiling the Architecture and Fundamentals
Lecture 2: Data Lake vs. Data Warehouse: Complementary Roles of Data Storage and Analytics
Lecture 3: Data Lakehouses: Unified Data Management Architecture for Modern Computing
Chapter 4: Methods: Modern DataWarehouse, Data Fabric, Data Mesh
Lecture 1: Modern Data Warehouses: A Practical Guide to Cost-Effective Data Management
Lecture 2: Demystifying Data Fabric: Building a Unified Data Management Architecture
Lecture 3: Delving into the Data Mesh: A Guide to Decentralized Data Management
Chapter 5: Data Architecture considerations for Data Science
Lecture 1: Data Science on Data Warehouses: Navigating the Challenges and Optimal Usage
Lecture 2: Data Science on Data Lakes: Navigating the Challenges & Unlocking the Potential
Lecture 3: Data Lakehouse: Unveiling the Challenges and Possibilities for Data Science
Lecture 4: Data Fabric: Navigating Challenges of Unifying Diverse Sources for Data Science
Lecture 5: Overcoming the Challenges of Data Mesh Implementation for Data Science
Lecture 6: Mastering the Challenges of ML Ops: Ensuring Success of Machine Learning Project
Lecture 7: A Primer for Conquering the Challenges of Data Infrastructure for Data Science
Lecture 8: Confidential Computing: Top Considerations for Secure Data Processing
Lecture 9: Challenges of Real-time Analytics: Unleashing the Power of Data-driven Insights
Chapter 6: Unseen Challenges around Digital Transformation and cloud adoption
Lecture 1: Top 10 cloud mistakes to avoid
Lecture 2: Top 10 Hybrid Cloud considerations: Navigating the Complexities of Unified Infra
Lecture 3: Top 10 Hiring Challenges For Data Science Professionals
Lecture 4: Decoding Digital Transformation: Maslow's Hierarchy of Needs for a Success
Lecture 5: Challenges of Outsourcing for Digital Transformation: Strategies for Success
Chapter 7: Applying the knowledge
Chapter 8: Conclusion
Lecture 1: Closing Remarks
Lecture 2: [Bonus Lecture] Reference Material with Links, Onboarding plan ideas and Notes
Instructors
-
RougeNeuron Academy By Subodh Chiwate
180,000+ Enrollments | Decoding Software Careers in AI era
Rating Distribution
- 1 stars: 1 votes
- 2 stars: 1 votes
- 3 stars: 4 votes
- 4 stars: 11 votes
- 5 stars: 11 votes
Frequently Asked Questions
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!
You may also like
- Top 10 Video Editing Courses to Learn in November 2024
- Top 10 Music Production Courses to Learn in November 2024
- Top 10 Animation Courses to Learn in November 2024
- Top 10 Digital Illustration Courses to Learn in November 2024
- Top 10 Renewable Energy Courses to Learn in November 2024
- Top 10 Sustainable Living Courses to Learn in November 2024
- Top 10 Ethical AI Courses to Learn in November 2024
- Top 10 Cybersecurity Fundamentals Courses to Learn in November 2024
- Top 10 Smart Home Technology Courses to Learn in November 2024
- Top 10 Holistic Health Courses to Learn in November 2024
- Top 10 Nutrition And Diet Planning Courses to Learn in November 2024
- Top 10 Yoga Instruction Courses to Learn in November 2024
- Top 10 Stress Management Courses to Learn in November 2024
- Top 10 Mindfulness Meditation Courses to Learn in November 2024
- Top 10 Life Coaching Courses to Learn in November 2024
- Top 10 Career Development Courses to Learn in November 2024
- Top 10 Relationship Building Courses to Learn in November 2024
- Top 10 Parenting Skills Courses to Learn in November 2024
- Top 10 Home Improvement Courses to Learn in November 2024
- Top 10 Gardening Courses to Learn in November 2024