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Google Cloud Training
This is a self-paced lab that takes place in the Google Cloud console. In this hands-on lab, you will import synthetic data* representing financial records offloaded from a bank’s mainframe.
Register for this course and see more details by visiting:
OpenCourser.com/course/r6zr49/offloading
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What's inside
Syllabus
Traffic lights
Traffic lights
Read about what's good
what should give you pause and
possible dealbreakers
Studies a domain-specific topic using theory and practice
Exploration of financial mainframe data is standard in the banking industry
Suitable for those with some experience in data analysis
Requires a foundational understanding of BigQuery and Elastic Search
May not be appropriate for beginners in data analysis
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Reviews summary
Practical mainframe data offloading to gcp
According to students, this is a highly practical and relevant hands-on lab focused on offloading financial mainframe data into BigQuery and Elastic Search within the Google Cloud console. Learners particularly commend the detailed steps and direct applicability to real-world data migration challenges, especially for professionals in financial tech and mainframe development. However, some learners noted that the course assumes a certain level of prior knowledge in GCP or data warehousing, making it potentially challenging for absolute beginners. More experienced cloud engineers, on the other hand, might find the content somewhat basic, wishing for more advanced techniques or depth in areas like optimization. Despite these points, the course is generally viewed as an excellent stepping stone for its niche, practical application.
Highly relevant for professionals migrating financial mainframe data.
"The focus on financial data made it very relatable."
"Very specific and useful. The practical application of offloading data from mainframes to modern cloud tools is exactly what I needed."
"Moving legacy financial data is a huge challenge, and this course tackles it head-on with practical steps. I gained significant insights into the process and tooling."
Provides invaluable hands-on experience and real-world applicability.
"This lab was incredibly practical and directly applicable to my work."
"Excellent course! As a mainframe developer looking into cloud solutions, this lab was a perfect bridge... I particularly appreciated the detailed steps and the fact that it was entirely hands-on."
"Highly relevant and practical. The hands-on aspect made all the difference. It's a challenging but rewarding lab, perfectly suited for professionals dealing with legacy financial systems."
Simplistic for advanced users, lacks advanced techniques or troubleshooting.
"I wish there was more depth on optimization or error handling for large-scale production environments."
"Okay, but a bit simplistic. For experienced cloud engineers, it might be too basic. I was hoping for more advanced techniques or troubleshooting tips for real-world scenarios."
"Useful if you're a complete beginner in this specific offloading concept, but the content depth left something to be desired for me."
Some steps clear and others require external lookup or debugging.
"I found the initial setup a bit confusing, but once past that, the core concepts of offloading data were clear."
"Disappointing. The lab instructions were unclear at points, leading to errors. I spent more time debugging than learning."
"My only minor gripe is that some explanations felt a bit brief; I had to look up external documentation a couple of times."
May challenge beginners lacking prior GCP or data warehousing.
"If you're completely new to BigQuery or Elastic Search, you might struggle."
"It assumes a certain level of prior knowledge, which wasn't explicitly stated. The concept is valuable, but the execution could be more beginner-friendly."
"It felt like it was designed for someone already familiar with the setup, not for learning from scratch. Not what I expected from a Google Cloud lab."
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Offloading Financial Mainframe Data into BigQuery and Elastic Search with these
activities:
Review SQL Basics
Show steps
Review basic SQL syntax and concepts to prepare for data analysis tasks.
Browse courses on
SQL
Show steps
-
Review online or textbook materials on SQL basics.
-
Practice writing simple SQL queries.
Financial Data Analysis Concepts
Show steps
Review fundamental concepts related to financial data analysis and interpretation.
Browse courses on
Financial Data Analysis
Show steps
-
Review materials on financial data analysis techniques.
-
Identify key metrics and indicators in financial statements.
Financial Data Resources Collection
Show steps
Compile a list of useful resources, including datasets, tools, and articles, related to financial data analysis.
Browse courses on
Financial Data
Show steps
-
Search for and identify relevant resources.
-
Organize resources into a structured document or website.
-
Share the compilation with other students or professionals.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Practice Queries
Show steps
Complete SQL queries in your own environment to reinforce understanding of data querying and analysis techniques.
Show steps
-
Setup a local database environment.
-
Review basics of SQL.
-
Import the provided financial data.
-
Write queries to extract and analyze data.
BigQuery Advanced Analysis Tutorial
Show steps
Follow an online tutorial to enhance your understanding of advanced BigQuery features for data analysis.
Browse courses on
BigQuery
Show steps
-
Choose a tutorial on advanced BigQuery analysis.
-
Follow the tutorial steps.
-
Apply the techniques to your own dataset.
Elasticsearch Data Visualizations
Show steps
Create interactive data visualizations to gain insights from the financial records in Elasticsearch.
Browse courses on
Elasticsearch
Show steps
-
Review data visualization best practices.
-
Choose a visualization tool.
-
Connect to Elasticsearch and import data.
-
Design and create visualizations.
Financial Fraud Detection Model
Show steps
Develop a machine learning model to detect fraudulent financial activities in the imported dataset.
Show steps
-
Review machine learning algorithms for fraud detection.
-
Choose a programming environment and tools.
-
Engineer features from the financial data.
-
Train and evaluate the model using supervised learning.
Review SQL Basics
Show steps
Review basic SQL syntax and concepts to prepare for data analysis tasks.
Browse courses on
SQL
Show steps
Show steps
Show steps
- Review online or textbook materials on SQL basics.
- Practice writing simple SQL queries.
Financial Data Analysis Concepts
Show steps
Review fundamental concepts related to financial data analysis and interpretation.
Browse courses on
Financial Data Analysis
Show steps
Show steps
Show steps
- Review materials on financial data analysis techniques.
- Identify key metrics and indicators in financial statements.
Financial Data Resources Collection
Show steps
Compile a list of useful resources, including datasets, tools, and articles, related to financial data analysis.
Browse courses on
Financial Data
Show steps
Show steps
Show steps
- Search for and identify relevant resources.
- Organize resources into a structured document or website.
- Share the compilation with other students or professionals.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Practice Queries
Show steps
Complete SQL queries in your own environment to reinforce understanding of data querying and analysis techniques.
Show steps
Show steps
Show steps
- Setup a local database environment.
- Review basics of SQL.
- Import the provided financial data.
- Write queries to extract and analyze data.
BigQuery Advanced Analysis Tutorial
Show steps
Follow an online tutorial to enhance your understanding of advanced BigQuery features for data analysis.
Browse courses on
BigQuery
Show steps
Show steps
Show steps
- Choose a tutorial on advanced BigQuery analysis.
- Follow the tutorial steps.
- Apply the techniques to your own dataset.
Elasticsearch Data Visualizations
Show steps
Create interactive data visualizations to gain insights from the financial records in Elasticsearch.
Browse courses on
Elasticsearch
Show steps
Show steps
Show steps
- Review data visualization best practices.
- Choose a visualization tool.
- Connect to Elasticsearch and import data.
- Design and create visualizations.
Financial Fraud Detection Model
Show steps
Develop a machine learning model to detect fraudulent financial activities in the imported dataset.
Show steps
Show steps
Show steps
- Review machine learning algorithms for fraud detection.
- Choose a programming environment and tools.
- Engineer features from the financial data.
- Train and evaluate the model using supervised learning.
Career center
Learners who complete Offloading Financial Mainframe Data into BigQuery and Elastic Search will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
Data Analysts design and build data collection and analysis systems to help businesses make informed decisions. This course can give you the skills you need to succeed as a Data Analyst by showing you how to use BigQuery and Elastic Search to manage and analyze data. These skills will provide a foundation for jobs that require expertise in data analysis and interpretation.
Data Engineer
Data Engineer
Data Engineers build and maintain the infrastructure that stores and processes data for businesses. This course can help teach you how to use BigQuery and Elastic Search to set up and manage data systems as a Data Engineer.
Data Scientist
Data Scientist
Data Scientists use data to solve business problems and develop new products and services. This course can give you the skills you need to succeed as a Data Scientist by showing you how to use BigQuery and Elastic Search to analyze data and extract insights.
Cloud Architect
Cloud Architect
Cloud Architects design and build cloud infrastructure for businesses. This course will help teach you how to use BigQuery and Elastic Search to manage data in the cloud for this role.
Software Developer
Software Developer
Software Developers design, build, and maintain software applications for businesses. This course may help you build a foundation for this role by teaching you how to manage data using BigQuery and Elastic Search.
Business Analyst
Business Analyst
Business Analysts help businesses understand their data and make informed decisions. This course may help you develop the data analysis skills needed for this role by teaching you how to use BigQuery and Elastic Search to manage and analyze data.
Database Administrator
Database Administrator
Database Administrators manage and maintain databases for businesses. This course may help teach you how to use BigQuery and Elastic Search to manage data as a Database Administrator.
Information Security Analyst
Information Security Analyst
Information Security Analysts help businesses protect their data from unauthorized access and use. This course may help you develop skills relevant to this role by teaching you how to manage and analyze data using BigQuery and Elastic Search.
Financial Analyst
Financial Analyst
Financial Analysts help businesses make financial decisions. This course may help you develop the data analysis skills needed for this role by teaching you how to use BigQuery and Elastic Search to manage and analyze financial data.
Data Warehouse Engineer
Data Warehouse Engineer
Data Warehouse Engineers design and build data warehouses for businesses. This course may help you develop the skills needed for this role by teaching you how to use BigQuery and Elastic Search to manage and analyze data.
Big Data Engineer
Big Data Engineer
Big Data Engineers design and build systems to manage and analyze large datasets. This course may help you develop the skills needed for this role by teaching you how to use BigQuery and Elastic Search to manage and analyze data.
Data Visualization Analyst
Data Visualization Analyst
Data Visualization Analysts help businesses visualize and interpret data. This course may help you develop the skills needed for this role by teaching you how to use BigQuery and Elastic Search to manage and analyze data.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design and build machine learning models for businesses. This course may help you develop the skills needed for this role by teaching you how to use BigQuery and Elastic Search to manage and analyze data.
Software Test Engineer
Software Test Engineer
Software Test Engineers test software applications for businesses. This course may help you develop the skills needed for this role by teaching you how to use BigQuery and Elastic Search to manage and analyze data.
Data Mining Engineer
Data Mining Engineer
Data Mining Engineers design and build systems to extract insights from data for businesses. This course may help you develop the skills needed for this role by teaching you how to use BigQuery and Elastic Search to manage and analyze data.
For more career information including salaries, visit:
OpenCourser.com/course/r6zr49/offloading
Reading list
We've selected 11 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Offloading Financial Mainframe Data into BigQuery and Elastic Search.
Provides a practical guide to using Google Cloud Platform for big data analytics. It covers topics such as data engineering, data science, and machine learning.
Provides a comprehensive overview of Elasticsearch, an open-source search and analytics engine. It covers topics such as Elasticsearch installation, configuration, and querying.
Gives a good introduction to machine learning, a key area in data science. It covers topics such as machine learning algorithms, data preprocessing, and model evaluation. This can be used as a supplement for the course.
This comprehensive guide to Hadoop, a popular framework used for distributed computing and big data processing. It covers topics such as Hadoop installation, configuration, and administration.
Save
Provides a gentle introduction to deep learning, a subfield of machine learning that has gained popularity in recent years. It covers topics such as neural networks, deep learning architectures, and deep learning applications.
Provides a practical overview of cloud computing. It covers topics such as cloud architecture, cloud services, and cloud security.
Provides an introduction to natural language processing, a subfield of AI that deals with the interaction between computers and human (natural) languages. It covers topics such as text analysis, sentiment analysis, and machine translation.
Provides a practical guide to data science. It covers topics such as data exploration, data modeling, and data visualization. It also provides hands-on examples using popular data science tools.
Provides an introduction to computer vision, a subfield of AI that deals with the interaction between computers and images. It covers topics such as image processing, object recognition, and facial recognition.
Can serve as a reference to the course. It comprehensively discusses data warehousing and how it is used to store and manage large amounts of data. It also covers data warehouse design, implementation, and maintenance.
Provides a gentle introduction to data science. It covers topics such as data cleaning, data analysis, and data visualization.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/r6zr49/offloading
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