Unlock the full potential of PL/SQL and revolutionize your data processing performance!
This comprehensive course is designed to equip you with the skills to optimize your Oracle database operations through the effective use of bulk data processing techniques. Learn how to harness the power of PL/SQL to handle large datasets efficiently and improve query performance dramatically.
You will delve into advanced PL/SQL concepts, including bulk SQL, collections, and performance tuning, to streamline your data manipulation processes. Discover best practices for loading, updating, and deleting data in bulk, and gain a deep understanding of how to optimize your code for maximum efficiency.
Whether you're a database developer, data analyst, or DBA, this course will provide you with the knowledge and tools to tackle complex data processing challenges and deliver exceptional results.
Key features:
In-depth exploration of PL/SQL bulk operations: Master the intricacies of bulk SQL, including FORALL, BULK COLLECT, and RETURNING INTO clauses. Understand when and how to apply these techniques effectively.
Advanced collection types: Learn to leverage associative arrays, nested tables, and arrays to optimize data handling and manipulation.
Performance tuning best practices: Identify performance bottlenecks, analyze execution plans, and apply indexing and partitioning strategies to enhance query performance.
Data loading and unloading techniques: Explore efficient methods for importing and exporting large datasets, including SQL*Loader, external tables, and data pumps.
Real-world scenarios and case studies: Apply your knowledge to practical examples and learn from real-world challenges faced by database professionals.
Hands-on exercises and projects: Gain practical experience through hands-on exercises and build your own PL/SQL applications.
Expert instruction from experienced database professionals: Benefit from the expertise of industry professionals who share their insights and best practices.
By the end of this course, you will be able to:
Significantly improve the performance of your PL/SQL applications.
Optimize data loading and unloading processes.
Effectively handle large datasets with ease.
Write efficient and maintainable PL/SQL code.
Become a sought-after PL/SQL expert in the industry.
Enrol now and experience the transformative power of PL/SQL for your data processing needs!
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Hello, I'm Akhil, a Senior Data Scientist at PwC specializing in the Advisory Consulting practice with a focus on Data and Analytics.
My career journey has provided me with the opportunity to delve into various aspects of data analysis and modelling, particularly within the BFSI sector, where I've managed the full lifecycle of development and execution.
I possess a diverse skill set that includes data wrangling, feature engineering, algorithm development, and model implementation. My expertise lies in leveraging advanced data mining techniques, such as statistical analysis, hypothesis testing, regression analysis, and both unsupervised and supervised machine learning, to uncover valuable insights and drive data-informed decisions. I'm especially passionate about risk identification through decision models, and I've honed my skills in machine learning algorithms, data/text mining, and data visualization to tackle these challenges effectively.
Currently, I am deeply involved in an exciting Amazon cloud project, focusing on the end-to-end development of ETL processes. I write ETL code using PySpark/Spark SQL to extract data from S3 buckets, perform necessary transformations, and execute scripts via EMR services. The processed data is then loaded into Postgres SQL (RDS/Redshift) in full, incremental, and live modes. To streamline operations, I’ve automated this process by setting up jobs in Step Functions, which trigger EMR instances in a specified sequence and provide execution status notifications. These Step Functions are scheduled through EventBridge rules.
Moreover, I've extensively utilized AWS Glue to replicate source data from on-premises systems to raw-layer S3 buckets using AWS DMS services. One of my key strengths is understanding the intricacies of data and applying precise transformations to convert data from multiple tables into key-value pairs. I’ve also optimized stored procedures in Postgres SQL to efficiently perform second-level transformations, joining multiple tables and loading the data into final tables.
I am passionate about harnessing the power of data to generate actionable insights and improve business outcomes. If you share this passion or are interested in collaborating on data-driven projects, I would love to connect. Let’s explore the endless possibilities that data analytics can offer!
