Upcoming Webinar: How to Boost Your Bottom Line: Achieving Greater Profits with Automated Inventory Optimization

Intuition tells us that an inventory item with 65% gross margin, everything else being the same, should have a higher service level/safety stock than one with 10% for the sake of maximizing profit. However, traditional methods fail to quantify exactly how much the service levels/safety stocks should differ between these items. This causes companies millions of dollars in lost profits every year.

Our proprietary Safety Stock Price Model, developed by Dr. Jay Zhou, solves this issue. The model accurately calculates the ideal service levels and safety stocks based on your products' gross margins. For the above example, it prescribes service levels of 99% vs 92% and safety stocks of 282 vs 170 units for the 65% vs 10% margin items (see the picture below). By optimizing service levels and safety stock in this way, your company's profit is maximized - exactly what you and your executives want!

Join our free webinar tomorrow at 9am ET to learn how our algorithm can boost your bottom line through smarter inventory optimization. Dr. Zhou will explain why traditional methods fall short and how our patented approach is the true path to greater profits. Register now here for "How to Boost Your Bottom Line: Achieving Greater Profits with Automated Inventory Optimization" on Wednesday, November 1st at 9am ET

Upcoming Webinar on How to Boost Your Bottom Line: Achieving Greater Profits with Automated Inventory Optimization

Upcoming Webinar on How to Boost Your Bottom Line: Achieving Greater Profits with Automated Inventory Optimization -Why Traditional Methods Fall Short and How Our Algorithm is the True Path to Financial Success
Will be delivered by Dr. Jay Zhou on Wednesday, November 1st 2023 - 9:00 PM (EDT). Please register here.

Speeding Up Bulk Data Loads in Oracle with Hints

Bulk loading volumes of data from staging tables into production tables is a common task, but a slow and tedious process using basic INSERT statements in Oracle. But using query hints can dramatically improve load times, as I recently discovered how dramatical it could be.

In our ETL process, we needed to load order data from a staging table to the main orders table. Our initial INSERT statement looked like:

    INSERT INTO Orders (order_id, customer_id, order_date, total_amount)
       SELECT order_id, customer_id, order_date, total_amount
         FROM Staging_Orders;

This took many hours to millions of rows. But then we came across hint syntax that lets you fine-tune SQL behavior.
Adding a parallel and direct-path hint like:

INSERT /*+ APPEND PARALLEL(4) */ INTO Orders (order_id, customer_id, order_date, total_amount)
SELECT order_id, customer_id, order_date, total_amount
FROM Staging_Orders;

In the above SQL statement, the /*+ APPEND */ hint instructs Oracle to perform a Direct Path Insert for faster data loading. and the PARALLEL(4) hint instructs Oracle to use parallel processing with four parallel execution servers (you can adjust the number as needed based on your system's resources).

The results were mind-blowing - loading finished in under 10 minutes! For big data loads, enabling direct-path INSERT with parallelism cuts the time from hours to minutes.

I hope this example gives you some ideas on optimizing bulk data operations in Oracle through hints. Let me know if you have any other tips for supercharged ETL performance!