As local Large Language Models (LLMs) continue to mature, the common consensus is often “bigger is better.” If you want production-grade code, you run a 7B or 14B parameter model. If you run a small 3B model, you accept compromised logic. But when you are developing on budget hardware—like an older NVIDIA GTX 1650 with […]
Apache Superset Dashboard: Gaining Insights into SKU Performance with the Complete Journey Dataset
Learn how to move beyond simple revenue rankings and identify truly high-performing departments using efficiency analysis. By comparing revenue contribution against SKU footprint, filtering out outliers, and creating a normalized efficiency metric, you’ll uncover hidden winners such as Salad, validate Groceries’ consistent strength, and reveal opportunities for assortment optimization, pricing strategy, promotions, and category management.
Preparing Apache Superset with Real-World Data: Loading the dunnhumby “The Complete Journey” Dataset into PostgreSQL
To explore Apache Superset beyond simple sample data, it helps to work with realistic business datasets such as dunnhumby’s **The Complete Journey**. While most CSV files can be imported into PostgreSQL using DBeaver without issues, the `causal_data.csv` file requires special handling because the `display` column should be defined as `VARCHAR` before import. This article walks through the issue, the PostgreSQL table definition that resolves it, and how to successfully load the dataset for building retail analytics dashboards in Apache Superset.
Fixing Apache Superset Connection to Host PostgreSQL from Docker
Connecting Apache Superset in Docker to a PostgreSQL database on the host initially failed despite successful network connectivity. After troubleshooting PostgreSQL listening addresses, Docker networking, and firewall rules, the root cause was identified as a missing PostgreSQL driver (`psycopg2`) inside the Superset container. Installing `psycopg2-binary` resolved the issue and allowed Superset to connect successfully.
The Analytics Software Comparison Matrix
“A strategic feature-by-feature comparison of top analytics software. Learn how to eliminate dashboard bottlenecks and plug financial cost leaks. The analysis reveals that proprietary giants like Power BI offer the highest overall feature scores but trigger compounding licensing fees. Conversely, modern open-source alternatives like Apache Superset deliver up to 80% of that critical operational utility at zero software cost.
Dynamic Approval Workflow with Drools
Business rule automation implementation – using Drools for dynamic approval process where rules assess the order amount and determine the right approval.
Understanding Drools Components
Discover how Drools, Business Central, and KIE Server work together to design, manage, and execute business rules effectively.
Installing Drools
Step-by-step guide to installing Drools with Docker. Learn how to set up Business Central and KIE Server, deploy rules, and verify your installation.
Sistem Operasi – 18 – Queueing Theory, Disk Scheduling, and File Systems.
Disc scheduling is an important process in operating systems that determines the order in which disk access requests are serviced. The objective of disc scheduling is to minimize the time it takes to access data on the disk and to minimize the time it takes to complete a disk access request.
Sistem Operasi – 17 – Performance, Storage Devices.
Advances in computer technology have mostly concentrated on processing power and not much on the I/O and storage component. This is why the CPU and GPU have advanced in leaps and bounds while system storage like the hard disk drive has only advanced moderately.