Advanced Data Development Platform
(ADDP)
Milovan Tomašević*
*Data & Software Engineer/Architect (PhD)
March, 2023 @ Ljubljana, Slovenia
Created by 23.03.2023. 23:23, press ESC for overview
- Advanced Data Development Platform (ADDP) is an end-to-end data analysis platform that helps businesses extract value from their data.
- ADDP supports extract, transform, and load (ETL) and extract, load, and transform (ELT) patterns*, allowing businesses to ingest their data, transform it, and extract value from it.
*Pattern 1 – ETL, Pattern 2 – ELT (Data Warehouse), Pattern 3 – ELTL (Data Warehouse + Data Lake), Pattern 4 – ELtLT (Data Warehouse + Data Lake), Pattern 5 – ELT (Data Lakehouse), …
- ADDP helps R&D teams accelerate product development, increase productivity, and the success of scientific discoveries.
- It is an integrated data stream without code that optimizes resources and increases productivity, simplifies visual verification of data, and automates data management.
- ADDP helps businesses unify their entire end-to-end data journey with Artificial Intelligence and Machine Learning capabilities in an All-in-One Big Data platform.
- It can solve complex integrations with a few clicks and connect the system or data source with agility and scalability to grow the business.
- Businesses can create and deliver APIs in a fast, scalable, and secure way, connecting their business with digital solutions with the best experience.
Industry-Specific Applications
- ADDP can be applied to specific needs in various industries.
- For retail, ADDP offers smart sales for omnichannel strategies that increase sales and integrate the ecosystem.
- For the financial industry, ADDP offers automated trading and credit management using alternative data, market data, and machine learning algorithms.
- In the healthcare industry, ADDP helps automate medical and hospital receivables management through data, achieving greater transparency and efficiency in processes.
- ADDP is designed for non-technical users, data engineers, and data scientists.
- Non-technical users can use Pipelines, Jobs, and Visualize to extract value from the data using low code.
- Data engineers can use visualization tools using SQL and the Sandbox to develop python applications.
- Data scientists can use the data already made available by data engineers in their python algorithms through notebooks in the Sandbox feature.
- ADDP’s features include Pipelines, Jobs, Sandbox, and Visualize.
- Pipelines execute data ingestion periodically, while Jobs execute a series of chosen steps when a selected trigger is activated.
- The Sandbox is a web application that allows businesses to create and share documents that contain live code, equations, visualizations, and narrative text.
- Visualize enables businesses to visualize their data, enabling all stakeholders to gain insights quickly and efficiently.
Conclusion and Call to Action
- Overall, ADDP represents a valuable solution for businesses looking to extract value from their data.
- It offers a range of benefits, including data quality, optimizing time and workload, automation, data integration, cataloging, and data retrieval, and team productivity.
- By leveraging ADDP, businesses can stay ahead of the curve and achieve success in the marketplace.