Introduction

• Advanced Data Development Platform (ADDP) is an end-to-end data analysis platform that helps businesses extract value from their data.

ETL and ELT Patterns

• 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), …

Benefits for R&D Teams

• 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.

Benefits for Businesses

• 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.

User-Specific Benefits

• 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.

Key features of ADDP

• 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.