Having multiple sources of the same data creates unnecessary redundancies that erode data integrity and data warehouse performance. Paragon helps clients create a single repository of data by consolidating sources and integrating the disparate sources when necessary. Whether a data migration or conversion, the process of capturing the data involves the following:
Not all data is created equal. Data that is not necessary for strategic analysis is not incorporated into the development of the data warehouse. Unnecessary data slows the development process and makes the data warehouse less efficient.
Selected data is extracted from its source.
Data representation is transformed from a variety of coding structures among the data sources into one structure.
Data from multiple sources is combined into a standardized, optimized source.
Data is cleansed and updated to meet quality expectations. The validation may detect an error that requires a manual or automated fix.
Data is prepared for loading in the staging area by making a backup of the data and sequencing the sources and data before loading into the data warehouse.
- ETL Implementation and Optimization
One of the most common tools implemented in a data management engagement is one that automates the ETL process. Paragon has experience selecting, implementing and optimizing those tools most appropriate for improving productivity of a client’s data warehouse.
- Data Quality Remediation
Improving the quality of the data accessed by key systems remains a critical challenge for clients looking to improve the productivity of their data warehouses and data marts. Paragon employs a best practice approach to assessing and improving the quality of the data sources.
User-Driven Business Analytics
Paragon is a leader in delivering business intelligence solutions,
from User-Driven visualization tools to large scale Data
Data Warehousing / CRM
A leading telecommunications company needed to market more effectively to a key segment of 12 million business contacts. The
root of the challenge was to reduce cycle time to process lead information and to generate higher quality market analysis. The
client’s existing system was not robust enough to accurately target its existing business prospects. To accomplish this, the client
needed to integrate three separate mainframe marketing systems into one consolidated server-based data warehouse with flexible
A leading telecommunications firm was seeking to automate its existing transaction pricing scorecard, which tracked contract
pricing levels on strategic products and compared realized prices for similar deals.