"Mindspan team has done a wonderful job with the design and implementation of the AMC data mart and OLAP solution. Their professionalism and hard work were evident in all aspects of the project. My compliments to them for a job well done. They are a pleasure to work with."
"Reporting from a central data warehouse are at the core of the Project Controls applications. Mindspan has made a significant contribution to our success in this area."
Dwight Pullen MIS Manager, Hartsfield Development Program, Hartsfield Atlanta International Airport
Businesses across industries are using Business Intelligence (BI) to get insight into customer information and behavior, product profitability, marketing campaigns, and several other aspects of business performance. The purpose of BI is to provide management with analytical inputs to make better informed decisions and drive business results. Data warehouses and data marts form the bedrock that supports all BI applications.
Designing and implementing data warehouses and data marts, and enabling users to access and analyze data through BI applications is one of Mindspan's core competencies. We employ a data warehouse solution development methodology that has matured with years of experience and learning.
DW Solution Development Methodology
Decision support and analysis requirements definition, i.e., identifying information analysis and reporting needs of users to add value to strategic or tactical decision making
Architecting a data warehousing solution that is robust, efficient and scalable
Designing data warehouses and data marts using dimensional data modeling
Developing applications to extract, transform and load (ETL) data from source databases into the data warehouse and/or data marts
Implementing mechanisms to ensure data quality and hygiene
Developing end-user applications using OLAP and reporting tools
From our experience of successfully delivering several data warehousing
and BI solutions and through interaction with leading industry experts,
we have systemized many best practices that lead to quality and efficiency
gains in the projects we undertake. Some examples are:
Standard templates for design documentation
Standards and guidelines for dimensional data modeling
A standard and effective approach for loading a data warehouse from multiple sources
