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Datasource principles have experience building and directing BI and data integration departments for major corporations. We know first hand what it takes to manage an initiative after the consultants have left. Our methodologies focus on implementing lean, innovative solutions that we have discovered to be successful from inside the corporate walls, not simply literature, conferences and external consulting engagements.

Steve Dine, President - Steve founded Datasource Consulting to help customers implement successful, maintainable data integration and business intelligence solutions. He built and led a successful global business intelligence program for a major global medical manufacturing company and led the business intelligence practice for a Colorado based consulting company. With more than 10 years of business and IT experience, Steve combines hands-on technical experience with strong business acumen. He helps companies design and implement high level, strategic data integration and lean BI architectures that align to the unique requirements of each individual organization. He has also helped companies by providing vendor neutral assessments for new and existing BI programs. Steve earned his bachelor degree from the University of Vermont and an MBA from the University of Colorado at Boulder.  He teaches a course on the topic of Lean BI at The Data Warehouse Institute world conferences.

Michael Sykes, VP Business Development -  Michael has both a deep technical knowledge of Business Intelligence and large team management experience. He has been responsible for architecting, developing and implementing several Enterprise Business Intelligence and Finance Performance Management solutions. These solutions included multi-Terabyte, Real-Time Data Warehouses with extensive Data Quality/Reconciliation processes and dashboards. He is well versed and have extensive experience in the major Data Warehouse architectures and development methodologies. He has been a guest presenter at The Data Warehouse Institute’s (TDWI) World Conference and has contributed to several articles related to Data Warehousing published in industry trade magazines.

David Crolene, Senior Solution Architect - Dave is a highly experienced BI Developer and Program Manager with more than 13 years in Business Intelligence & Data Warehousing. He is a strong influencer and motivator able to create an energetic team spirit, and interface effectively with other areas of the business. He has partnered with executive teams and fosters effective relationships with vendors, clients, peers and subordinates to align infrastructure strategies with business system needs, technical and service requirements. He has established standards, provides technical leadership, and drives technology design, development, testing and problem solving to meet requirements, improve quality, and complete delivery on-time and within cost.

Matthew Caton, Principle Consultant - Matt specializes in implementing, customizing, and optimizing a variety of front-end enterprise reporting solutions. He has more than 8 years of Business Intelligence (BI) experience and a solid understanding of data warehousing. He has a deep level of experience across a variety of tool sets including, Cognos, Business Objects, Microsoft BI and Jaspersoft.  He has worked on every aspect of a full life-cycle BI implementation. He has consulted for a variety of clients within a broad array of industries including, Telecommunications, Merchant Services, Retail and Mining.

Nancy Abramson - Principle Cloud Evangelist - Nancy is an insightful, results-driven integration developer and statistical analyst that provides optimally integrated business problem solutions using data tools including SQL, SAS, ETL and predictive analytics. She has a deep level of experience working and managing deployments in the Amazon Cloud and has led the development of the Datasource Cloud Strategy.  In addition, she is a certified SAS 9 Base Programmer, Oracle SQL Expert and has experience with multivariate optimization, very large database (VLDB) analysis and data warehouse architecture. 




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