Data Servers ImageThrivOn builds agile data warehouses that are built to last.

Traditionally, building of data warehouse or business intelligence environments often required that business model and analytical requirements be frozen before any technical development takes place. For many organizations today with changing business processes and new business requirements, this poses long term restrictions on leveraging the benefits of the data warehouse initiative.

When planning for a new Business Intelligence and Analytics infrastructure, organizations should learn from past mistakes. First-generation data warehouses spent many cycles building rigid and complex BI and Analytics solutions that became obsolete even before they went live. The Business Intelligence platform for any agile organization must be flexible enough to incorporate new requirements without having to undergo a cumbersome re-design and development effort.In addition it should provide integrated data sets to the analysts for predictive analytics. Incorporating Master Data Management and setting up structures and processes for effective Data Governance are also key to a successful data management program.

ThrivOn Methodology

Our innovative and iterative, AIM © (Adaptive Implementation Methodology) approach of building foundations for data management solution will eliminate a number of manual efforts in the Data Warehouse or Business Intelligence lifecycle thereby enabling rapid delivery of new analytical functionality to business.

The adaptive platform built using AIM © approach will also be able to adapt to changing business needs of the twenty-first century; be it starting a new business line/initiative, acquiring or merging businesses or just performing what-if scenarios, market competition and predictive analysis.

Salient features of ThrivOn Agile Data Warehousing Methodology

  • Perform business information modeling, not data modeling.
  • Automate the backend data warehouse creation and update for every change in business information model
  • Rapid iterative prototyping and user acceptance testing of business intelligence and data visualization
  • 2 – 3 weeks data warehouse release cycle
  • Virtually guaranteed buy-in of business users for every new change due to their early involvement.

Proven track record

Our approach has been tested and proved to be highly successful at some of world’s leading dynamic organizations, where change is constant.

  • World’s largest maker of consumer packaged goods handled a series of global multi-billion dollar acquisitions in their data warehouse using this approach
  • One of nation’s largest financial institution transitioned from a six months data warehouse release cycle to four week release cycle, thereby accelerating the market risk analytics modeling frequency by upto 10 times.
  • A leading health insurance company increased their reimbursement from the state in millions of dollars and also secured one of highest quality rating attributed to better data quality in the data warehouse.
  • A large P&C insurance company replaced their legacy data warehouse with agile data warehouse and got ready for IPO in record nine months.



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