The operations of global manufacturers of industrial and consumer packaging produce ever increasing quantities of data that need to be sorted and analyzed for business insight and reporting requirements. A failure to manage this data effectively can hamper effective decision-making, reduce efficiency and lead to compliance issues.
Here is how Mindtree helped a North American industrial and consumer packaging major build an innovative data warehouse to integrate data from different sources and support efficiency as well as effectiveness.
The customer’s existing data warehouse had been build for a single division and had grown without a unifying strategy to take on new sources of information and geographies. Within a few years it had expanded 1500%, with more than 50,000 reports and ad hoc downloads per month. Its unstructured growth meant that reporting quality had steadily declined, and auditing and tracking was virtually impossible. The need to merge new business units with the existing repository made an effective data warehouse solution an urgent issue for the customer.
The customer tasked Mindtree with developing a next-generation data warehouse that could take care of its business and IT needs; and allow robust and rapid reporting, including next-day availability of select reports for business decision makers.
Mindtree collaborated with the customer to devise a data warehousing strategy and implementation plan. We determined that the best solution lay in data vault modeling, a lesser known approach compared to the conventional dimensional modeling method. Data vault modeling is designed to provide historical storage of data from multiple operational systems leveraging a hybrid approach.
We ﬁrst developed a logical architecture for the warehouse including the design for a staging area, Transactional Data Store (TDS) and data marts. Following that, we built the data vault components. Throughout the engagement, Mindtree remained focused on the customer's current as well as future needs.
Our innovative approach made it easier for the customer to integrate data from new sources and has equipped them with better reporting capabilities. In addition, our approach enabled a more rapid data warehouse implementation, including reducing Extract, Transform and Load (ETL) design and development time by approximately 50%. Where appropriate, the team pointed out data quality issues and ﬂaws in business processes to help the customer improve its performance. Keeping in mind the customer's current issues, Mindtree also improved data preservation, ease of audit and back tracking.
Following the success of this initiative, the customer has added further data warehouses leveraging the data vault approach.