Technical Definition – A special purpose data store used to aggregate varied data sources into a uniform, single source of truth.
For many businesses, data is a vital part of the ecosystem. It drives creation, state retrieval, and updates of various business objects. At times, however, as applications or business domains mature, these data sources can grow or multiply at an unexpected rate. In other cases, a flagship application might need a way to process data from various, non-uniform sources. This can lead to unnecessary overhead, such as manual processing, and can lead to data inconsistencies between supposedly connected systems. Business decisions are often directly impacted by data, so it’s a problem if the stakeholders can’t make sense of it. In these situations, we can find solutions to these problems in a Data Warehouse. Data Warehouses can store large, processed amounts of data, most importantly in a standardized format. This allows business to confidently rely on a single source of truth to power applications and BI for a particular domain, while being flexible enough to consume varying data from multiple sources.
We’re no strangers to data at alligatortek, and, likewise, have extensive experience implementing solutions that are based on data warehouses. Most recently, we were chosen by a financial services and insurance firm to lead their internal effort of a data warehouse rebuild to support BI solutions. That effort was kicked off with the automation of their ETL process.