The Rising Complexity of Data – Why Traditional Data Services FailData is increasingly becoming an essential part of businesses. Companies have to gather huge amounts of data in various forms, such as receipts, images, e-documents, audio, etc. Although this data allows organizations to gain additional insight and value, the sheer volume of data makes it incredibly difficult to process and control. Due to the absence of concrete procedures, companies struggle to aggregate, organize, and manage data from disparate sources. Numerous data sources overwhelm under-equipped organizations and bad management leads to data inconsistencies. This prevents them from extracting value from data and making most of the resources they have. As the volume of data and its sources expands, organizations develop multiple data silos, making data management increasingly complex. Here a few ways data silos affect your organization’s productivity:
- Data silos stop companies from delivering real-time insights and meet the analytical needs of their business in a timely manner.
- Data gets replicated across multiple data silos, decreasing reducing transparency and resulting in time-consuming reconciliation efforts.
- Organizations struggle to handle new data types in the absence of relevant processes.
- The demand for data-driven insights and analytics continues to increase among both internal and external elements of your organization.