A data silo is a collection of data held by one group that isn’t easily or fully accessible by other groups in the same organization. Departments manage their own data in their own silos, and even when they share their data, they deliver it in a format that isn’t consistent across departments. Data silos create problems when information is shared because the data must first be reformatted before it can be used. Data silos get in the way of cross-departmental collaboration because of the time it takes to determine who holds the data and the effort it takes to manually alter the data for cross-departmental questions. These silos prevent leadership from having a holistic view of their business as importing data from multiple departments is a time- and resource-intensive undertaking. Worst of all, it’s hard to trust the data that’s finally found and aggregated because differences in methodology, quality, and metadata keep the data from aligning well across silos.
With an end-to-end analytics platform, an organization can connect and standardize disparate data sources. The platform automates the connection to data sources, applies formatting automatically, and moves data from silos into a shared repository that all departments can access. It makes data visible and accessible across the organization, with defined metadata that simplifies use. The platform gives business users access to self-service analytics so users can work with trusted data that has an established data lineage.
When users know the process and trust the data, they can use the end-to-end platform to arrive at their own insights. The previously arduous task of trying to analyze data across silos becomes far more efficient.