How to Avoid the Data Silo Trap
The key goal of a data-centered architecture is data accessibility. Accessibility can impact future business innovation, improve the ability to generate metadata and new data sets, enable search and discovery of the data, and further empower data scientists to deploy said data for machine learning and AI.
If captured data is brought to a specific location to serve a single purpose but then fails to flow to other areas where it might provide value—coming to rest in a single location where it’s rarely accessed for other purposes—a data silo has formed. According to the Rethink Data report, enterprises report that one of the top five barriers to putting data to work is the difficulty of making siloed data available.
Data silos prevent companies from unearthing the full value of data at their disposal. Data goes unused or doesn’t get shared fast enough for distributed teams to analyze and make use of.
If you want the power to use your data your way, your organization needs to examine how disconnected its data is and implement storage and cloud infrastructure that easily transmits mass data where it needs to go at efficient speeds.
Here are five key areas data managers can focus on to prevent data silos from forming.
A single public cloud provider can give you integrated, end-to-end solutions for storage, network, computing, and applications. But it comes with natural limitations, including potential overspending on bundled services you don’t need, limits on how much data you can move and where, high costs to pull your data out, and interoperability issues with outside cloud services.
Instead, leverage multiple cloud service providers offering different services—such as storage as a service (STaaS), compute as a service, platform as a service, and software as a service—and design a multicloud that best suit your needs.
A composable cloud helps prevent data silos by enabling you to move and leverage your data to whatever location and service provides the most value. Companies that adopt a composable approach to infrastructure may outpace the competition by as much as 80%, according to Gartner.
As data capture grows exponentially, so does data’s value—but only if all potentially valuable data is available for analysis.
By incorporating STaaS as central to your multicloud, you can move or copy most or all your data into a data lake where it can be assessed using data analysis software based on your criteria. Data curators and scientists use these tools to mine information from the data to provide to decision makers.
Ingesting most or all data into a data lake eliminates silos and allows connections to be made from seemingly unrelated data elements.
Your data needs to be free to move as you see fit.
