Data. We now have lots of it. Everywhere. Historically, before we tried to do too much to manage any of it, we first moved data to a central location (e.g., the staging area for an enterprise data warehouse). This blog post touches on the top five benefits of managing data where it is (e.g., in-cloud, in-database, in-memory, in-stream).
Minimize data movement
In addition to staging it for data management processes, another common reason for moving data is to make a local copy of it. The proliferation of those copies is the data silo challenge most organizations are mired in. However, most of what are referred to as data silos are actually application silos because data and applications became tightly coupled as applications were built around where the data was moved to and manipulated (i.e., cleansed, transformed, unduplicated and structured). Storing data in one easily accessible location (e.g., in the cloud or in Hadoop) and, instead of moving it, building services around your data, is a best practice more and more organizations are moving toward.
When data doesn’t have to be moved before it can be managed, it frees up valuable resources, such as IT personnel who can be more productive when freed from iterative data provisioning tasks. When data continues to be available at the same place users are accustomed to accessing it, improved data not only becomes more accessible to business users – this practice also limits the downtime associated with training people how to use new applications and interfaces.
Reuse data management techniques
It is far easier to reuse data management techniques (e.g., data quality rules) when data movement is minimized. One reason is that when data is moved, you risk leaving data management techniques – and associated metadata – behind. By creating data management techniques once and reusing them, you give the enterprise a standard, repeatable method for managing data. When combined with limited data movement, this benefit becomes exponentially more powerful, allowing you to continually improve your data with minimal incremental costs.
Improve data governance
A fundamental issue with moving data to another location to perform data management tasks is the disconnect it creates between sourced data and managed data. And since governance and management go hand in hand, it also creates a disconnect between sourced data and governed data. In the era of big data, these disconnects quickly multiply. Governing big data isn’t easy. But when data stays put, minimizing the number of places where data must be managed and governed, it becomes easier to employ data governance policies, procedures and processes. Key data governance issues like establishing and sustaining the right level of data quality, privacy and security are often a necessary disruption to daily business activities. Data governance becomes less disruptive when it’s a grass roots movement happening because data moves less often.
Share valuable skills
Skills silos are almost as common as data silos. Some in-demand skills, such as data stewardship, are not as available throughout the organization as they should be. Part of the reason is that good data stewards are hoarded like high-value data. Being a data steward is scary. It’s definitely a tough role to play. It’s even tougher, however, when data stewards have too many data stores to steward. Limited data movement expands the availability of data stewards, allowing them to share their valuable skills across the enterprise.
What say you?
What additional benefits have you experienced by managing your enterprise’s data where it is? Please share your perspective by posting a comment below.Read an article: How data stewards score with data visualization