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Let's Distinguish "Data Warehouse" from "Talent Data as a Service"

May 22, 2019

Undeniably, ours is an era focused on "data." And the information revolution shows not signs of slowing down. As data technology spreads, so do terms to distinguish the collection and use of data.

For example, a "data warehouse" is a massive collection of business data available to aid decision making. Such data is gathered from many different sources such as an organization's marketing, sales, and customer-tracking systems and, externally, from partner organization systems.When a data warehouse pulls such data, it applies formatting and import processes so incoming data matches data already in the warehouse. In that way, the data is stored ready for decision makers to access. Some benefits are that warehoused data tends to be consistent and relevant, which aids decision making.  However, it also needs a unique identifier and the process of "extract, transform and load" can mean getting new data to it can face long delays and high costs.  Finally, the data in a warehouse will primarily be structured, and will usually be force to a single data dictionary, so data that only exists on a few people doesn't fit the model.

A data lake store masses of data in a much less processed form. 

Of concern to human resources teams, including recruiters, is talent data—the totality of information an organization has on internal and external talent, including data analyzed to produce insights. All such data must be collected from the organization's talent management system (TMS), which includes, of course, not only recruiting, but  phases such as onboarding, performance evaluation, and compensation.

Talent Data as a Service (such as the SwoopTalent data platform) are used to collect, integrate, curate, and "serve" your organization's data to wherever it is needed.  Talent DaaS combines the integration of your software with collating your data, all automatically.  That means migrations are easier, data is not lost, and data is curated for maximum possible value.   The quality of such a system is judged in part by the clarity and relevance of the data-based information it provides everyone in your organization concerned with recruitment, and partly in how quickly and clearly it gets data into the right hands.

The result is improvement of employee engagement and productivity because better data makes possible better, faster workforce decisions.

A final relevant term heard today with increasing frequency is "big data." In a sense, the term is self-explanatory. The information revolution has meant massive and exponentially increasing volumes of employee, customer, and transactional data in many organizations. Typical data handled by a strong talent management system might include skills, performance ratings, age, tenure, safety record, sales performance, educational background, supervisor, and so forth. In some cases, this goes beyond internal metrics to encompass social media data, government data, and external benchmarking systems.

All of it is intended to enable HR teams to make smarter and more accurate decisions, to better measure efficiencies, and to identify potential bottlenecks that impact workforce productivity, training programs, and attrition—to name but a few.  The use cases are wide and varied.  Why not contact us to brainstorm the challenges Talent Data as a Service might solve for you?

Photo by Elli O. on Unsplash

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