According to a recent Gartner survey, 49% of respondents view self-service data and analytics as a driver of employee productivity. In addition, at least one in four respondents see the technology as fueling greater organizational speed and agility.
These capabilities will be increasingly important to organizations as they look to combat inflation, slower growth, and increased pressure on profitability. Gartner believes that companies that invest in analytics and other digital technologies will be more likely to successfully weather these challenges compared to counterparts who simply pass the cost increase on to customers.
As companies look to empower more employees to make data-driven decisions, many must adjust their technology environments. One action is ensuring that a data catalog exists to document key data and provide it with the right context. Generally speaking, these data catalogs serve as hubs for data sets and related assets like reports, dashboards and models, making it easier both for data stewards to set parameters and ensure the privacy and security of the company’s information and for users to search for relevant data.
The Culture Imperative
Investing in the right tools and technologies is certainly part of prioritizing self-service analytics.
Equally critical, however, is establishing a culture that strikes the necessary balance between supporting self-service data access and also providing assistance as needed.
If employees are left to educate themselves on data practices, the self-service initiative will surely suffer. By contrast, when employers take the time to train staff they are paid in dividends. For example, Forrester found that over 90% of employees were satisfied in their roles if their companies were investing in data literacy training.
A decentralized analytics model is another consideration for enabling successful self-service analytics. In this approach, the data itself is centralized so that it can be managed by data stewards who will ensure its quality and integrity. Decentralizing all analytics components, including the query, analysis, and deriving of insights, is essential so that knowledge workers don’t have to wait for data teams to develop the reports, dashboards, and models they need to make more data-driven decisions.
Head over to TechTarget for more on these and other self-service considerations, and how they can give you the competitive advantage necessary for thriving in today’s volatile environment.