In the last article in our Anatomy of a Decision series, we explained the criticality of scalability and governance for analytics deployments.
A highly scalable analytics solution can ensure that both small and large teams of users enjoy immediate access to large volumes of data and can explore and analyze with high performance, to make impactful decisions. When end users employ self-service tools, strong controls must be in place to ensure that the data being used is both secure and suitable for employees based on their roles and authorizations.
In this article, we’ll examine the importance of ensuring that data are easily consumable by knowledge workers.
Big Data is complicated and just keeps getting bigger. According to IDC, the digital universe is doubling in size every two years—and the anticipated impact of the Internet of Things will only exacerbate the Big Data challenge. Spreadsheets no longer work to analyze the abundance of data that comes from so many sources.
Increasingly, adoption of visual, self-service analytics is on the rise because savvy organizations know the competitive importance of analytics. They aren’t going to let the size of data become an obstacle in their quest to drive a-driven culture. Easy-to-use data visualization tools make interpretation of data fast, easy, and intuitive for executives and front-line decision makers. As the saying goes, “a picture is worth a thousand words.” It is a lot easier to understand a graph than row upon row of numbers.
A visualization conveys more information in a much smaller space. Business users can quickly pull together data from a variety of sources, examine data through interactive charts, and intuitively see things that were not obvious to them before—patterns, trends, outliers. Even when data volumes are very large, patterns can be spotted quickly, providing a better understanding of sizable data sets. Through data visualization, outcomes of even the most complex analyses can be made easily accessible to executives and frontline decision makers, saving time and improving decision making.
Arming employees with visualization tools hides the complexity of Big Data and makes analytics more accessible to the every day knowledge worker. Deploying a self-service analytics solution with these capabilities enables users to make discoveries from data independently while strengthening organizational productivity through a data-driven enterprise that can quickly assess and act on data quickly and effectively.
Next Steps:
- To learn more about the factors that are driving self-service data discovery requirements, check out the Blue Hill Research study, “Anatomy of a Decision”.
- Try Spotfire and start discovering meaningful insights in your own data.
- Subscribe to our blog to stay up to date on the latest insights and trends in Big Data and Big Data analytics.
