Three Ways to Help Everyone Make Fast, Data-Driven Decisions with Modern BI
4 min read
fairly difficult
Innovative—yet approachable—data analytics is developing at the speed of light…and how your employees comfortably interact with that data is just as important as understanding its worth.
This is the second post in a three-part series about transformational modern analytics. In case you missed it, read the first post to learn how governance and data management enable your digital business.

In our age of digital transformation, we are witnessing the transformational power of data to inform business decisions and drive change in real time. Tapping into organizational data can help your teams shape connected customer experiences, surface system constraints and improve operations, and align business leadership on shared metrics.

However, many organizations still struggle to increase the number of people using data in their daily routines and workflows. There are plenty of barriers between employees who rely on data and the sophisticated analysis required to make the best decisions.

Fortunately, evolving modern analytics platforms can help everyone make informed decisions with trusted data quickly and confidently, from power users to everyday front-line employees.

Let's explore this evolution, which is happening through a convergence of three paradigms:

1) Data democratization

2) User interfaces that equip people of all skill levels to obtain faster insights

3) Artificial intelligence (AI) applications that make advanced analysis approachable

Democratize data to empower organizational agility

With millions in capex spent to capture, curate, clean, and store data, it's surprising that many organizations are not also democratizing it. If you can get data into the hands of those who intrinsically know your business, rather than restrict access, that's when the magic happens.

IT is often a gatekeeper and bottleneck to how businesspeople get insights. A dashboard or report may help answer some questions, but what happens if teams have follow-up questions? Do they go back to IT and wait in a queue of requests? Or do they export data to spreadsheets, sacrificing data governance? What's the typical scenario at your business?

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