Did you know that in 2020 the world will produce 50 times the amount of data that it did in 2011? With that in mind, it’s important to understand how today’s organizations need to integrate and derive insight from a growing number of multi-structured data sources in order to drive innovation. In this article we’ll show you how integrating a data discovery tool can help you create a smarter, more efficient data discovery process within your current workflow.

First, let’s answer the most fundamental of questions: what is a search based data discovery tool?

In short a search based discovery tool allows its users to cultivate and improve views and analyses of structured and unstructured data using search terms. Think of it like visualization-based data discovery tools, as they work in many of the same ways, only search based data discovery tools utilize text search in order to garner the needed information. Two of the current leaders in search based data discovery are Tableau and QlikTech.

Tableau is one of the leading data discovery tools, and a lot of that has to do with its accessibility. The product is both easy to use and to learn. It also links analysts to a myriad of data sources, both specific sources as well as in memory technology. You can build appealing and valuable that can be shared across the company via being published on the server.

Qlick is Tableau’s direct competitor and they also have a product that makse analytics truly intuitive for anyone in need of creating dashboards that help aggregate and visualize disparate data points.

Regardless of which discovery platform you choose to work with, both allow for the connections in your data to become visible, providing an opportunity to see patterns from every angle. They do this by concentrating on usability, manageability, transportability, enabled data discover, and pleasing visual aesthetics.

In this next section we’ll focus on four different ways of implementing these tools which can help your business realize its innovation goals.

Breaks Down Data Silos

A data silo is when only one department dominates a repository of fixed data—just like in farming when a grain silo is isolated. However, because silo data can only aid one specific group of analysts, discovery data tools give employees from all departments access to information across the business. By working with a discovery data tool you can allow cross department collaboration like: engineers the power to see sales data in order to understand what designs have been flourishing in the market, and what improvements need to be made.

Promotes an Analytic Culture

Everyone in your company should not only have access to data, but should also be able to analyze it in order to cultivate a deeper level of decision making. Getting data discovery tools not only creates an atmosphere of collaboration across departments, but moreover, creates an analytic culture, where all employees are looking to the data for answers. The value of an analytic culture is that it inspires users to understand the importance of data from other departments, and vice versa.

Helps Build Trust

Recent Aberdeen research labeled “trust as one of the three pillars of a successful big data strategy.” And using a data discovery tool, which enables a business to connect with a diverse volume of data, enables the user to trust the data they’re analyzing, as well as make a deeper analytic decision—rather than one made on instinct alone. Furthermore, when users make an informed decision they are 71% more likely to be satisfied with their ability to access higher volumes of data, which indicates that they also feel that their data was not prescribed to them. Furthermore, they won’t have to face calling for a solution that needs data which is not readily available.

Predicts Risk Implications

Aberdeen also states that nearly two thirds of organizations employing a data discovery tool are in finance, but that organizations across the board—from corporate management, sales, marketing and customer service— could benefit from implementing one. This is because a data discovery tool creates pipeline of information that can be assessed for future risk, creating a compelling vision of the risk implication of different situations.

Conclusion:

In the past you had to implement teams of analysts and data scientists together in order to interpret your data, but with a data discovery tool, you can simply talk to the software, and get answers. When the both the CEO and the sales manager feel they have the same skills to engage with data via a discovery tool, everyone in the company is empowered to work with the data, thus moving every business decision forward.