Let's discuss the various possible users of the data discovery tool and their advantages. Here's a small schema of possible data flows in an organization:
There are many systems which generate data. Organizations try to catch all the data and put it in data warehouse. In addition, for big data volumes they can use Hadoop because it offers cheap storage, high scalability, distributed computing power, and can be used as a staging area for raw data.
On top of the DWH we have a business intelligence tool, such as SAP BusinessObjects, MicroStrategy, Oracle BI, or Cognos BI. This uses data from the DWH and gives the opportunity to build reports and visualize data. But it takes long a time to create the semantic layer via a BI tool such as the universe, schema or repository. In addition, it requires technical skills. As a result, there is no agility and it is not user friendly for any non technical business users.
Fortunately, we have a data discovery tool which can easily complement our existing BI tool. Let's look and compare how a data discovery tool can impact on our data flow in an organization:
Data discovery tools have many advantages for the whole organization. It can be easy to connect with various data sources, and it doesn't require any technical skills from the business users. Users can combine and merge various data sources and visualize big data sets. They can easily find insights from data and use it for their decision making process.
In addition, let's now look at the benefits of using a data discovery tool for various roles in the organization:
Business management: It provides better information for the decision process, plus greater accuracy, richer detail, an enhanced ability to identify factors affecting business outcomes, and the connections among them.
IT managers: It eliminates the stream of individual support requests for analytics. It will free IT staff for other responsibilities and improves internal customer satisfaction.
IT staff: It allows them to dispense with the oodles of requests for data extracts.
Distinguished analysts: It gives greater productivity, fewer errors, and more time to spend on the more interesting aspects of data analysis. It allows better and easier data access, better integration among data sources, and the opportunity to probe data in greater detail. It provides a roader range of analytical methods.
Other data analysis roles: It provides access to a greater variety and depth of data, and to analysis methods.
Everybody else: It provides better information to support daily decision making at all levels of the organization.
We can continue this list with other roles in your organization and try to determine, what benefits they will get.
