Role of Datasets in self-service analytics


Many industries consider data as a very important asset of businesses. This is because, the data are used to identify trends, patterns, and preferences to maintain a high competence level as well as to offer a better customer experience.

Data are important because certain users find difficulty in finding data to perform desired analytics.

Today, Real-time data, KPIs, and performance metrics are way more important to a business.

Analytics plays a vital role in business decision making in organizations. Certain data-driven organizations use Business Intelligence (BI) or self-service analytics, which helps non-technical background users such as executives or marketing staff to gather data, generates reports and outputs which would help them to make effective business decisions. While in organizations with traditional analytics, users are required to raise a request to a data professional to perform the above tasks. This process would take more than a couple of days.

Therefore, a self-driven analysis tool can perform the process automatically and users can explore the data and share visualizations while maintaining all kinds of security protocols to protect sensitive information.

Self-service analytics (SSA) tools such as Tableau and Qlik helps both the analysts and non-technical users to gain insights and to be data-driven. These SSA tools and BI enables users to gather information without the help of IT or reports. However, using analytical tools alone will not add value to the business. Organizations should make sure the users can access all the data that are spread over the computers and must have data integrity for better results. While collecting disparate data from different systems, tools must be able to understand and recognize similar data, relationship with the data, and the organization’s data map.

Data has to be cataloged properly so that self-service tools could yield desired results. This data catalog incorporated with machine learning gives greater insights and provides recommendations based upon the previous user behavior or purchase pattern like Amazon. This catalog makes the work easier and quicker for users to yield data for decision-making.

Today many organizations have started to adopt self-service tools for BI to improve the analytical capabilities for better business growth through better decision-making and customer engagement.


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