7 Major Benefits of Self Service Analytics

Since the early 1990s, a series of new data analytics and business intelligence platforms came along promising the idea of self-service analytics. However, this vision has remained elusive for most companies. Most data analytics environments are characterized by high costs, long delays, and limited insights. Self-service analytics solves some of these challenges by offering end-users to converse with data directly without needing any specific technical knowledge. This can finally help companies create the DNA of “data-driven decision making”.

1. Prevents Existing Data Silos - Making Data consumable for All

In the previous paradigm, ad hoc reports and dashboards were created with the help of multiple data silos. Business users will have to rely on special skill developers to get their basic reports & dashboards. On the other hand, self-service analytics platforms connect to source data and alleviate the need for creating data silos. With the help of self-service analytics platforms, users can use the intelligent search functionality to ask questions in natural language and get instant answers/charts which can be pinned to their own dashboards.

2. Accurate insights without an in-house data scientist

Most modern self-service analytics platforms expand the scope of insights by offering advanced AI-powered insights automatically. For a normal business user, this is a great advantage as she does not have to hire in-hour data scientists for specific needs.

3. Data Democratisation across your Organisation

Self-service analytics platforms offer an intelligent search paradigm to users for easy data conversations. This helps organizations with the data democratisation process as business users can now explore data on their own. Data democratisation breaks the existing barriers of data access, enables business users to work with data and insights with no delays and creates a culture of data-driven decision making.

4. Data-Driven decision making - Uncover critical business Trends

While giving the end-users an ability to converse with data in an intelligent search interface, Self-service analytics platforms also expanded the paradigm of insights by offering deeper, AI-powered insights such anomalies, trends, seasonality, clusters, and root cause analysis. In the old days, insights used to be mostly about “what” happened in the past. With self-service analytics platforms, insights become accurate & actionable.

5. Self-service analytics tools reduce IT overhead

Most legacy tools required a large army of special skills developers to create reports and dashboards. Modern self-service analytics platforms require very little ongoing maintenance infrastructure. Companies that adopt self-service analytics platforms do not need to maintain an army of special skill developers. With a platform like MachEye, a small company or a SMB organisation can start with a starter plan and create self-service capability in minutes.

6. Get instantaneous answers for any queries

Self-service analytics platforms offer an intelligent search interface as the primary interface for data conversation. Search interface interprets English language questions and converts them into SQL in real time - this changes the paradigm as users can now get instantaneous answers to their english questions in real time.

7. Better Data Governance

Modern self-service analytics platforms use a data governance framework to control data access at table, column and data level. This is a key innovation in the world where it is very important to ensure that data security and governance rules are enforced with a user-friendly interface

A few common mistakes to avoid

Not all self-service analytics platforms are similar. NLP search based self-service analytics platforms are robust technology platforms which require sophisticated technology. It would be wise for business leaders to evaluate these platforms at a deeper level before making a purchase decision. While self-service analytics has rich benefits as articulated above, it is important to not confuse the end user by putting too many platforms in front of him. It is important to choose a platform that helps self-service analytics while extending and improving the paradigm of insights for business users. Finally, simplifying an end user interface and experience while delivering necessary and relevant insights should also be considered an important goal while choosing the self-service analytics platform.

MachEye is an innovative augmented analytics platform that offers intelligent search, AI-powered insights and root cause analysis in a simple, easy to use interface for every business user.

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