What is Self-Service Analytics? The most reliable way to achieve data literacy
by Katy Yuan, Marketing Manager
What is self-service analytics? The most reliable way to achieve data literacy
by Katy Yuan, Marketing Manager
What is Self Service Analytics?
With nearly 2.5 quintillion data bytes generated per day, consuming data is both an opportunity and a source of frustration. Luckily, analytics can tame this data chaos.
As the name indicates, “self-service analytics” describes BI tools that enable users to interact, analyze, and explore data without the manual involvement of technical resources. The goal of self-service analytics tools is to generate actionable data-driven insights, while advanced solutions may incorporate technologies like artificial intelligence (AI) and machine learning (ML) algorithms to leverage automation and personalization.
Benefits of Using a Self-Service Analytics Tool
Greater Data Accessibility
Self-service analytics tools are a requirement for data literacy. Data democratization initiatives must provide a friendly interface for all users to consume insights easily, without requiring extensive training or technical knowledge. In order to successfully create a data literate workforce, users need tools that help them dive deep into data and generate deep insights that aid decisionmaking. Here, taking advantage of AI-powered analytics boosts the usability of data by augmenting decisions with personalized, timely insights.
Data Resource Optimization
By reducing dependency on IT, self-service analytics frees up valuable human resources, such as Data Scientists, to focus on larger projects that require manual effort. Their expertise can be put towards complex challenges such as revenue forecasting models, competitive intelligence, and predicting market trends. On the other hand, business users can quickly automate less complex activities, such as data visualization, exploration, and periodic reporting.
Greater Data Accuracy
Self-service analytics encourages a single source of truth as all consumers receive data from a centralized data source updated in real time. Today, ad hoc analysis is often done offline in Excel sheets or static reports, resulting in data siloes and outdated insights. Self-service instant insights break through the data siloes that may hamper accuracy.
In addition to basing business decisions on live data, self-service analytics further improves decisionmaking by expediting data access. Business users no longer have to wait for input from IT or data analysts, and can immediately tap into personalized insights to gather actionable recommendations. Organizations can now become insight-driven, instead of simply data-driven.
Advanced self-service analytics tools make businesses cost-efficient by saving manpower, streamlining access to data, and helping users make the right decisions at the right time. In addition, high user adoption means better scalability across the organization and faster time-to-insight for new employees. Many companies are also turning to modern cloud analytics for rapid onboarding and deployment across multiple business units.
Who Should Use a Self-Service Analytics Tool?
Through self-service analytics tools, organizations can now empower every business user to become an augmented consumer of data insights.
Users can interact with, discover, and consume insights on demand and at the point of decisionmaking. Thanks to artificial intelligence, insights are now more personalized and actionable than ever before, leading to optimized efficiency and costs for a data-literate organization.
Interested in looking for a self-service analytics solution to streamline your business? Talk to us!