What is Self-Service Analytics?
Earlier, data and reports were restricted by the number of users and the high cost of analytics tools. So, the companies were mindful of providing access to data and reports. However, organizations are now willing to offer democratized access to domain experts as they want to increase operational efficiencies and need faster access to informed insights for decision-making. Thus, subject matter experts are encouraged to ask a query and perform self-service analytics to discover trends, patterns of activity, and actions associated with each event.
Self-Service Analytics is a type of business intelligence (BI) where all the business users are empowered to run their queries and produce reports with minimal IT support. Self-service analytics is characterized by easy-to-use BI tools and a foundational data model, simplified for a clear understanding of business data.
Challenges in Implementing Self-Service Analytics
Implementing self-service analytics and giving BI ownership to more employees inside the organization comes with its own set of challenges, such as:
Low-level Data Literacy
Self-service BI users must be data literate to comprehend and interpret the data and make informed decisions for your organization. Data literacy issues or a lack of data comprehension negatively affect a company. To make informed business decisions, every employee with access to data should be knowledgeable about the data in their specific domain.
No Data Governance
Data democracy does reduce/limit IT team’s responsibility for data security. But an organization may get exposed to inconsistent data risks if it lacks strong governance frameworks. No matter how much a company wants to give all employees equal access to data, self-service analytics must be implemented with controls that govern the data’s ethical and trusted use.
Benefits of Self-Service Analytics
Reduce Dependency on IT
Self-service analytics gives all business users access to data without dependency on IT personnel. Business users can now independently handle less complex tasks like data exploration, visualization, and reporting.
Empower Business Users
Instead of limiting access to only IT users, self-service BI tools let business users run their queries as needed. Self-service analytics tools enable business users without technical expertise to easily create the reports they need to address business challenges, saving time and money compared to hiring additional IT staff.
Single Source of Truth
All users can access the same version of data with self-service analytics. Self-service analytics ensures consistent data across departments, enabling better collaboration and increased productivity for any file across multiple devices.
Self-service analytics, if implemented appropriately, can do wonders for a business. Business users can get insights that facilitate collaboration, streamline operational procedures, and raise customer satisfaction. Therefore, it is essential to choose the right tools as per business requirements and train the employees well in advance to handle and run analytics independently.
Best Practices to Follow for Self-Service Analytics
Easy data Accessibility
While performing self-service analytics, users must have access to enterprise-wide data, including historical and new data. This will ensure that the business insights generated are accurate and complete.
User Interface
Providing a user-friendly interface is important for the extensive use of self-service analytics. Users should be able to easily navigate through the application and customize their experience as needed.
Collaboration
Wider circulation of self-service reports becomes crucial when multiple users are trying to access insights. When users are empowered to share information, the decision-making process becomes seamless.
Data Governance
A data governance layer supports the entire data architecture of the organization. Data quality controls and standardization protocols are essential for self-service analytics to be implemented successfully. Security and data breach concerns are the topmost priorities for all enterprises and need to be addressed for efficient self-service analytics.
Artificial Intelligence for Analytics
Artificial Intelligence tools enable comprehensive use of data and quicker creation of insights. Self-service analytics can benefit from artificial intelligence capabilities to help users increase the usage of data for decision-making and remove dependence on IT professionals.
