The rapid advancement of technology over time has propelled the evolution of Data Warehouses and has influenced how organizations plan and build their BI solutions.
Self-service business intelligence is aimed at empowering business users to discover data trends and make decisions by providing them controlled access to the data. As per Gartner, self-service business intelligence is defined as end users designing and deploying their own reports and analysis within an approved and supported architecture and tools portfolio.
The evolution of BI aided by newer analytical tools facilitating self-service has helped redraw the traditional crossover between IT and Business teams. A self-service business intelligence solution is designed with clear roles. For instance, the IT team would be responsible for building the service platform (tools and data) and the business users would analyze and consume data as per their reporting requirement.
Planning and Building the Self-service Platform
Organizations need to clearly define expectations from the self-service business Intelligence platform. The setup of the self-service platform requires close collaboration between the IT and Business teams. Once the platform is built, the business users take over and accomplish the majority of their analysis, discovery, and reporting using the analytical toolset integrated into the platform without having to depend on the IT teams.
Self-service business Intelligence is a vision of BI enablement and hence the journey starts with defining the BI requirements aligned with the business goals and objectives of an organization.
Identify the Users and their needs
One size does not fit all when it comes to defining self-service. Hence, it is imperative to identify the variety of users and their specific requirements. The user base can be broadly categorized as ‘Report Consumers’, ‘Functional Users’, and ‘Power Users’. The responsibilities of power users may vary based on organizational requirements and individual user capability.
- Report Consumers – Consume the batch or canned reports created by the BI developers
- Functional Users – Use the parameterized report template or interactive dashboards for their specific analysis and reporting requirement
- Power Users – Create reports, publish reports for internal and external consumers, trend analysis, data discovery, and advanced analytics. They are the business domain experts and collaborate with the IT teams to enhance and maintain the self-service platform.
Data Provisioning – Building the Data Lake
- Identify data sources in line with business requirement
- Define data model and storage layers (primarily raw, processed, sandbox and presentation)
- Define extract, transform and load strategy for each layer
- Data integrity via ETL checkpoints, business-driven quality checks, and database constraints
The users will have the following role-based functionalities enabled for them:
- Read-only access to Raw, Processed and Presentation layer
- Read-write access to the sandbox layer
- Sandbox Setup (categorization by Business vertical, Demography, Users)
- Sandbox layer supporting data manipulation and discovery
Power users will be able to copy data from any of the read-only layers based on defined access into their designated sandbox environment.
Selecting the Self-service Toolset
The organizational goal, BI strategy, and business user requirements will drive the selection of the toolset. Following parameters can help the tool evaluation aligned with business requirement:
- Support for data preparation
- Prompts for forming query
- Support for real-time analytics
- Support for predictive analytics
- Support for mobile versions
- Ability to build rich, intuitive dashboards
- Support for scheduling and distribution
- Social media analytics
Defining Success Criteria
Collaboration between the IT and Business teams is the key to building a robust and sustainable self-service Business Intelligence platform. Following factors will influence the ROI and success of the self-service platform:
Alignment and Adaptability
IT teams would be responsible for maintaining, aligning, and adapting the platform to variation in usage or querying patterns in collaboration with the business users.
Continuous assessment, evaluation, and adoption of newer analytical tools to facilitate advanced analytics (real-time, predictive). The framework should support easy integration and adoption of newer tools.
Minimal Handoffs between IT and Business Teams
Business users should be able to create their reports and run the majority of their analysis independently without having any dependency on the IT teams. This ensures experts in the business domain have the capability of running their own analysis, creating and generating their own reports. IT teams would be primarily involved in facilitating, maintaining, and enhancing the self-service platform.
Feature-Rich Toolset Support
The selection of the right toolset tuned to the business user requirement is a key to enhancing the self-service experience. The ability to analyze multi-dimensional data to create rich, interactive, and intuitive dashboards for executive consumption empowers the power users to be creative and innovative.
Provision for building and maintaining Adhoc custom utilities enhance the capability of the platform. In addition to building reports, the business users should have access to either use a pre-built utility or to create a custom process to pull data (external or from the Data lake) into their Sandbox for analysis. This action would be controlled via the data access roles and associated permissions.
Conclusion – Self-service is no More a Luxury but a necessity
More and more organizations are realizing the benefit and ROI associated with enabling a self-service business intelligence platform thereby empowering the business users (domain experts) to analyze, query, design, and share their reports. With clearly defined roles (between IT and Business), the benefits are quite evident and visible in the form of improved time to production, the overall cost of ownership, and goal-driven development aligned to the business strategy. Self-Service as a BI enablement practice has seen greater adoption, with business users becoming advocates for BI practices. The self-service requirements will change with time, user base, and changing business requirements, hence the key to sustaining an effective self-service capability would be continuous assessment, collaboration (IT and Business), and adoption of new technology trends/tools.
Dipayan Deb SR. PROJECT MANAGER
Specialized in enabling technology solutions, end to end Data warehouse implementation, migration of on premise Data warehouse to cloud based platforms and implementing Agile based onshore offshore delivery model