Self-service business intelligence empowers different teams, including product, marketing, sales, finance, operations and more, to answer data questions without relying on IT teams for ad hoc reporting requests. Self-service BI tools help users gain valuable data insights to make robust decisions and attain business objectives within a stipulated time. Instead of using gut instincts and premonitions, BI tools rely on data to generate interpretations, make forecasts and create a data-driven culture.
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This Guide Covers:
- What is Self-Service Business Intelligence?
- What Makes a Platform Self-Service?
- Benefits
- Challenges
- Features
- Factors to Consider while Selecting Self-Service BI Tool
What is Self-service Business Intelligence?
Self-service business intelligence is an approach to BI that empowers users to access, explore and analyze vast amounts of data without technical expertise in data mining, statistical analysis or related fields.
Self-service BI tools help users connect, filter, sort, explore and visualize datasets without assistance from IT teams. With such apparent value, it’s no surprise that the self-service BI market is expected to reach $14.19 billion by 2026.
Organizations implement self-service BI capabilities to give the frontline workforce straightforward control over the organization’s data and derive valuable insights from it. It ensures informed decision making that supports positive business outcomes like increased efficiency, seamless customer experience and improved revenue.
Differences Between BI and Self-service BI
Traditional BI relies on IT departments to formulate data analytics processes to achieve business objectives. Business users from sales, finance, HR and other departments store their data and request analysts to query it and generate performance reports, forecast trends and more. This process gave IT teams complete control over data quality but hampered their speed.
However, self-service business intelligence gives users end-to-end control over the data analysis processes, from data ingestion and transformation to creating intuitive visualizations. The data teams still take part in the process and focus on how business information is ingested and governed. Analysts can leverage their data mining expertise and project modeling skills rather than catering to ad hoc reporting requests.
What Makes a Platform Self-service?
A BI platform can be considered a self-service tool if it meets the following conditions:
Data Sources
Users should be able to connect to different data sources seamlessly, and they need to be accessible from anywhere, on any device. Supported data sources should include contextual data, not just traditional data models. The solution becomes more resourceful if it provides data source metadata.
Data Preparation
While preparing data for analysis, it is important to identify and remove outliers, treat missing values, change data types, join tables and more. Users need to consider how much scripting they need to prepare the data for analysis and if they need advanced SQL knowledge to do so.
A self-service BI solution should facilitate quick transformations to save time and ensure faster analysis.
Interaction with Reports
Users need the ability to create, modify, manipulate and implement business logic to reports using advanced capabilities with ease. Filter reports to derive insights and make the right decisions.
User Interface
Successful platforms possess an intuitive interface for data exploration and visualization. Their desktop application should also support data sharing and collaboration, along with a mobile application that provides a responsive touch interface to create and share reports and dashboards.
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Primary Benefits
Let’s look at the benefits of self-service BI tools:
Single Version of Truth
Self-service BI offers a consistent and updated version of data to all decision-makers. As opposed to spreadsheets, it provides consistent data flow. It pulls data across different systems, including ERP, HRMS and CRM, into a centralized location.
Perform data transformations, develop robust models and create intuitive visualizations to derive insights that impact business outcomes, eliminate waste and improve products and processes. BI tools eliminate the need for disparate data silos and foster consistency and transparency to ensure user productivity.
Reduced Dependency on IT
With self-service capabilities, users can create reports based on ad hoc requests. This accessibility frees up IT teams to create reports, dashboards and visualizations. It also allows them to focus on tasks that require technical expertise, such as curating data sets and creating complex queries.
Cut Costs
As BI adoption rates increase, self-service platforms can scale with ease and accommodate additional servers without causing access issues. A major value addition that self-service BI tools provide is eliminating the need to invest in data warehouses and related infrastructure and licensing costs.
Fosters Decision-making
Self-service BI lets frontline users take charge of their data and conduct robust analyses to make data-driven decisions. This control accelerates business processes and offers opportunities to drive business growth.
Notable Challenges
The challenges of adopting a BI solution are as follows:
Resistance To Change
Executives and managers who want to base their decisions on their knowledge and intuition resist BI adoption. BI tools that lack an intuitive interface discourage user adoption too.
Inaccurate Results
Self-service analytics can produce inaccurate results due to incomplete or erroneous datasets. Users may work with the different versions of the same dataset, producing flawed output. These issues can ultimately lead to chaos over BI findings and faulty decisions.
Data Security
Self-service BI could create data access and sharing problems if robust security and data governance policies aren’t in place. Unauthorized users can access sensitive data and violate data privacy rules and regulations without proper security measures.
Key Features
Let’s look at some self-service BI features:
Drag-and-Drop Interface
Leverage an intuitive drag-and-drop interface to navigate around the tool. It allows users to directly select variables and data fields from source tables.
Connect data from different sources, join tables using append and merge queries, perform table transformations and develop intuitive visualizations, dashboards and reports. It facilitates ad hoc analysis and report sharing with other team members and stakeholders.
Data Connectors
Self-service BI tools support integration with third-party systems. Data connectors facilitate connections to databases, CRM and ERP, on-premise systems, finance and marketing automation tools, and more. They offer the flexibility to access data from multiple sources to perform advanced analysis and extract useful insights.
Interactive Reports
Convert data into knowledge through interactive reports, and get a data overview from multiple perspectives. Slice and dice and drill up and down through data to gauge trends and patterns. Apply techniques such as moving averages and regression analysis to highlight trends. Perform time series analysis to identify fluctuations in datasets with respect to time.
Personalized Dashboards
Visualize, monitor and understand real-time data with personalized dashboards. Deliver metrics, KPIs and summary information to executives to make faster decisions. Leverage exception reporting to alert users to unexpected events that need quick action.
Location Intelligence
Map and visualize data in a geographical format. Explore and visualize datasets based on spatial elements to enable the organization to gauge their business operations from a new perspective, such as sales per region, customer base in specific areas and more.
Needs Analysis
All BI tools have three main functions: gathering data, analyzing and visualizing it. Let’s look at some factors to consider while selecting a self-service BI tool.
Quick Implementation
Ensure all data sources, including databases and data warehouses, are easy to connect to the BI platform using direct connections. If it doesn’t possess a direct connection, the IT team has to create a custom connection to facilitate integration.
A successful solution should take less time to go from purchasing a license to creating the first dashboard.
Ease of Use
A self-service BI platform is intuitive to use for technical and non-technical users if:
- It is straightforward to connect to new data sources without assistance from IT teams.
- It is possible to query data with no SQL knowledge. Visual SQL builders allow users to create queries with a visual interface.
- It is possible to create visualizations and dashboards in a few clicks.
Dashboards
Choose from numerous graphical tools, including charts, graphs and maps, to create robust dashboards. Facilitate dashboard collaboration with team members and stakeholders to make data-driven decisions.
Affordability
Ensure the vendor offers flexible pricing plans to make the platform affordable for small and medium businesses. Requirements change as the organization grows, so it is best to avoid long-term contracts.
Scalability
Scalability that matches growing data requirements is key. The ability to create custom tables and schemas provides data flexibility to adapt to dynamic demands.
Conclusion
Although self-service business intelligence can be challenging to adopt, organizations are finding immense benefits in embracing a data-driven culture. Choosing a BI solution that fits into the existing data architecture, implementing training programs and developing a self-service BI strategy can lead to quick adoption.
How does self-service business intelligence benefit your organization? Please let us know in the comments below.
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