Companies collect data from multiple sources in order to gain insights about their customers. This data can be a powerful tool that can help businesses make data-driven decisions. To do this, the correct set of tools are necessary to make the process efficient. One type of software that caters to this is Self Service BI (Business Intelligence).
Self Service Business Intelligence helps synchronize the data obtained from multiple company departments and extract trends and relationships among variables. All company departments generate data, but at different rates. In most cases, the data analysis process is done by the IT or BI team. This means that data has to be shipped from the departments to the IT or BI team. After analysis, the departments must request reports from the IT or BI team. This introduces delays when it comes to making data-based decisions. The purpose of Self Service BI is to solve this problem by moving Data Analytics to the departments.
This article provides a comprehensive guide on Self Service Business Intelligence and explains its importance to any organization. It also compares Self Service BI with their traditional counterparts and provides their features, benefits, and limitations. Read along to discover all about Self Service Business Intelligence!
Table of Contents
Introduction to Self Service Business Intelligence
Self Service Business Intelligence or Self Service Analytics refers to the process of Data Analysis that is done by departments and non-technical staff in an organization rather than by IT or dedicated BI teams. This process can be done using simple BI tools and simplified interfaces which Business Professionals can manipulate with a lot of ease to execute queries and extract insights.
Initially, Business Analytics was seen as the task of IT teams. However, things have shifted and it has now been moved to the Business User. Today, most BI Software Vendors offer some kind of self-service reporting capabilities. This makes it easy for users to access data from different sources, extract insights from all sources, and make accurate business decisions.
This empowers organization teams like Sales, Product Developers, Finance, Operations, Marketing, and many more to answer data-related questions. Hence, Self Service Business Intelligence plays a significant role in creating a culture of using data in everyday operations in an organization.
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Comparison Between Self Service Business Intelligence & Business Intelligence
Traditional BI relies on IT and BI teams to perform data analysis processes in order to achieve business goals. Business Users such as Finance, Sales, and HR generate and store data and request the IT or BI teams to execute queries to generate performance reports, predict trends, etc. This gives the IT and BI teams more control over the quality of data, but it imposes bottlenecks and resource constraints that can delay the process of extracting insights from data.
On the other hand, Self Service Business Intelligence focuses on supporting the end-user, giving Business Analysts and users an opportunity to perform Data Analysis tasks. The IT team is allowed to focus on how data is ingested and governed in the organization. Data Analysts use their skills to dig deep into Data Modeling or Mining projects instead of answering Ad Hoc requests about reports. They give Business Users the ability to analyze their data quickly within the boundaries set up by data or IT teams.
Real BI is an iterative process. Business teams should be given an opportunity to extract insights from timely data. Deploying platforms is a great way of helping business teams to accomplish this.
Note that Self Service Business Intelligence doesn’t mean training every employee in the company to become a Data Analyst, neither does it mean taking away responsibility from the IT team. Instead, it means educating and encouraging business teams to interact and understand the data that they create throughout their work.
The figure given below distinguishes Self Service BI and Traditional BI.
Features of Self Service Business Intelligence Platforms
Not all BI software tools are made for Self Service Business Intelligence. A Self Service BI Platform tool should be easy to use by non-technical users. To know whether a particular BI software platform can be used for Self Service Business Intelligence, ask yourself the following questions:
- How easy is it to connect the platform to data? Does the platform come with this functionality built-in or should it be custom-developed?
- Does the platform require scripting to be done to prepare data for analysis?
- How much scripting is needed to prepare data for analysis? Is knowledge of SQL needed for this?
- Will your organization’s departments are self-sufficient, or must they rely on professional services from the vendor?
After getting answers to the above questions, you can know whether the BI platform will enhance Self Service Business Intelligence in your organization or not. You must choose a platform that will help you meet your company’s needs.
A good Self Service BI Platform must have the following features:
1) Ease in Fitting with the Data Architecture
Self Service Business Intelligence Platforms easily fit with the Data Architecture of your organization and synchronize all the processes smoothly.
2) Efficient Report & Dashboard Creation
Self Service BI Platforms must have efficient report and dashboard creation capabilities in order to handle multiple data sources and customers.
3) Easy Deployment
Self Service Business Intelligence Platforms are easily deployed on almost any computer system.
4) Estimate the Amount of Effort Needed
Self Service BI Platforms help users estimate the amount of effort required to perform Data Analysis and Visualization as well.
Although Self Service Business Intelligence can be challenging, most organizations have found huge benefits in teaching and encouraging business users to use data in their decision-making processes. The features of Self Service Business Intelligence Platforms are depicted in the figure below.
Benefits of Self Service Business Intelligence
Many companies have found a great return on investment from Self Service BI. Some of the benefits offered by them include:
- Fast speed when extracting insights from data.
- Reduced lag time since users can answer their questions from data.
- High-quality data reporting.
- Competitive advantage due to having timely insights.
- High data literacy in organizations.
Practical Self Service BI Tools
In this section, you will learn about the main features and elements of professional Self Service Business Intelligence tools that one should focus on to get the maximum out of the data.
- Drag and Drop Interface: Self Service BI tools with a user-friendly interface makes work a lot easier. It allows users to easily navigate around the tool and learn it quickly. The drag and drop interface help users easily select the data fields and variables from the table available in the data source. One can select the data to be analyzed and visualize it in different ways. It also makes it easier for users to create customizable dashboards and adjust the charts and reports on the dashboard according to their needs and convenience. The click and go interface helps users easily perform ad hoc analysis with the connected data sources and quickly share reports with other teams members, stakeholders, and managers.
- Data Connectors: Self Service BI solution supports many easy-to-go Integrations with 3rd party tools and services that companies use for daily business activities. BI tools support connections to Databases, CRM platforms, ERP systems, On-premise systems, Marketing tools, Finance platforms, etc. It provides flexibility and accessibility to the data existing in multiple data sources and allows users to easily get data and analyze it using an intuitive interface.
- Multiple Reporting Tools: To deliver high performance, flexibility, and power to analyze and visualize any kind of data in different formats, self Service Business Intelligence tools come with multiple Reporting options. It allows users to easily get an overview of data from multiple perspectives. One should use the right Rpoting tool based on the type of data to be analyzed. The Reporting tools are easily sharable via inks and users can view the reports in their dashboards with the help of shareable links.
- Pre-built Dashboards Templates: Managers, professionals, or individuals don’t have time to design full dashboards because they need to see quick results. Self Service BI tools come with many pre-designed dashboard layouts that one can use based on the type of data and use cases. These tools also offer Dashboard creator as a part of the software to customize the dashboards and come with many options where users can connect various data sources, set the refresh interval time, etc.
- AI-based Tools: Self Service BI tools powered with Artificial Intelligence boosts the overall performance of Data Analysis. AI-based tools help in gathering data faster than traditional methods and also provide access to more data. Self Service BI tools send automated alerts to users for any business anomaly in data detected or any goal is achieved. It ensures a hassle-free environment and uses Predictive Analytics to deliver deeper automated insights.
Limitations of Self Service Business Intelligence
Although Self Service Business Intelligence is a beneficial approach to data analysis in companies, it presents a number of challenges to adapt. Some of these include:
- It requires an investment in a new platform to be used by business teams for Data Analysis.
- Business Users must be trained on how to use the new platform for Data Analysis.
- Business Users may face challenges when there is a need to share data between departments or pull data from external sources.
This article provided a comprehensive guide on Self Service Business Intelligence and explained its importance to any organization. It also explained its features, benefits, and limitations and highlighted the difference between Self Service BI and Traditional BI. Overall, Self Service Business Intelligence is a unique way for companies to handle Data Analysis and maintain relationships within their departments simultaneously and it is a great asset for any organization.
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