Agility in business intelligence is a continuous and repetitive process in which production does not take place all at once. Managers and leaders always need accurate and timely information from their organizations, which is what business intelligence meets.
Agile business intelligence enables rapid development using agile methodology. Agile methods are an important way to improve the development of business intelligence software such as dashboards, balanced scorecards, reports, and analytics software.
With the help of agile business intelligence, business intelligence teams and their managers will be able to make better business decisions and, as a result, take appropriate action faster.
The agile methodology is based on reproducibility (Dr. Gholamhossein equated misery with the word barest for iterative). This method is unlike the traditional cascade model where only the final product was presented; Allows new software features to be introduced to end-users sooner.
In the agile model, the requirements and design overlap with the development phase, so as the software development cycle is shorter, adaptive scheduling, gradual development and delivery, a fixed iteration approach, and speed and flexibility in the face of change are the hallmarks of this method.
Agile business intelligence encourages business users and IT professionals to think differently about their data through low change costs.
What is Agile Business Intelligence?
Agile Business Intelligence (BI) by emulating agile software development for business intelligence projects reduces the value creation time and effectiveness of business intelligence projects in the organization compared to traditional methodologies and helps the project to quickly adapt to changes in needs and localization.
The Forrester Research Center defines agile business intelligence as a convergent approach that combines processes, methodologies, tools, and technologies to improve adaptability and responsiveness to business changes and regulatory requirements in strategic, tactical, and operational decisions.
Research shows that organizations that make the most of business intelligence development are more likely to have processes that ensure business success. The success of agility in current intelligence depends heavily on end-user participation and ongoing collaboration between IT and business.
What are the key criteria for agile business intelligence?
The maturity framework of the overflow classification uses three key performance metrics to determine the effectiveness of business intelligence in each industry:
Timely availability of management information – Information technology should be able to provide accurate and timely information to business managers to make the right decisions. This measure of performance monitors the availability of information during periods when information should reach the user.
Average time required to add a column to an existing report – Sometimes new columns need to be added to an existing report to see the information needed. “If information is not available in time to support the decision, the information has no material value. This measure measures the total time required to change an existing report by adding a column.”
Average time required to create a new dashboard – This metric measures the time required to access any new or updated information and measures the total time elapsed required to create a new dashboard.
Five Steps to reach it
Agile business intelligence is made up of the following five steps:
Agile Development Methodology:
The need for agility, an iterative process that reduces the time to present the business intelligence needs of the market by shortening development cycles.
Agile project management methodology:
continuous planning and implementation. Planning is done at the beginning of each period, not like traditional projects once at the beginning of the project. In an agile project, the range can be changed at any time during the development phase.
The system must be capable of virtualization and horizontal scalability. This makes for flexible changes at the infrastructure level and can keep the Extraction, Conversion, Load (ETL) model up to date at the right time.
Cloud computing and agile business intelligence:
Many organizations are now using cloud computing technology because of the cheaper alternative to storing and transmitting data. Companies that use it in their infancy should consider cloud technology because cloud services can now support BI and ETL software in the cloud.
Organizational IT and Agile Business Intelligence:
To achieve agility and maximum effectiveness, not only the IT team must communicate with the business, but also pay attention to business problems and have a strong and integrated team.
Why use an agile business intelligence model?
It is used for a variety of reasons such as accurate data entry, data consolidation, and compatibility, data collection from various fields, accurate information preparation, timely information delivery, data analysis, and access to consistent information.
Statistics show that it usually takes 7 days for the data to reach the end-user (on time). In addition, it is not possible to cross-database the database in 70% of the company information (scope). 65% of the time, managers do not receive the information they need (appropriately). 60% of the time, users will not be able to get instant online analytics from them (analytics). 75% of key new sources of information on the web are not transmitted to users during the year (agility).
Overall, it is concluded that adding agility to existing business information minimizes problems. Organizations are slowly trying to turn the whole process of the organization into a methodology and agile development. Agile business intelligence will play a big role in a company’s success, as it emphasizes “integration with rapid development and innovation.”
Improve business intelligence agility
Several factors affect the success of business intelligence agility.
20% of the data is incorrect and about 50% is inconsistent, and this number increases with the new data type. Processes need to be re-examined and modified to minimize data entry errors.
Most companies have multiple stores and the information is spread across multiple stores. “Agility theory relies on the automatic discovery of each new data source and the automatic upgrade of new data repositories.”
One process is to gather a large number of data sources and display a summary report of them. Online analytical processing (OLAP) is a simple type of data collection tool that is commonly used.
One of the most important tasks of agile business intelligence is to send the right data to the right person at the right time. Historical data should also be preserved to compare current performance with the past.
One of the biggest benefits of agile business intelligence is improving its users’ decision-making. Agile business intelligence should focus on analytics tools that improve the operational process or new product development. An agile business intelligence approach will save the company money, time, and financial resources, otherwise, we will not have the savings to build a traditional data warehouse using the cascading method.
Agility checklist in business intelligence
A team of developers and business representatives must work together
Select your business stakeholders or technical partners to represent your business
Identify and prioritize appropriate user stories or requirements for referrals during an initial project
Evaluate the types of agile business intelligence tools that can be integrated with your existing data warehouse and business intelligence environment
Begin the iterative development process
Advantages of Agile Business Intelligence
Agile business intelligence leads its users to self-service business intelligence. Agile business intelligence offers organizations flexibility in terms of delivery, user acceptance, and return on investment.
Faster in delivery
Using the agile method, the product is delivered in a shorter development cycle with several repetitions. Each iteration is working software and can be deployed for production.
Increase user acceptance
In a sustainable development environment, information technology and business together (often in the same room) improve business needs with each iteration. “This increases user acceptance according to the typical needs of the non-technical professional user, leading to end-user interaction and increasing user acceptance rates.”
Increase return on investment
Organizations can achieve ROI due to shorter development cycles.