10 Steps of Business Intelligence Implementation

Imagine you have put your data into any tool, and surprisingly you got the desired insights for your business. This is possible through Business Intelligence (BI). Most organizations are facing problems in the management of data to make active decisions and get accurate and actionable insights. Due to having a large amount of unstructured data, organizations got confused while choosing the right Business Intelligence tools. 

Gartner highlights the five critical capabilities of business intelligence and analytics platforms as data visualization, automated insights, product usability, data management, and data preparation.  

In this blog post we are going to learn about what Business intelligence is, its workflows, process, implementation of business intelligence and how Beyond Key will help you to maximum usage of BI: –

What is Business Intelligence?

Business Intelligence is the practice of turning the raw data into actionable insights for better decision-making. It helps in the growth of business by gaining knowledge of past insights. Business Intelligence tools are used to collect, analyze and convert data.                   

 Organizations can take improved decisions, identify the issues, and detect the market trends and can take advantage of upcoming business opportunities.  

According to Wisdom of Crowd’s report 2021 BI, 17% of organizations feel that embedded BI contained with a portal or application or integrated with other systems is critical for their businesses, and 43% of organizations think that embedded BI is important for their companies.

How does Business Intelligence application work?

Business Intelligence workflow process through different stages by collecting, extracting, analyzing, visualizing, and exploring the data.

  • Data Collection: It collects information from various sources like cloud, database etc.
  • Extraction: It transforms and cleans the raw data to ensure accuracy and consistency.
  • Analysis: It analyzes the data and looks for the trend and of results in data might use tools like data mining, data modeling.
  • Visualization: It indite visualization through graphs, dashboards through Tableau, Domo, MS power BI.
  • Exploration: Business analytics explores the obtained stats and strategies for further enhancement.

Steps of Business Intelligence Implementation

Business Intelligence implementation is made through multi-processes. It needs thorough construction to make the understanding of processes and results. A successful BI implementation relies on various essential steps. It starts with analyzing business needs and extending through the deployment and constant management of Business Intelligence solutions.

1. Defining a Goal: The first and foremost step of any business is to set how the BI implementation contributes to their business to achieve the goals, risks objectives and expectations. Mainly connecting with the stakeholders and heads can give you a clear definition of what we need to achieve. The first thing to do is to go through our current data structure, including:

  • Identifying Data sources
  • Reviewing reports
  • Uncover any existing data limitation or silos 

2. Gathering of Data: The next step is to collect data from various sources like cloud, databases, datasets etc. Collected data is integrated through ETL processes for clear results. Here BI consultant plays a significant role in planning and implementing through gathering and prioritizing the goals, objectives etc. by interviewing and collecting knowledge from the stakeholders.

3. Understanding of Business: Another step of Business intelligence implementation is to know the requirements of business, like what the business needs for growth, and what strategies should be followed to the rate and efficient results. It includes choosing the right tools and technologies such as functionality, scalability, user-friendliness, integration.

4. Key Performance Indicators: The next step of BI implementation is to set KPIs, which measure the performance indicators to track efficiency and monitor the progress. It helps to reduce risk, implement strategy, produce feasibility gives data quality reports which helps in attaining the objectives. It also delivers the backbone for data-driven decision-making.

5. Data Modeling: Modeling is the prototype of raw structure of our plan. It is another step that is vital, it lays the foundation for how data is stored, accessed, and structured. It designs local and physical models for organizing data. It develops logical and practical data designs and models for aligned and accurate data processes.

6. Dashboards and Visualizations: Dashboards and visualization is the next step of BI implementation to provide a user-friendly interface to monitor trends and KPIs. It develops interactive dashboards and visualization using BI tools such as Domo, tableau, etc. for real-time insights. Dashboards are easy to understand once you have the knowledge, visuals leave an impact in our brain and hence it is quick to understand and learn.

7. Validation and Testing: Before launching the BI system widely, it is tested on a small scale just to check if any bug is bothering or if everything is running well. Its easy to make changes at a lower level than at a large one. And if everything goes well then it is ready to launch.

8. Launching BI Solutions: The last step is to customize the BI solution by configuring tools, setting up storage, preparing data, automating ETL processes, optimizing performance building a dashboard, and integrating the system. The solution should be scalable to fulfil and meet the demand of your organization’s growth needs.

9. Monitoring and Improvement: After launching the system, it is time to monitor and track the performance, user interaction, and usage of data. Monitoring means it wants continuous improvement and advancements for more and more reach. Through monitoring, improvements and follow-ups are an ever-ongoing part.

10. Expand and Scale: To scale and expand your Business Intelligence services, you need to collect feedback from users to refine the reports, dashboards and workflows. It scales and updates the BI implementation solutions as business needs evolve.

Challenges of Business Intelligence

Apart from having multiple benefits of Business Intelligence, but there are still some challenges that need to be improved and will get better by time, though we are discussing them below:

  • Quality: The BI system needs high-quality data to deliver accurate insights, outdated data can give inaccurate and poor results which can lead to incorrect decision-making.
  • Data Integration: Business Intelligence needs integrated data, so it is collected from a variety of sources. Due to gathering of data in different structures and formats can be challenging while consolidating data into unified data.
  • Adoption: Even with an advanced BI platform, organizations may suffer to get employees to fully adopt and utilize the system.
  • Expertise: Talented and competent individuals, such as data experts, engineers, and analysts who can configure and manage the system, are needed for a successful implementation of business intelligence. These specialists are frequently hard to come by and expensive to employ, particularly for smaller businesses.
  •  Security: Sensitive data, including bank records, client information, and other private data, is stored in BI systems. For BI systems, security might provide certain challenges, particularly in large businesses with complicated user series.

Beyond Key’s Experts   

By using Beyond Key’s expert BI setup services, you may open growth and have a thorough understanding of business operations. Our customized BI solutions bring together data from several sources onto a single platform to allow data-driven insights. We offer exact tactics, from advanced data warehousing to integration and visualization, to get around challenges and accomplish organizational goals. To transform data into strategic insights that might affect decisions, we can work together to update and enhance your business intelligence (BI) systems.