Contact us
Our team would love to hear from you.
Back to blog
Business intelligence life cycle: from definition to full process description
Business intelligence (BI) is the key to unlocking potential and fueling business success. Guided by a comprehensive view of data from multiple sources consolidated in a single location, organizations can analyze past and present experiences to predict future conditions and make strategic decisions.
The exponential increase in data volumes has complicated the way information is stored, transferred, shared, and used. To successfully address challenges and capitalize on the value of data, decision-makers are adopting advanced business intelligence tools.
What is BI and how does it work? In this article, we will uncover the essence of business intelligence and explore its life cycle from beginning to end, providing a holistic view of how it works.
What is business intelligence?
Business intelligence involves processing and analyzing data, transforming it into knowledge that organizations can use to make informed decisions. BI uses a combination of analytics, strategy, and technology to help decision-makers develop plans and tactics to drive change and adapt to the market.
Business intelligence software offers invaluable advantages to companies by aiding in data organization, converting data into actionable insights, and predicting market dynamics and future trends based on discernable patterns.
BI tools help businesses improve their offerings, maximize productivity, and accelerate the analysis of information from different sources, thereby boosting data-driven approaches, economic growth, and profitability. To gain a better understanding of the process, let’s delve into the business intelligence workflow.
How does business intelligence work?
Simply put, BI takes information from different sources and transforms it into convenient and understandable analytics presented in user-friendly views (tables, charts, graphs, histograms, and more). BI uses two types of sources: internal and external.
Internal data refers to the enterprise’s information, which is typically stored in databases such as archives, ERPs, CRMs, device sensors, and other company-owned assets. While internal information is the backbone of an organization’s data system, it is not always sufficient.
When internal information does not provide a complete picture, internal data can be supplemented with information from external sources. External sources refers to publicly available data found outside the company’s infrastructure, such as social media, public statistics, research, government data, and more.
Data Visualization Services
Explore our expertiseBusiness intelligence life cycle
Business intelligence is multifaceted and only functions effectively when properly optimized. It is an ongoing process requiring constant evolution to provide relevant, accurate, and meaningful data. To illuminate the essence of BI, we outline below the steps of the BI life cycle.
Gathering requirements
Before deciding on tactics, it is essential to make a robust plan. Start from the finish line to determine what you need to accomplish. Examine business requirements, assess the biggest challenges, and define the purpose of the analysis. What is your priority? What data do you already have? Where is your data coming from? Can the data analysis be automated? How much time is needed to create the insights? This stage is for finding the answers to these questions.
Preparing data
Once the requirements are established, the next step is to design the logical model and physical schema to facilitate data analysis. Following that comes the construction of the data warehouse where the gathered information will be stored.
The data collected from different sources must be consolidated and made available to those who will use it for decision-making. To ensure the reliability of the data, it must be cleaned by removing duplicates and fixing bugs before it is loaded into the BI system.
A business intelligence software development company can help you collect, clean, and load your data, provide you with robust tools, and guide you through the next steps of the BI cycle.
Analyzing report
This is where the magic of BI happens. The data that has been aggregated and consolidated into a single place is converted into a visually appealing report that meets the requirements established in the first stage. Interactive dashboards allow stakeholders to communicate the narrative and drill down into market trends, customer experience, business performance, problems, statistics, and other factors, providing valuable insights to enable informed decisions on the organization’s development.
Taking action
This is where an idea becomes reality. In this stage, you can harness the power of BI systems by creating comprehensive reports covering all areas of interest to business leaders. Leveraging business intelligence software, decision-makers can measure and monitor key performance indicators to align strategy with business objectives.
Repeating the cycle
The last stage of the BI cycle is the iteration of the process. Evaluate the success of your decisions and make adjustments to improve the outcomes, obtain more valuable insights, and take more impactful actions. This could entail a complete reevaluation of the requirements, circling back to the first step and creating an iterative process.
Conclusion
By helping enterprises collect data from myriad sources, consolidate it in a single place, and visualize it in a convenient and consistent way, business intelligence plays a critical role in successful business development. Companies that leverage data to analyze the present and predict future conditions acquire new perspectives and have a competitive advantage over companies that have not yet implemented BI in their processes.
If you are looking for a BI development company, you are in the right place. Contact us today to put your BI plan into action! Our BI developers are ready to help you uncover the power of business intelligence for a better understanding of your organization and data-based decision-making.
Key takeaways
- Business intelligence consists of five key steps focused on setting business goals, collecting and analyzing data, and taking action based on insights derived from reports.
- The requirements set in the initial stage influence the outcomes of the subsequent actions.
- Effective business intelligence requires quality data from reliable sources.
- Business intelligence is an iterative process.
Blog
Related articles
Challenges in Power BI projects and how to deal with them
In today’s data-driven world, business intelligence tools have become go-to solutions for many organizations looking to leverage their data for strategic decision-making. However, having a BI tool is only the first step in that endeavor. The next is using it correctly to effectively gain insights.
Healthcare data management in clinics: challenges and solutions
The healthcare industry is generating an increasing amount of data from different sources and in various formats. Healthcare data management systems help medical organizations handle all this information, facilitating patient care and decision-making. However, healthcare clinics must be prepared for the challenges they may encounter when implementing these systems.
Big Data in financial services
Finance has always depended on data, but big data has transformed this reliance into a competitive advantage. By leveraging vast datasets and sophisticated analytical techniques, financial institutions can gain insights that drive success.
The ultimate guide to data transformation
Data is a valuable asset utilized by organizations to derive actionable insights, support informed decision-making, and develop far-reaching strategies. However, before businesses can harness the ever-expanding data streams, they must navigate the complex process of data transformation.
Data science in gaming: applications, benefits, and challenges
Over the past few decades, the gaming industry has witnessed disruptive transformations, developing from simple arcade video games to complex mobile gaming strategies. This progress, powered by evolving digital technologies, has resulted in a considerable surge in player numbers worldwide. As user bases are anticipated to continue expanding indefinitely, handling extensive amounts of player and gaming data is becoming increasingly challenging for organizations. Data science effectively allows companies to harness these ever-growing data flows and extract actionable insights.
Using predictive analytics in retail: benefits, examples, and best practices
A data-driven approach is the prime power of the modern retail market. Information and data analytics fuel every aspect of retail, from inventory management to pricing and marketing, and serve as a basis for predicting future trends. However, retailers have yet to unlock the full potential of forecasting outcomes with predictive analytics.
The power of cloud data warehousing
Your data doesn't wait for hardware upgrades to grow — it grows exponentially every day. An on-premises solution can't keep up for long. Moving to a cloud data warehouse that is infinitely scalable to meet your growing needs is the only way to reach new heights of scalability, flexibility and insight.
Importance of data quality in healthcare
From routine lab tests to proprietary formulations of the breakthrough medicines, high-quality data is essential for every aspect of modern healthcare. Implementing right data strategies is crucial for advancing care, improving patient outcomes and developing innovative treatments.
How to build an effective data lake for your business
How important is data for a business? The answer is - it is vital. From uncovering new opportunities to incorporating effective strategies, data is the driving force behind any thriving business. However, storing, processing, and analyzing large amounts of raw data from multiple sources can be challenging, even for experts in the field. This is when data lakes come into play.
Data party: warehouse vs. lake, battle of the giants
Data comes in all shapes and sizes. Discover how to organize your data flood using two contrasting styles: the strictly organized warehouse and the free-flowing data lake.
Data lake architecture, tools, and technologies
Data drives businesses, from building a strategy to making well-informed decisions. That’s why companies are continually improving the ways they work with data and trying to make the best of it. Still, it can be challenging to store and use all the enormous volumes of information. That’s what data lakes are made for.
Big data analytics in healthcare: a key to improving patient care and outcomes
Healthcare has already moved from a paternalistic and disease-centered approach to a value-based and patient-centered one. To meet the requirements of this newer model and deliver effective care, it is essential to embrace Big Data analytics tools.
Choosing the best BI tool for your business
Our principal BI developer Darya Drobova has shared ideas on how to choose the best Business Intelligence tools for your business.
Order an IT consultation
Fill out the form to receive a consultation and explore how we can assist you and your business.
What happens next?
- An expert contacts you shortly after having analyzed your business requirements.
- If required, we sign an NDA to ensure the highest privacy level.
- A Pre-Sales Manager submits a comprehensive project proposal. It may include estimates, timelines, lists of CVs, etc., for a particular situation.
- Now, we can launch the project.