The current business ecosystem is continuously evolving in the digital world. The global economic scenario enables business opportunities as well as challenges. The factors affecting the business ecosystem are ever-changing customer needs, globalization, etc.
Business owners often face difficulty in making business decisions due to unorganized data and a lack of business insights. The way data is organized & stored can affect the way how business decisions are made. With proper data storage and management, business owners can utilize reliable data for better decision-making. Business intelligence architecture is a data management framework frequently utilized by organizations for this purpose. Let us give you an in-depth look into understanding business intelligence architecture, as well as why developing businesses need it.
Overview: Business Intelligence Architecture
Business intelligence is defined as strategies and technologies used by organizations to analyze & manage data. In relation, the architecture is composed of data, technology, processes, people, and the management utilized in business intelligence systems. The sustainable architecture comprises of three major components that include
Data Collection Streams: This component includes different ways of collecting data within an organization. Sustainable architecture helps recognize the origin of data and which data is important for each company department. This holds significance because the data quality is how reliable insights are generated.
Data Management: The second component defines data integration and how it is maintained within the business intelligence architecture. Sustainable architecture has the capability to manage multiple data sources. Business users should be able to quickly extrapolate data so they can make meaningful insights.
Business Intelligence: Owners and department managers utilize data to measure key performance indicators (KPIs) and other trends within the organization. This feature allows decision-makers to better optimize choices based on business insights.
Why Do We Need Business Intelligence Architecture?
A business intelligence architecture articulates data and analytics practices that support BI efforts and tools deployed in the process. It serves as a technology roadmap to collect, organize, and manage BI data efficiently. Further, the data is made available for analysis, data visualization, and reporting. A strong BI architecture includes policies to govern technology use. We’ve listed below a set of reasons why organizations need business intelligence architecture.
Backlogs: A well-organized BI system enables self-service capabilities to help users resolve any issues on their own, so it doesn’t get overwhelming for the IT department to fix each task at hand.
Poor IT Systems: It becomes difficult to fulfill report requests because of complex IT systems including data silos. With the right BI architecture in place, users can overcome this issue by consolidating the data into a uniformly formatted system.
Price: It can get costly maintaining all the critical IT resources for various data silos, information systems, etc. When each department has different ways to manage, there can be a lack of efficiency in completing assigned tasks. Contrasting systems can increase the workload for each department to handle. This can lead to increased management resources and waste valuable resources.
Components of Business Intelligence Architecture
BI architecture consists of various key components to make it functional. Some of the components include:
Operational System: Data should be first organized within an operating system so that it can be utilized to process day-to-day transactions within the organization. While the majority of data generate from operational/source systems, some generate from different sources. If the true essence of data is not captured in the operational/source system, it cannot be analyzed further.
ETL Process: Once the data has been organized within the operational system, it is extracted and put into the data warehouse. This processing mechanism is referred to as Extract Transform Load (ETL). SQL Server Integration Service, IBM Websphere DataStage, Oracle Data Integrator, etc. are some of the ETL technologies.
Data Modeling: Data Modeling is a process of extracting data from data sources, choosing its format, and managing its relation to other data within the source system. Extracting all of the data from an operational system can be expensive because data has to be saved in case the backup system fails. Data modeling extracts genuine data and organizes it to minimize the cost of data replication and storage.
Enterprise Information Management: Enterprise Information Management (EIM) includes different data management tools that include data profiling, metadata management, gathering statistics on data within the data source, data modeling, etc.
Business Intelligence Hardware: It is important for companies to make meaningful business decisions pertaining to BI hardware. Reliable data warehouse appliances collate databases, servers, secure systems, etc. Users should research the performance capability of different systems before making any business decision.
How Can I Use Business Intelligence Architecture?
Before utilizing business intelligence architecture, organizations should consider mapping out their data and analytics strategies. Some strategies include what the data sources are, the type of operating system being utilized, and the codified data to expect from each department.
Analyzing data provides a framework for users to understand how employees are contributing to the sales goals of the organization.
BI architecture should encompass data sources and components to enable reliable and appropriate sales data analysis. After the data sources are selected, it can be determined which data is more valuable and how to store it in a secure way. High-performing and advanced data analytics tools allow organizations to easily understand data to better optimize business decisions and capture real value.
The demand for business intelligence architecture is growing. To learn how leading organizations are reducing costs and boosting sales, contact us today and learn the best BI practices from Polestar experts.