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Business Intelligence – Architecture, Components, and its Benefits 

 February 15, 2023

 

From collecting, storing, and analyzing corporate data to data mining and visualization – business intelligence tools provide enterprise-wide assistance to make more data-driven decisions. Are you still doubting about implementing a business intelligence tool?

Among others, the most critical components for companies remain data collection, storage, and analysis to secure smooth operations workflow and high-level performance. With plenty of emerging technologies and tools, a business intelligence architecture is the icing on the cake by boosting the company’s efficiency while collecting and analyzing data. Admit it, the ever-changing business environment provides numerous opportunities and challenges at the same time. The key factors striking businesses are customer needs, globalization, and local government policies. While almost all companies have digitalized business support, it appears in the form of a decision support system, business analysis, etc. Diving deep into business intelligence and its architecture will clarify how to implement this framework within your company. Today, we will discuss the business intelligence architecture and components, as well as explore its benefits for the business.

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Business Intelligence

Business intelligence is a specific framework intended to facilitate the decision-making process. It is a mix of architecture, databases, analytical tools, and apps. In other words, it is a data-driven decision support system or DSS that informs about a company’s strategic and tactical business decisions.

As a rule, it offers the past, current, and predictive perspectives of business operations by leveraging data gathered into a data warehouse. After analyzing big datasets, Business Intelligence tools bring analytical findings in several forms, such as reports, charts, dashboards, maps, or graphs, to provide detailed intelligence about the state of the business. What’s more surprising, it puts forward a gateway for users to research data, understand current trends, and make informed decisions by optimizing their efforts.

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For example, Business Intelligence tools can be deployed to check big data sets, such as student attendance reporting or performance monitoring. As for the business,  Business Intelligence tools are widely employed to coordinate and manage the supply chain, identifying delays and fluctuations within the shipping process.

Architecture

Since efficient business intelligence tool depends upon a sustainable architecture, the process of creating a BI architecture is split up into several areas:

–    Data collection: This area relates to enterprise-wide data collection. It covers understanding of data required for multiple users. It is also extremely important to verify the quality and type of collected data reflected in the Business Intelligence insights.

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–  Information Management: This area implies data integration, dataset scraping, the structure arrangement, and data administration.

–      Business Intelligence: It is a part of overall corporate architecture capable of analyzing organized data properly to provide insights about business performance.

As per Forbes, the business intelligence architecture sets the technology standards, as well as data management and analytics best practices. A reliable architecture establishes policies to determine the use of the technology components. Implementing such a framework enables a BI team to operate in a coordinated and disciplined way when building an enterprise Business Intelligence program in compliance with corporate data analytics needs.

 

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Framework

Today, businesses proactively use Business Intelligence services. Companies consistently look for the most optimal ways to collect, store, and interpret data since any business requires accurate information for decision-making.

As said above, Business Intelligence blends data warehousing, business analytics, performance, strategy, and user interface. The data is kept in the data warehouse, where it is stored, arranged, and summarized as per long-run utilization. Only authorized users are able to access and leverage this data to reach the desired outcomes.

Components

One can differentiate five components of Business Intelligence, namely:

–      OLAP or Online Analytical Processing: It makes it easier for executives to sort out and select data aggregate to monitor it from a strategic point of view.

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–      Corporate Performance Management /Advanced Analytics: This tool is vital when working with statistics of products or services. The obtained data can also be used to forecast which markets a new product or service may have the best success in.

–   Real-time Business Intelligence: It helps businesses keep up-to-date with the ever-changing marketing trends. By using software apps, a business can address and follow real-time trends in email, messaging systems, and digital displays. For example, the marketing team can present special offers to grab clients’ attention when clients are engaged on the website.

–      Data Warehousing: It covers big datasets storage to the benefit of different divisions of a company. Reviewing sales data over several years can significantly improve product development or customize seasonal offerings. Data warehousing involves keeping big amounts of data in ways that are advantageous to different divisions within one company.

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–      Data Sources: It is related to processing raw data and creating systematic data sources by leveraging various software applications. Business Intelligence Analysts proactively create data tools enabling data to be collected from a large cache of spreadsheets, charts, or graphs that can be used for a variety of business purposes.

Categories

One can outline three types of Business Intelligence analysis, which cover many different critical needs and uses:

– Predictive analytics processes historical and real-time data to model possible outcomes for planning and strategizing.

– Descriptive analytics relates to identifying trends and key relationships in data leveraging historical and current data.

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– Prescriptive analytics processes relevant data to address the issue.

Benefits

The significance of Business Intelligence is skyrocketing, and its usage has become widespread across various types of users. Previously, it was in the domain of IT professionals only, but now business teams also proactively adopt business intelligence tools. Business intelligence usage can be easily optimized by determining critical projects on which a specific company would like to focus. Companies should consider using Business Intelligence tools at any stage to analyze, manage, and visualize business data enabling the company to maximize revenue streams. Among the key benefits of Business Intelligence, it is important to outline the next:

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– Accurate reporting with rapid turnaround

– Detailed data analysis

– Consistent data quality improvement

– High operational data efficiency

– Customer satisfaction growth

– Flawless decision making

– Lower margins

– Business revenues optimization

Conclusion

Business Intelligence helps business executives use data in meaningful and effective ways. Using the tools obtained from Business Intelligent components, companies can better leverage data for competitive advantages. When used wisely, the data can facilitate informed business decisions that respond to market trends and other external factors. Business Intelligence provides methodologies and tools for business leaders to boost transformation and change effectively and lead their companies with a more holistic view of growth perspective.

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Businesses experience a strong need to stay competitive, and here is the business intelligence that comes in. Nowadays, up to 50% of small and large companies proactively employ Business Intelligence tools, which tend to grow in coming years. Business intelligence is developing to cover all business needs and emerging technology. With companies getting more data-driven, efforts to share data and collaborate cross-functionally will rapidly grow.

About the author:

Janet Polson is a graduate of George Washington University in International business. She is an unspoken expert in the study of science and philosophy. Janet is also a blogger, author of tech articles and she works as business analyst at Computools.

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