bi framework

High-quality information is necessary for efficient decision-making in business. In today’s cutthroat business market, quick access to a data storage warehouse that is structured to boost corporate performance and provide quick, precise, and pertinent data insights is necessary. Data warehousing serves as the foundation of the bi framework that has developed to fulfil these needs.

Let’s look into what a BI framework is, what components make up a BI framework, and all the benefits of implementing a business intelligence framework. 

But first, the basics. 

What is a BI Framework? 


Building business intelligence systems requires a framework made up of best practises, policies, and standards.

By offering this framework, business intelligence architecture makes sure that the development efforts of various projects seamlessly integrate to produce the intended BI solution.

A strategic method of gathering business intelligence for enhanced decision-making is called a BI framework or architecture.

It aids in ensuring that all pertinent data is used, that the data is accurate and vetted, and that the data is used appropriately.

In the end, a BI framework is a method that enables you to fully utilise your data to solve business challenges at their best and seize opportunities as they arise.

As its name suggests, a business intelligence framework integrates all of the major components of a company, including organisational roles, KPIs, authorization, and visualisation. This aids in making it easier and faster to implement business intelligence plans.

Why do You Need a BI Framework? 

There are several factors for why you should think of developing a BI system long before a company begins to implement a business intelligence framework.

Although there are numerous crucial elements, the following stand out:

Helps with Business Request Backlog 

The IT department is under considerable pressure to fulfil the report requests from numerous business users.

An effective BI framework can help simplify and streamline this procedure. 

Helps with Ineffective Functioning IT Systems 

Data silos, diverse data and applications, and various data formats combine to create a complicated IT system, supporting the need for a more robust BI architecture.

Helps with the Need for Self-Service 

Business users are in a bind because they must rely on IT for even little pieces of information.

This impairs their ability to make decisions and creates a bottleneck for efficient functioning.

Finances and Costs 


A company suffers when information silos are maintained and large amounts of IT resources are used to process even tiny collections of data.

These elements force the firms to create a business intelligence architecture that aims to improve their decision-making.

A strong architecture will aid in organising the process of enhancing business intelligence and aids in the cost-effective implementation of the business intelligence plan.

Benefits of Implementing a BI Framework 

Although it is apparent that you need a BI framework, what else can you gain from implementing such Bi architecture? 

Let’s examine the benefits of utilizing a BI framework in more detail. Here are four potent advantages you might anticipate.

1. Better Quality Data 

data analytics in small business

You can verify that your data is accurate, comprehensive, relevant, clean, and current by following a consistent structure and step-by-step procedure.

You won’t inadvertently ignore crucial data, start your analysis before the data has been cleansed and confirmed, or utilise obsolete data.

The location of data that is ready for analysis will be known to decision-makers with the use of a business intelligence framework.

Additionally, you’ll prevent data extracts that impair data quality if you utilise a cloud-native BI tool that works with your cloud data warehouse.

2. Decision Making Made Faster and Simpler 

Because it is speed-optimized, a business intelligence framework also leads to quicker decision-making (while preserving accuracy).

Decision-makers must have access to information as soon as possible since business evolves swiftly.

When you employ a BI system that enables users to work in a spreadsheet-like interface while automating SQL creation, this performance is increased even further.

3. Better and More Accurate Understandings 

You can be sure in the calibre of the insights you draw from your data when you are confident in the quality of your data.

Additionally, all potential perspectives on a problem may be taken into account with a framework that encourages decision-makers to thoroughly analyse the facts and dig deeper to find the answers to follow-up questions.

4. Useful Reporting 

useful reporting

By making reporting actionable, a business intelligence framework enhances the reporting process.

A framework places a strong emphasis on adhering to a structured procedure, which helps business problems to be clearly stated and allows findings to be used practically.

Business Intelligence Components 

Well, it is very clear that a BI framework is an essential tool for any business to gain valuable benefits and continue to progress.

So, what makes up the elements of business intelligence? 

There are seven key elements of business intelligence. Let’s go over each of these seven business intelligence components in turn. 

1. Tools and Technologies 

BI Framework analytics-tools

What tools and technology you choose to develop a BI framework is an essential element.

It includes both the front-end UI tools and the EIM toolkits. There are various full-featured BI systems as well as cloud solutions, SaaS models, and other options available.

The BI architecture should provide rules for deciding what the organisation needs.

2. Business Intelligence Hardware 

Making judgments about the hardware needed to support a high-performance and scalable BI system is crucial.

In addition to server configurations, data warehouse appliances are available to integrate the server, database, and data storage into a single solution.

3. Source Systems 

There are two kinds of source systems:

  • Systems for Processing Transactions: This serves as the foundation of every BI endeavour. In these databases, organisation data is initially established. One thing to keep in mind is that you cannot analyse data if it is not captured in the operational system.
  • OLTP or Operational Systems: For data warehousing, the majority of the data comes from operational systems (OLTP). Additionally, source systems could also contain information from secondary sources, like market data, benchmarking data, etc. All of these distinct data sources, which use multiple formats and standards, should be addressed by the business intelligence architecture.

4. Data Modeling 

The structure of the data and its relationships to other data pieces will be addressed through data modelling, which will also assist in determining exactly what is required from data sources.

The expense of extracting everything from a source system makes it impractical. Data organisation through data modelling will reduce the cost of storage replication and the time required to establish a data warehouse.

5. Data Warehousing 

cloud-data-warehouse BI Framework

Data will be gathered from multiple operating systems, converted to ensure consistency, and placed into the warehouse for analysis.

Cross-functional analysis, summarising data, and keeping one version of the truth throughout the organisation may all be accomplished with the use of a data warehouse.

6. EIM or Enterprise Information Management 

Another BI acronym that may be confusing to newcomers is EMI.

The phrase often relates to metadata management, master data management, data quality, data profiling, ETL tools, and data modelling tools.

7. ETL Processes 

Data is taken from the operating systems and placed into a data warehouse through an ETL process.

ETL, which stands for Extract Transform Load, is often carried out utilising market-available bespoke solutions.

How Ascend Helps You Implement a Business Intelligence Strategy 

Ascend-Analytics-logo BI Framework

Ascend Analytics uses descriptive, diagnostic, prescriptive, and advanced analytics to maximise an organization’s potential.

The data science service providers at Ascend contribute to increased visibility, which boosts operational effectiveness and increases business profitability.

Our data analysis specialists at Ascend Analytics can assist your company in implementing business solutions using vital digital data.

Whether you want to improve customer experience, design your goods and services, or save expenses, we can aid your business’s bottom line as a data and analytics consulting firm with experience across several industries.

Forecasting, optimization, and the creation of a straightforward yet effective plans are all made possible by BI Solutions.

Businesses that offer business intelligence services synthesise and analyse complicated data for optimal functional usage. This is done through:

  • Importing and cleansing data 
  • Data mining 
  • Viewing and visualizing big data 
  • Achieving casual usability 
  • Dissemination 
  • Evaluation 

In Conclusion  

A business intelligence framework enables decision-makers to swiftly find answers to key issues and have faith in the precision of their insights, enabling businesses to make the most of their data.

We looked at the advantages of BI frameworks as well as the elements that will enhance your team’s capacity to employ data to drive growth.

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