How to Centralize Business Intelligence Through System Integration

Still navigating a sea of spreadsheets, dashboards, and disconnected systems to get a complete picture of your business data? You are certainly not alone. 

For most modern organizations that collect data across people and departments, including sales, operations, human resources (HR), and marketing, data overload results in disconnected insights.  

The result is slow decisions, duplicate efforts, and missed opportunities. This is the strength that centralized Business Intelligence (BI) can provide, and the backbone of BI is system integration.   

In this blog, we will show you how to centralize your BI by integrating your data, the real benefits, the pieces involved, and best practices for a seamless integration experience.  

What is Centralized Business Intelligence?

Centralized Business Intelligence is the practice of consolidating data from multiple individual locations into a single, centralized platform.  

This way, decision-makers are not reading various reports and referencing different systems; they are using real-time, reliable insights from one true source of truth.     

Picture a single control tower for your business, where all data is fed into one location in its cleaned/transformed state, analysed, and ready to drive strategic insights and informed decision-making.    

Rather than allowing different departments to build their reports in a siloed fashion as commonly done in decentralized BI, centralized BI provides uniformity, alignment, and transparency across the organization.  

Why Businesses Struggle with Fragmented BI

Let’s dissect it using a relatable example.  

• Your sales department uses Salesforce.  

• Your marketing department uses HubSpot.  

• Your finance department uses Excel sheets.  

• Your operations data is in an on-prem ERP system. 

Now imagine measuring your customer acquisition cost (CAC) or ROI amidst this mess. Each platform contributes to the full picture, but without integration, your BI becomes a guessing game.    

This disconnection causes:

• Inconsistent KPIs between teams    

• Manual pulling of data and reporting inconsistencies    

• Redundant dashboards that are outdated    

• A lag in decision-making and reactive instead of proactive  

System Integration: The Bridge to Unified Intelligence

Systems integration is combining existing IT systems, software applications, and data sources, which enables them to work together as one system or collection of similar systems (an ecosystem).   

When systems integration is applied to BI, it means that you can move your data sources (data from CRMs, ERPs, HRMSs, cloud apps, legacy systems) to one source of truth (data warehouse or lake).  

Then you can display that integrated data with a data visualization system, such as Power BI, Tableau, or Looker.     

Here are some key reasons why integrating your systems to achieve BI is a good move:   

• Real-time reporting: you have current data and insights instantly     

• Improved accuracy: reduced human error from manual data entry   

• Data transparency: everyone is working with the same version of the truth     

• Enhanced collaboration: teams are working toward common metrics and goals 

What Makes Up a Centralized BI System?

To successfully centralize BI, there are several elements to consider.  Let’s look at the ingredients:    

1. Data Warehouses or Data Lakes:
   Data stores that centrally house integrated data.  Data Warehouse is appropriate for (structured) data with reporting, and Data Lake is appropriate for raw or unstructured data (logs, sensor data, etc).  

2. ETL/ELT Pipelines:
   ETL (Extract, Transform, Load) or ELT (Extract, Load, Transform) pipelines move data from siloed sources, sanitize it, and load the result to a central data store.  

3. Integration Platforms (iPaaS/Middleware):
   Platforms such as MuleSoft, Dell Boomi, or Azure Data Factory automate the Data Integration in let's mess with hybrid (Cloud and on-premises) environments.

4. Visualization Tools:
   Dashboarding that engages business users certified in visualization professional packages such as Power BI or Tableau, allowing users to see trends, compare metrics, and interpret the signals without having to analyse and interpret the underlying raw data.

5. Master Data Management (MDM)
   MDM ensures that core business entities (e.g., customers, products, locations) are defined in the same way across applications.  

Step-by-Step: Centralized BI Through Systems Integration

Let’s break the journey to centralized BI into distinct, actionable steps:  

Step 1: Evaluate Your Current Data Environment

Consider every source of data, such as CRMs, ERPs, HR systems, spreadsheets, APIs, etc. Identify where your data lives, the formats in which it may exist, and how that data flows across departments.   

Step 2: Identify Business Outcomes and Key Performance Indicators (KPIs)

What outcomes are you trying to achieve with centralized BI (more accurate forecasting, better customer-based insights, improved visibility across the organization, etc)? You need to pin down what you’re trying to achieve and the associated metrics.

Step 3: Select Appropriate Integration Strategy

There are several ways to take these integration steps:

• Point-to-Point: Since data integration architecture is simple and operates directly from source to destination, the resulting architecture becomes chaotic on a large scale, and area-specific integration points also become unmanageable.   

• Hub-and-Spoke: Uses a broker or hub as the central integration point. Less chaotic & more maintainable.   

• iPaaS: Cloud-based integration platforms are designed for quickly and easily building complex integrations and applications.     

Implementing these technologies will require deciding on your infrastructure choices, whether to use a cloud-native, on-premises, or hybrid technology architecture.   

Step 4: Develop a Scalable Integration Framework

Identify the tools and platforms to use for your current tech stack with your expected future state in mind. Build your data pipelines as robust as possible, define your metadata, and implement a version control system.

Step 5: Clean Your Data and Govern it

Bad data = unsuccessful BI. Once you have created a data pipeline and continuous integration plan, it is essential to establish data quality standards. This could include standardizing data formats, eliminate duplicates, and create data governance rules for ongoing data quality validation.

Step 6: Produce BI Dashboards/Reports

Now that your system(s) are talking to each other, producing dynamic dashboards that provide visual clarity and role-based access to limit who sees what data, data publication, and management become easier.

Best Practices for a Successful BI Centralization Journey

Centralizing BI via integration isn't a task; it’s a journey. To help ensure success over the long run, consider these suggestions:   

• Start Small, Scale Up Later:   
  Start integrating the essential pieces - CRM and ERP - and expand to marketing, HR, and more.     

• Establish Good Data Governance:  
  Create policies around access to data, ownership of data, and the length of time for retaining data. Good, clean data governed correctly = trustworthy BI.     

• Provide Training on BI to Teams:
  Provide your employees with the training and skills needed to use centralized BI dashboards.     

• Automate Everything You Can:   
  Set up automation for data refreshes, alerts, and for detecting anomalies so you can keep data accurate while minimizing manual interventions.   

• Review, Evaluate, and Iterate:
  Continue to review and assess system performance, data latency, and usage of reports (who is using what?). You want to continuously iterate on the back-end integrations as well as the front-end dashboards.  

How Vionsys IT Solutions Helps You Integrate and Centralize BI

Vionsys IT Solutions helps businesses connect their siloed systems to insightful information.

Our BI & Analytics solutions are based upon:

• Strategic Data Alignment:Your data model must support your business goals, not the reverse.  

• Smart Source Integration: We connect cloud, on-prem, and third-party data sources into a comprehensive domain layer.  

• Contextual Data Modelling: Our data architects develop dynamic, flexible data models contextualized to your industry.    

• Insightful Dashboards: We deliver user-centred dashboards for Executives, Managers, and Analysts.    

• Ongoing Optimization: We are continually optimizing your system for your organization's evolving needs.  

Vionsys IT Solutions provides genuine business intelligence to mid-sized and enterprise-level organizations in a faster, more intelligent manner.  

It's Time to Break Down the Walls

Your data is the most valuable component of your business, but only if it's accessible, accurate, and usable.

Centralizing Business Intelligence through systems integration is much more than doing a technology project; it's a business change. It gives you agility, confidence, and insight to act.

And when everything in the market is changing by the minute, that's everything.

Are you ready to centralize your BI and turn your data into a competitive advantage?

Get in touch with our team at Vionsys IT Solutions - we'll help you create both the roadmap and the structure to get there.

FAQs

1. What is the main objective of centralizing your business intelligence?     
   To create a single, real-time perspective of your business data to enable smarter and quicker decision-making.   

2. Can small businesses also benefit from BI centralization?   
   Yes. Any small business can minimize manual reporting and have an easier way to make decisions with an integrated system.   

3. What are some common challenges to integrating business systems?     
   Legacy systems, data-silos, a lack of documentation, and differences in data formats are just some challenges.

4. How long does it take to centralize BI through system integration?     
   The length of time to centralize BI depends on the size and complexity of your systems. It can take from a few weeks to several months.