Steps to Efficiently Create a Reporting Platform
“Every company has big data in its future, and every company will eventually be in the data business,” said Thomas H. Davenport, the President’s Distinguished Professor of Information Technology and Management at Babson College. Indeed, data analytics is a valuable tool for entrepreneurs looking to make data-driven business decisions.
According to the Global Reporting Software Market report, the reporting software market size was valued at USD 14.94 Billion in 2024 and is projected to reach USD 37.56 Million by 2031, growing at a CAGR of 12.81% from 2024 to 2031. The market is growing at a fast pace, therefore if you want to create a reporting platform and gain market share, this article is for you. Keep reading on to learn how to make custom report writing software.
What are the Superpowers of Reporting Software?
First of all, what is reporting software? Reporting platforms fall under the umbrella of Business Intelligence tools, designed to generate reports from various data sources based on user inputs. Since the data is extracted and presented in predefined formats, BI software aids entrepreneurs in analyzing and forecasting potential outcomes related to interactions with customers, markets, and other businesses. This analytical capability simplifies decision-making processes that contribute to the company’s future success.
There exists a variety of reporting software types, such as dashboards, BI tools, and specialized platforms. They offer a deep overview of key performance indicators (KPIs) and other crucial metrics i.e. advanced analytics and data visualization features.
A primary advantage of reporting platforms is their ability to enhance decision-making processes within companies. By delivering precise information, this software enables users to detect patterns, recognize trends, and make decisions grounded on data-driven insights.
The capacity to automate reporting workflows saves measurable time and efficiency while also focusing on transparency and flexibility. The best practices in reporting software constitute an extensive list with these being the top:
- Automated data collection. The report solution features automated data collection that enables it to address multiple issues and facilitate business analysis. The software assesses data consistency across reports and maintains an auditable history. This significantly reduces report creation time and minimizes errors.
- Elimination of data bureaucracy. Reporting software offers self-service capabilities, eliminating traditional bureaucratic hurdles where only specific executives can access data. Users simply log in with their credentials to access reports, streamlining access requirements.
- Mobile accessibility. Reporting software is accessible via mobile devices, which empowers users with full functionality on the go. This feature allows remote users to update project statuses in real-time — as a result, businesses get timely data for informed decision-making.
How AI is Transforming Reporting and Data Analytics
First thing first, before we move on to steps required to build an efficient reporting platform, let’s talk about the role of artificial intelligence in analytics and how to incorporate AI in your reporting tool.
AI reporting refers to an advanced strategy that uses modern data processing techniques, machine learning algorithms and natural language processing (NLP) to create comprehensive narratives and visualizations from large data volumes. It surpasses traditional reporting approaches by automating the entire process, from data gathering to analysis.
At its foundation, AI reporting converts raw data into actionable insights that can help businesses make decisions — so BI tools can be even more efficient, being able to uncover patterns, trends and connections that humans may find difficult to determine in short time. This helps businesses better understand their operatons, clientele and market trends.
Business Intelligence software works best with the implementation of four categories of data analytics which include descriptive, diagnostic, prescriptive and predicative.
- Descriptive analytics — reveals “what happened” by showing data from past events and business performance trends, like year-over-year comparisons and user volume, forming a foundational basis for data insights.
- Diagnostic analytics — investigates reasons behind outcomes through techniques such as drill-down and data mining. This helps to identify behavioral patterns and connections within data.
- Predictive analytics — forecasts future trends and events through statistical modeling and existing data, crucial for proactive decision-making in fields like marketing and insurance. Predictive analytics covers decision trees, neural networks, and regression models.
- Prescriptive analytics — uses AI to recommend optimal actions and strategic decisions. Overall, this approach helps to refine decision-making processes and improve overall business performance.
Together, these analytics types collectively boost business performance and drive success. Good reporting solutions based on AI will help you to handle the burst of data. But how to develop such software most efficiently? Below are key custom web application development steps.
Define Your Objectives – Step 1
Prior to hiring IT specialists, you should have a clear vision of what you want your data reporting platform to do, as well as the types of data sources and tools it will work with. You should also define the scope and frequency of your data reporting needs, such as daily, weekly, monthly, or ad hoc reports, as well as the level of detail and customization.
Build vs. Buy: Evaluate the cost-benefit of custom development vs. pre-built reporting tools
Choosing whether to purchase or create your report generating software is a big decision. You want to be sure that you end up with a reporting system that has a high ROI, helps decision-making, and is simple to use.
If you’re set on bespoke development, you get maximum flexibility and control. However, it requires significant development resources and ongoing maintenance. Consider a custom build if you have highly specific reporting needs or a complex data landscape. With a ready-made tool, you can hit the ground running immediately, but it usually comes with limited capabilities listed in the table below.
| Aspect | Custom Development | Pre-built Reporting Tools |
| Initial Cost | High (Development costs, infrastructure setup) | Low to Moderate (Subscription or licensing fee) |
| Maintenance Cost | High (Ongoing maintenance, updates, bug fixes) | Low to Moderate (Vendor handles updates/maintenance) |
| Time to Implement | Long (Months to years, depending on complexity) | Short (Immediate to a few weeks) |
| Customization | High (Fully tailored to specific needs) | Limited (Depends on tool flexibility and customization options) |
| Scalability | Variable (Depends on design and infrastructure) | High (Usually designed to scale) |
| Expertise Required | High (Requires skilled developers and IT staff) | Low to Moderate (Some training for users) |
| Integration | High (Can be integrated with any system) | Variable (Depends on tool’s compatibility with existing systems) |
| Support and Training | Variable (Depends on in-house resources) | High (Vendor typically provides support and training) |
| Upgrades | Custom (Depends on development cycle) | Regular (Provided by vendor) |
| Data Security | High (Custom solutions can be built with security in mind) | Variable (Depends on vendor’s security protocols) |
| Control | High (Full control over features and data) | Moderate (Vendor controls certain aspects) |
| Vendor Lock-in | None (Fully owned and controlled in-house) | High (Dependence on vendor’s ecosystem and future pricing) |
| Innovation and Features | High (Can innovate as needed) | Moderate (Dependent on vendor’s roadmap) |
| Compliance | High (Can be tailored to specific regulations) | Variable (Depends on vendor’s compliance standards) |
Identifying key metrics and KPIs
It is essential to ensure that the platform effectively measures and communicates business performance. Key metrics and KPIs should be aligned with the business’s strategic objectives and provide actionable insights. These may include financial metrics such as revenue, profitability, and cost efficiency; operational metrics such as production output, customer satisfaction scores, and efficiency ratios; and strategic metrics like market share, customer acquisition cost, and retention rates.
Understanding stakeholder needs
Your data reporting solution should meet the demands and expectations of your internal and external stakeholders, including executives, managers, analysts, customers, and partners. You should learn who they are, what type of data they require, how they prefer to access and consume data, and what kind of feedback and collaboration they provide. For this purpose, it is important to create clear communication channels and feedback loops with your stakeholders and users and include them in the design and testing of your data reporting solutions.
Setting clear goals for your reporting platform
This stage is where your idea turns into a value. Determine clear objectives that influence the overall development process and the ways everything will be designed. Different departments demand differently. However, these factors must be included:
- supporting multiple data sources;
- easiness in designing reports;
- flexible reports delivery;
- ease of customization; and
- convenience for operation & maintenance.
Choose the Right Tools and Technologies – Step 2
You should take into account the features, prices, and compatibility of various data reporting frameworks and tools, and select the ones that fit your business needs and preferences. Here’s how.
Evaluating reporting tools and software
Whatever feature you need to build for your data analytics platform, there are dozens of custom reporting tools that can be used for it. While there are some standard programming languages for front-end and back-end development, tools for specific functionality differ a lot.
Considering scalability and integration capabilities
Scalability is another critical factor when choosing tools for your reporting platform. Since your business is constantly growing, the reporting tool should be able to handle increasing data volumes and user demands smoothly. Additionally, the chosen tool should integrate seamlessly with your current IT infrastructure, including databases, CRM/ERP systems, and cloud services. This integration capability streamlines data flows and ensures consistency across different platforms. This way you level up the overall efficiency of your reporting processes.
Comparing self-service vs. enterprise-level solutions
Self-service solutions empower users to create and customize reports independently, with flexibility and agility in data analysis. On the other hand, enterprise-level solutions provide robust governance, security, and advanced analytics capabilities suitable for large-scale deployments and complex data environments.
Design the Data Architecture – Step 3
After stakeholders and the software development team have compiled the requirements for the data analytics platform, the next step is for a software architect to design the application’s reports architecture and logic.
Concurrently, a UI/UX designer does their part during this phase too. It is crucial to visualize the structure of your data analytics system before commencing development. Once the enterprise reporting architecture and UI/UX design are ready, development can start.
Overall, creating an effective reporting platform hinges on designing a robust data architecture that ensures data integrity, accessibility, and reliability. Here’s how to strategically approach each aspect:
Data source identification and integration
Begin by cataloging all potential sources — whether they’re operational databases, CRM systems, marketing platforms, or external APIs. Utilize ETL tools to consolidate data from many sources into a unified format suitable for reporting.
Ensuring data quality and consistency
Employ data cleansing and validation mechanisms to identify and rectify inaccuracies, duplicates, and missing data. Establish data governance policies to enforce standards for data entry, storage, and usage across the organization.
Data warehousing and ETL processes
Data warehousing plays a crucial role in housing consolidated, cleansed information that serves as the basis for reporting. You can utilize ETL software to collect data from source systems, transform it into a consistent format, and load it into the data warehouse. In your reporting system architecture, consider data modeling techniques, indexing strategies, and partitioning to optimize query performance and ensure timely access to critical business insights.
Step 4: Develop Interactive Dashboards and Reports
Data alone is not enough. To make informed decisions and take action, we must evaluate, visualize, and effectively explain it. One of the best ways to do this is to create dashboards and reports.
Best practices for dashboard design
Start by understanding the needs and preferences of end-users through stakeholder consultations and user feedback. The dashboards are efficient when focused on key metrics and KPIs relevant to the audience and when they avoid clutter and unnecessary complexity. Also, it is recommended to use interactive features like drill-down capabilities, filters, and hover-over tooltips to enhance user engagement and enable deeper exploration of data insights.
Creating user-friendly reports
Interactive dashboards and reports enable:
- exploring and uncovering patterns, trends, and relationships within data to gain insights and understanding;
- communicating effectively with data through compelling storytelling and emphasizing key messages;
- monitoring performance and progress by tracking and comparing metrics and indicators; and
- analyzing processes and outcomes to identify and address challenges and opportunities for optimization.
For the best match, it is advised to utilize charts, graphs, and tables judiciously to present data in a digestible format. Also, it is recommended to integrate interactive elements in your reporting application design such as clickable elements, filters, and dynamic parameters to allow users to customize views and drill deeper into specific data segments. For this purpose, there are many tools and platforms available for creating interactive dashboards and reports, such as Microsoft Power BI, Tableau, Google Data Studio, and others.
Utilizing data visualization techniques
Choose appropriate visualization types based on the nature of the data and the insights you wish to convey — common types include bar charts, line graphs, pie charts, and heat maps. Use colors strategically to highlight trends, comparisons, and outliers while maintaining readability and accessibility for all users.
Business owners need a reporting platform for data-driven decision-making. If you have a concept of creating a data analytics platform, we at Broscorp can guide you through this process.
Implement Security and Access Controls – Step 5
Security and access controls are critical elements of any reporting platform to safeguard data integrity, confidentiality, and compliance with regulatory requirements.
Here’s how to implement these measures in your custom reporting tool:
Ensuring data privacy and compliance
Working with data requires protecting data privacy and ensuring compliance with regulations such as GDPR, HIPAA, or CCPA. We strongly advise that you start by conducting a thorough assessment of data handling practices and identifying sensitive data. To secure data both at rest and in transit, incorporate encryption techniques.
Role-based access controls (RBAC)
RBACs are instrumental in managing user permissions and restricting access to sensitive data based on predefined roles and responsibilities. You can utilize authentication mechanisms such as single sign-on (SSO) or multi-factor authentication (MFA) to verify user identities securely.
Test and Iterate – Step 6
Once a reporting application is developed, you need to ensure it meets user expectations and operational requirements. Let’s consider a structured approach to testing and refining the platform:
Conducting user testing and gathering feedback
The first step is conducting comprehensive user testing with representatives from all stakeholder groups who will interact with the platform. You can collect quantitative feedback through surveys and analytics to measure user satisfaction and engagement.
Identifying and fixing issues
During testing, it is important to identify and prioritize issues such as bugs, usability challenges, and performance bottlenecks. At this stage, it is essential to conduct regression testing to ensure that fixes do not introduce new issues and verify that all reported issues have been adequately addressed before proceeding to deployment.
Continuous improvement and updates
Achieving excellence in reporting platform performance requires a commitment to continuous improvement. For this, you can implement a feedback loop where user insights and operational metrics inform ongoing updates and enhancements.
Train Users and Promote Adoption – Step 7
Introducing a newly developed reporting platform involves not only deploying the technology but also ensuring its successful adoption and utilization.
Training programs and resources for end-users
Implement comprehensive training programs tailored to the needs of different user groups, such as administrators, analysts, and executives. Offer training sessions that cover basic functionalities as well as advanced features of the reporting platform.
Encouraging a data-driven culture
Promote a data-driven culture within the organization by highlighting the value and benefits of data-driven decision-making. Emphasize how the reporting platform enables users to access timely, accurate insights that inform strategic initiatives and operational improvements.
Tracking usage and engagement for further enhancements
Monitor and analyze usage metrics and engagement patterns to assess the effectiveness of training efforts and identify areas for improvement. Also, utilize analytics tools integrated into the reporting platform to track user activity, such as logins, dashboard views, and report downloads.
Industries That Benefit from Reporting Platforms
Now that we have a better understanding of how to build a custom reporting app, let’s take a look at some use cases.
Fintech
Fintech companies use custom reporting software to manage vast amounts of financial data efficiently. They benefit from a comprehensive analysis of customer transactions, risk management, and portfolio performance provided by these platforms.
An example — Enhanza. Via Fintech software development, we at Broscorp have built a financial data pipeline that fetches real-time data from ERP, stores it, aggregates it, and creates comprehensive analytics on top. This solution speeds up the decision-making process and cuts profit losses.
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Crypto
In the cryptocurrency sector, reporting platforms are responsible for tracking and analyzing transaction data, market trends, and investor behavior. These on-chain analytics solutions provide real-time insights into trading volumes, price movements, and market sentiment, helping traders, exchanges, and regulators make informed decisions.
Telecommunications
One more industry that actively utilizes reporting tools is telecommunications. Telecom companies utilize telecom real-time network analytics, telecom network performance monitoring, and provisioning systems to monitor KPIs such as call volumes, network congestion, and customer satisfaction metrics.
Energy and Utilities
Last but not least, reporting platforms are essential for energy and utility companies to monitor and manage energy production, distribution, and consumption. These platforms analyze data from smart meters, sensors, and IoT devices to optimize energy efficiency, detect anomalies, and predict demand patterns. Additionally, these platforms aid in grid management, outage response, and maintenance planning.
Final Notes
As you can see, custom reporting apps can be used to track a variety of key metrics and performance indicators. By taking advantage of all the data you’ve already pulled in your BI tool, your business can gain valuable insights into the performance of its operations.
Ready to unleash the power of data? If you are looking to build custom software for creating reports for your business, contact our Broscorp developers. We will build an app that is tailored to your specific needs. In time, you’ll begin to find that the insights offered by the implementation of business intelligence are far more valuable than simple bar charts like Excel were able to offer.
