It doesn’t matter what kind of business you have; it’s going through some form of BI development process. Today, every business runs on applications that generate data and provide basic reporting. Executives and managers in business use spreadsheets for more than just complex calculations, but also for shaping and working with numbers and tables, gaining insights into business operations through these tools.

It’s not full-fledged business intelligence, though. A spreadsheet or report is an essential tactical tool, but it’s not strategic. A report today is a commodity application that doesn’t contribute to an organization’s vision of where and how it wishes to achieve its objectives. It’s just a tool.

Creating a BI development process begins with crafting a strategy. Business intelligence strategies are blueprints for how your company will use data. To realize a return on investment, you need more than just the right technology. Three factors must be considered to create a strategy.

What is the plan for deploying the software platform? How will you manage the data to analyze it? What will you do to ensure your people can make informed, data-driven decisions? Having actionable insights is the result of a business intelligence strategy. 

To create an effective BI development process, you can get help from Ascend Analytics.

Benefits of a BI Strategy

  • Developing a business intelligence strategy requires understanding how to deliver a competitive advantage. 
  • With BI and analytics, businesses can gain a better understanding of markets, customers, operational processes, and business performance by using data-driven and objective insights and from better-informed business users. This includes developing an architecture for BI and deploying BI systems and applications based on that architecture, whether on-premises or in the cloud. 
  • An effective BI strategy is more than an outline of technology: It builds an ethos of wise, reasoned decision-making that will serve your organization well in both good and bad times.
  • By improving decision-making and streamlining processes, business intelligence development can help organizations maximize the value of their data.

Here are some tips on how to develop a winning business intelligence strategy.

Outsource your software development to Ascend Analytics’ experienced and qualified teams of data engineers and BI developers to build an effective BI solution.

How to Create a BI Development Process?

Data can drive transformation in your organization. You should align your BI strategy with your organization’s goals and vision. 

Let’s walk through some of the most productive BI development process steps.

Identifying business needs

Defining what success looks like is a key component of business intelligence success, which can be challenging. Business users often don’t know what they want at the start of this process because they don’t have access to adequate data and don’t know what’s possible. 

However, even if the business can define some requirements, IT won’t yet know what can be delivered since they will need to fully understand the business requirements before comparing them to the available source data.

With our BI Requirements Survey, clients can identify their requirements on an ongoing basis and populate the desired insights database. This allows requirements to change over time and forms the basis for setting goals at the beginning of every sprint.

Gap analysis of data


A goal pool is defined by one-half of a business requirement and by the other half of the available data. In consultation with various subject matter experts, you will examine the available data carefully and continually reevaluate which goals are most likely to support and provide the most outstanding business value. 

This process results in a list of achievable goals and an estimate of how much effort it will take to accomplish each.

Selection and prioritization of goals

When a technical solution is developed using an agile process, it can adapt quickly to changing requirements and data without unnecessary delays. As a result, every development cycle presents a chance to reevaluate everything you know and adjust goals and strategies.

Detailed requirements & design

data-requirements-and-design BI Development Process

It is important to conduct detailed requirements gathering whenever a goal is prioritized for development, including interviews with stakeholders, subject matter experts, and data stewards. This process results in a user story describing how the business would like to receive the information and the technical details required to source, transform, and load the data. Combining discovery and design allows you to move quickly and avoid unnecessary delays that typically occur when requirements gathering is delayed by technical design.

Data governance & compliance

Organizations must take steps to protect people’s personal information and govern how it’s used in light of increasing concerns over data privacy and legislation.

It is important to consider the specific needs of each discipline when implementing a BI strategy, even though data privacy and security are naturally related. A particularly large data set that isn’t stored in a conventional relational database with mature, fine-grained access controls is especially vulnerable to this problem. Good security is necessary to maintain privacy, but that alone does not guarantee that sensitive information is held securely and used appropriately.

The governance of data and regulatory compliance are closely related as well. Although good governance cannot guarantee compliance with specific legislation or codes of practice, it isn’t easy to know how your organization stands on them without effective governance processes.

By understanding this distinction, you will be able to take the next steps in the BI implementation more confidently.

Selection of data solutions

This portion of the technical solution enables the acquisition of data and the preparation of it for reporting. In determining which types of reports can be produced and by whom, the data solution (not the reporting software) is of the utmost importance. An enterprise-wide dimensionally-modeled data warehouse can be as simple as direct system reporting. A single company may require data solutions based on their requirements at different times. 

As it is the heart of the technical design, we constantly reevaluate the data solution.

Data infrastructure

data-infrastructure BI Development Process

To perform accurate analyses, business intelligence platforms must have clear data sources. Traditionally, business intelligence platforms import data from a data warehouse. But modern BI lets you analyze data from a variety of sources. Two types of data are considered: trusted and untrusted.

A database containing trusted data, such as spreadsheets, customer relationship management (CRM) data, financial data, etc., is stored or imported easily into the database. In previous business analytics, this type of data may have been used. 

With modern BI, you can analyze untrusted data in a governed and secure environment. Untrusted data can include emails, customer conversations, business processes, images, news items, trade journals, etc. Before deploying the BI platform, stakeholders and information consumers need to be surveyed to determine which data sources are required for analysis.

Data collaboration for quick actions

Analysis without action is just as wasteful as data without analysis. A complex business intelligence dashboard may present a range of metrics but cannot direct business users to act.

BI tools can be integrated with operational applications. They can also be used to create low-code or no-code apps for operational use. 

However, most business actions are initiated by collaboration between individuals. Integrating business intelligence systems with email, chat platforms, and other collaboration channels is an increasingly important requirement.

Your BI strategy must include effective communication and collaboration to drive action and decision-making based on analytics insights.

Develop a business intelligence roadmap

Your BI team should create a roadmap for implementing your strategy. Here are some things to consider:

  • Maintain milestones and dependencies on your data warehouse, such as when it will be completed
  • Maintain a forward-looking perspective and adapt your roadmap as necessary
  • Take a proactive rather than a reactive approach

Your BI roadmap should be flexible. Business intelligence works best when it is proactive. Determine when your BI platform will launch and when your data warehouse will be ready. 

Your business intelligence strategy cannot be optimized if it focuses solely on responding to ad hoc reporting requests. Whenever a new business is established, new initiatives are implemented, the market changes, or customer behavior changes, mark it on your roadmap.

Strategy implementation

You will need to work with your IT department on deploying the business intelligence platform as part of the overall strategy. Your IT department will likely have its ideas for implementing the tool. 

The BI team should use an agile or traditional project management plan with a built-in feedback loop to communicate their progress. Establish the reporting structure for the BI team before deploying. Where do they fit into the broader organizational structure? Decide who the BI team reports to and how these reports should be formatted. 

Finally, determine security permissions for the BI stakeholders with IT. You want stakeholders to be able to access and work with the data, but it is also important to ensure that the data is secure. Build a feedback loop into your implementation plan so that stakeholders, your BI team, and IT can provide each other with feedback as the project progresses. 


For BI infrastructure to be effective, it must be able to handle any type of data that can reach all corners of the organization. Among the steps to doing this are knocking down system silos, moving different data types into a single repository, and ensuring consistency and accuracy across all systems. 

You cannot achieve all of these things without a robust data architecture consisting of a variety of data marts, warehouses, and repositories that are all able to exchange data within your business intelligence system. 

Different BI software providers and consulting firms provide different levels of expertise in BI.

For those who are new to BI development process and BI strategies, it can be helpful to work with someone who has already walked the path.

Leave a Reply

Your email address will not be published. Required fields are marked *