How to Develop an Effective Business Intelligence Strategy?

Business-intelligence

A decade ago, autonomous cars, delivery drones, or cancer prediction seemed impossible. But not anymore. We can now create computer algorithms that mimic human-like thinking and learning thanks to artificial intelligence software development.

Business intelligence (BI) is one area that is expected to grow exponentially in the future. Data lies at the heart of BI and AI, which is why they are frequently seen in the same context. But how these technologies function and their value to the business differ significantly.

BI Vs. AI

BI offers knowledge of prior performance. In other words, BI uses data to provide organizations with insights in the form of graphs, dashboards, reports, summaries, and maps to support decision-making.

Unlike BI, AI can empower computers to make business choices independently. Chatbots, for example, may answer client inquiries without human participation. While AI forecasts future patterns and the most effective course of action, BI delivers comprehensible insight into past performance.

BI and AI are better together

Every business today generates an enormous amount of data. BI can help businesses organize this data and drive meaningful insights using beautiful dashboards and visualizations. Though, insights might not always be enough, as in the case of risk management, where insights should always lead to decisive actions. 

While BI leaves decisions making primarily to humans; AI can step in and further automate the decision-making process and eliminate undesirable bias or human errors. 

To summarize, AI and BI no doubt work well independently, but together they can be genuinely transformational. By embracing the convergence of AI and BI, businesses can transform vast amounts of data into their most important asset. 

The Perfect Business Intelligence Strategy

The business environment is very competitive these days. To succeed, a business must innovate at a pace. This innovation doesn’t have to be tangible all the time. Businesses can innovate their customer service, marketing approach, or internal processes and workflows. 

Data can help businesses to innovate at a rapid pace. However, data in itself is not at all valuable. It must be gathered, cleaned, analyzed, and visualized to make a substantial impact. In short, every business today needs a BI strategy. 

In layman’s terms, Business Intelligence is about identifying a problem and then using all the data resources you have to find information or insight to help solve that problem. In short, business intelligence is about using data to make effective business decisions.

Hence it becomes crucial to implement an effective strategy with data at its core. But most businesses do not know the essential steps for a successful BI journey. We are here to help you with all the information you need to build an effective BI strategy. 

How to Develop a BI Strategy

Any business intelligence strategy has four core elements:

  • Vision
  • Processes and people
  • Data Architecture and tools

Any effective BI strategy should revolve around these elements. Here are the steps you should follow.

1. Create a BI vision

Start with a clear and concise vision. Identify key business areas that data analytics can help improve. Be realistic and practical in setting expectations. To do so, find clear answers to the following: 

  • The different data sources and the volume of data you will need.
  • The resources at your disposal to implement the BI plan.
  • The KPIs you will target and monitor during the BI lifecycle.
  • The BI tools you will use.
  • The BI lifecycle management. 

2. Assemble a BI team

You will need a team of data engineers, analysts, visualization experts, and project managers to realize your BI goals. You may even have to hire experts in data collection, cleansing, analysis, engineering, and visualization. 

Hiring BI experts is never a hurdle for large organizations. But, if you run a small business with a tight budget, you should consider outsourcing to an artificial intelligence development company.

If you intend to build an in-house team, take into account the following leadership positions:

  • BI Project Manager – For successfully managing project timeline and stakeholder expectations. 
  • BI architect – For creating the proper data pipelines that meet every end-user concern.
  • BI analyst – To leverage data and discover patterns, identify potential problems, and provide solutions.
  • ETL developer – For extracting company data and transferring it into the new warehousing environment.
  • Data visualization analyst – To transform insights into a visual form(charts, graphs, animations) that is easy to interpret and understand for other teams and stakeholders.

3. Establish your BI architecture

During this stage, you will create the framework for your organization to run business intelligence and analytics applications. You need to define the data sources that need to be integrated and the type and architecture of the data warehouse. Depending on your needs, you can choose from one-tier, two-tier, and three-tier data architecture.

Each of this architecture has its pros and cons. However, it would be best to choose by evaluating factors such as security, privacy, and budget. 

4. Choose the best BI vendor

There are several choices available when it comes to BI vendors. Before choosing one, there are a few factors to keep in mind. Many functionalities offered by specific BI solutions may never even be used. Others offer pre-built solutions, which might not be the best option for specific business needs.

Another element that needs to be taken into account is the cost. Even though purchasing pre-made BI tools may be less expensive, the subscription model (which excludes maintenance) may cost you significantly more in the long run.

Selecting a BI vendor is indeed hard work. Here’s a list of questions to ease some of the load: 

  • Is the tool easy to use?
  • Will your internal staff require a lot of training?
  • Is the tool compatible with your existing infrastructure?
  • What are the deployment options- cloud, on-premise, or hybrid?
  • On-premise is excellent if your priority is data privacy and security.
  • The cloud environment is ideal if you don’t want expenditures on hardware and infrastructure purchases. 
  • A hybrid environment is an excellent option if you want the best of both worlds. You can store business-critical data on-premise and the rest of the data in the cloud.
  • Is the BI solution easily scalable?
  • Are the dashboards customizable?
  • Can you set data privileges based on job roles?

5. Evaluate the governance framework

The BI tool you opt will be used by multiple stakeholders, managers, team leads, and more. Controlling which BI users have access to what types of data become crucial. You should be able to allocate or renounce permissions in a business intelligence software to manage who may view and update your BI framework.

You may define permissions based on your requirements and control how your teams can access and edit critical business data at a much more detailed level with custom BI solutions. Hire an artificial intelligence development company for customized BI solutions that effortlessly meet all your demands and expectations.

6. Build a BI roadmap

A business intelligence roadmap is a graphic representation of the timeline’s milestones, deliverables, and dates for scheduled operations. The roadmap should include technical information and appeal to end users.

Standard reporting should not be the only function of a BI application. The objective is to assist businesses in exploring their data and discovering insightful information to aid decision-making. Some of the essential features that a BI tool must have are:

  1. The ability to connect to and extract data from various data sources.
  2. The capacity to use a wide range of charts to show data.
  3. Make it easy for people to explore and analyze data swiftly.
  4. The ability to drill down and assist people in learning more about the issue and potential solutions.
  5. The capacity to use predictive analysis.

Conclusion

Being data-driven is no longer an option for 21st-century business. It’s a necessity. Transform your data with a business intelligence approach to support efficient, quick decision-making and boost revenue. Follow the step-by-step BI plan and let data drive your business growth and innovation.

Of course, each business has unique requirements. When it comes to BI, there is no one-size-fits-all approach. Explore companies in the market and select the leading Business Intelligence (BI) and artificial intelligence software development company for comprehensive business intelligence reporting, visualization & implementation services.

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