How to Unlock the Potential of Business Intelligence Automation

How to Unlock the Potential of Business Intelligence Automation?

Estimated read time: 8 minutes

Are you interested in business intelligence automation and how it can unlock the true potential of your business intelligence activities?

In this article, we are going to discuss the same in detail. According to PR Newswire, the market for business intelligence will reach USD 2.787 billion in 2026. 

Moreover, integration with the latest Artificial Intelligence and data science technologies is expected to surge the demand for BI analytics tools. Let’s explore how automation in business intelligence is profiting business owners.

Why Invest in Business Intelligence Automation?

Business intelligence uses business data to make better-informed business decisions. Business intelligence has been a common concept for a long time now since excel spreadsheets were used to format and analyze data.

With the popularity of big data and technologies like IoT, businesses have gained access to a lot of information in real-time. Traditional BI systems are not enough to make sense of these huge data sets.

On the other hand, business owners want to find hidden insights in such data to formulate their future business strategies effectively.

For example, business intelligence software may tell about increased sales of a certain product but not efficiently alert you of the changing shopping behavior of customers. 

In other words, traditional BI dashboards show data analytics of set parameters and report on explicitly set metrics.

It is not possible to go through all these reports and figure out embedded data insights manually. The amount of data increases drastically with an increase in the number of users. Hiring a data scientist to manually perform data analysis is not a feasible choice.

Business intelligence automation provides the right solution to the problem of finding valuable insights from big data quickly.

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Business intelligence automation uses a combination of technologies to design and configure information technology processes to maximize business efficiency and profitability.

Some of the technologies used in business intelligence automation are,

  • Cognitive learning;
  • Intelligent document processing;
  • Natural language processing;
  • Machine learning and Deep learning;
  • Computer vision, etc.

These AI domain technologies help in building intelligent business process management software that not only streamlines the business processes, making them more efficient but also helps in performing tasks impossible for human beings to do manually.

The global market for BI solutions is rapidly growing with BFSI, IT, retail, healthcare, etc. being the key end-user industries. 

Next, let’s see how these businesses are unlocking the true potential of automated business intelligence.

How to Implement Business Intelligence Automation in Your Business?

According to a research study conducted by Harvard Business Review, 86% of business leaders consider extracting valuable insights from the company’s data important and 75% believe it is crucial to provide actionable insights to the employees.

It is clear that business owners want to implement business intelligence automation for effective decision-making and taking swift actions.

You can implement business intelligence automation in your organization and achieve its true potential in the following ways:

Improve your business data quality

According to Ted Friedman, a senior analyst at Gartner, poor data quality is a major crisis factor in the information technology sector that reduces business value and ultimately financial gains.

As the information becomes more complex, businesses and their customers face major data quality issues. According to Gartner, businesses lose $15 million every year to problems that arise due to poor business data quality.

For this reason, data analysts spend the majority of their time in data cleaning and formatting. Automated business intelligence tools can significantly reduce this time of improving data quality.

Software like Tableau has features that automatically gather, clean, and label data for their effective use in business processes. 

Similarly, robotic process automation (RPA) techniques help not only automatically collect data from multiple sources but also to format it as per requirement after passing through quality checks.

Moreover, RPA technology helps to avoid human errors that are more likely to happen in manual data entry and formatting. Data management tasks like repetitive data collection and synchronization are easily automated using RPA tools.

Hidden Insights Discovery

Artificial intelligence algorithms can be used to find embedded data trends in huge business data. Data scientists can provide them with logic, and AI-powered tools can go through thousands of data records instantly to find valuable information.

Today, businesses have to make quick decisions given the digital nature of the marketplace. AI helps to come up with effective strategies quickly based on the data available. 

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It is not humanly possible to go through data silos and forecast what your business users are thinking or how their consumption behavior may change in the coming time, but artificial intelligence can help you with such decision-making processes.

The advanced computing power available today facilitates AI to make good use of big data and provide businesses with valuable insights.

Analyze business data from any system

Business intelligence automation helps to connect with legacy systems that do not have application programming interfaces (APIs). Banking institutions, for example, still work with mainframes that lack APIs. 

RPA BI tools can help interface such legacy systems, virtual systems, etc. to gather information and format it in a way that analytical tools can understand for performing business data analysis.

Moreover, AI-powered BI tools can process unstructured data such as images, PDFs, emails, etc. All of this data is then compiled in a spreadsheet such as excel and passed on to the relevant departments for further analysis.

Take faster actions

Having all the required data at your disposal is one important thing. It helps you with efficient decision-making. Acting on these decisions swiftly to save time and money is also equally important.

Business intelligence automation tools cover this aspect of business efficiency too. BI dashboards with clickable features help to immediately take an action depending on the data report.

For example, in a supply chain scenario, as soon as your warehouse managers see a low-stock alert for a product, they can initiate a purchase order request through the BI platform.

Business Process Automation

Business process automation is rapidly being adopted by companies given the efficiency it introduces with the focus on cutting down unnecessary use of resources.

AI-powered business intelligence further strengthens the automation process where business workflows are made more streamlined. Availability of the right data in real-time helps to automate processes that have the potential to run independently without much human interference.

For low-risk use cases, you can automate the business process activities to take place when certain conditions are met. 

For instance, send emails to target business customers highlighted by the BI analytics software, generate automatic reminders for clearing invoices, make payments when terms and conditions are met, inspect a production area without leaving the office, etc.

Accessibility

BI automation not only gathers data from different data sources but also presents it in the form of reports and graphs. This helps in performing efficient data analysis. You won’t have to go through large excel sheets to look at the daily performance or weekly KPIs (key performance indicators).

You can automatically extract data, convert it into any user-friendly format like PDF, Microsoft PowerPoint, etc. and distribute it across communication channels.

Moreover, there is a record of any data changes made including, who made them and when. In this way, business data not only becomes easily accessible but there is also information transparency.

Remove Bias

Bias is an important issue when it comes to data. There is a huge chance of misinterpreting bias in data when handling it manually. This can also lead to wrong data insights which may lead business analysts to make wrong business decisions.

For example, bias in customer behavior data can be due to personal opinion, outdated information, wrong perception, etc. Artificial intelligence helps filter out such biased information and derives true trends from business data.

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Business intelligence tools powered by AI will help you gauge the real potential of business intelligence automation in your company. Some prominent BI tools used by businesses include, but are not limited to:

Tableau: A data analysis and visualization tool to help businesses make data-driven decisions. It offers multi-layer security and is available as a native mobile application for both, Android and iOS.

Read more on using Tableau for a data collection process from different sources in our blog here.

Power BI: By Microsoft, provides business data insights through features like data mining, data visualizations, reporting, etc. It provides a live 360-degree view of data and updates dashboards in real time. It features on-the-go access, secure insights, and collaboration across the organization.

Apache Spark: It is an open-source data analytics solution, usually used in distributed and rapid real-time data processing environments. It supports server programming languages including, Python, Scala, SQL, etc. It is popular for its fault tolerance and ease of use.

Oracle Analytics Cloud: This BI tool provides AI-powered data analytics and reporting features to businesses of all sizes. It is a cloud-based tool and uses conversational analytics to help non-technical users effectively interact with the data.

Conclusion

Business intelligence automation can make your business grow by making use of the business data available through growing digital transformation. It can help you streamline your business operations and provide you with information that can support you in devising better future strategies for your business.

Business intelligence automation will also assist your resources across the organization. Automated processes and actionable data insights will help them perform their jobs confidently. 

Moreover, automation of mundane and repetitive tasks will free them to take on more creative jobs that require analytical thinking. 

If you plan to avail all these benefits of business intelligence automation to increase your business profitability, you have made the right decision. 

Furthermore, if you are looking for experienced software developers to help you through the process, DevTeam.Space can help you. 

Get in touch with DevTeam.Space via this quick form mentioning your initial business intelligence automation requirements. One of our technical managers will respond to your request and connect you with software developers who are experts in BI automation solutions.

Top FAQs on Business Intelligence Automation

1. What is business intelligence automation?

Business intelligence automation uses technology to automate business information procedures from the collection, and formatting, to reporting. Such automated data collection and analysis helps in making better business decisions, benchmarking performance, monitoring important KPIs, etc.

2. What are some risks associated with business intelligence automation?

Data loss, data breach, business process failure, and loss of money and efforts are some risks business automation can face. These challenges with automating business intelligence tasks can arise due to complicated IT environments, complex business processes, unprecedented technological challenges, cyber security risks, inexperienced human involvement, etc. 

3. How can I implement business intelligence automation?

You can implement business intelligence automation in several ways across your organization. Some of these include intelligent automation of data gathering and formatting procedures, automated insights discovery, automated data visualization and reporting, etc.


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