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Risks and Benefits of Business Intelligence Automation

Since businesses have gone digital, not just with marketing but also through systems analysis, Business Intelligence (BI) automation has become the next buzzworthy word. But what exactly do we know about it?

What are the risks and benefits of shifting towards this new movement in business tech? Let’s discuss these important points today and read through them to see if the benefits outweigh the risks.

What is Business Intelligence Automation?

In the simplest way possible, Business Intelligence (BI) uses automation tools and artificial intelligence for you to better assess raw data and information towards actionable and purposeful insights.

This big umbrella covers tools, visualization, mining, infrastructure, and analytics, among others. Automation comes into play to enable you to access comprehensive summaries essential for making decisions based on data.

All in all, Business Intelligence Automation is essential to anyone who might just be starting a business or is thinking of finally going digital.

Business Intelligence Benefits

To name a few general benefits of BI Automation, these can include:

  • Efficiency in data analysis
  • Discovery of new insights
  • Enables ranking of insights based on priority and/or significance
  • Easy accessibility to data
  • Simplifies data for better understanding
  • Real-time feedback from customers
  • Automation of possible responses to customers
  • Reads behavior and patterns of customers for better actionable decisions

However, some more detailed benefits can be found from utilizing business intelligence automation that are unique to this system.

Data Quality Improvement

Because business intelligence automation empowers the data-driven person most crucial to make decisions, you make the most out of the kind of data that has been gathered. Through BI automation, you can embed insights directly into platforms that customers regularly use.

More so, you can also extract biases through AI, thus reducing the possible human error margin.

Subsequently, through BI automation, data collection, alongside filtering and repairing, can become significantly more accessible, thus, saving you time from hiring and working with analysts to do the same task.

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Analyze Data from Any System

The most convenient and powerful benefit of automated business intelligence is allowing your customers to be a click away from expert help within the BI platform, which is an extension of support and a decision-making system.

With this, no one is required to be a data scientist to address and make wise decisions.

Drawing out data for analysis is a tedious task that usually resorts to manual work. However, with advanced business automation intelligence, such as robotic processes, you can widen the reach of the data that BI and other tools for analytics into any system–even those that don’t have an application programming interface (API) yet.

Automation in BI is beneficial for gathering and analyzing information and collecting data from a specific website to be translated into a particular format for analytics tools to be used.

BI Data in IT Process and Business Automation

As bigger groups start looking into and are now welcoming analytics alongside data science to gain more insights to make smarter decisions, BI does the work of leading you to better choices through the advancement of the flow of work in the business.

Through robotic process automation (RPA), extracting data becomes an easy, seamless task that no longer requires manual work. This is convenient even in cases such as reaching payment terms.

The RPA can set reminders and even escalate concerns based on information automatically downloaded from BI reports to ascertain that necessary payments are made within the terms signed.

In IT, tracking reports can also be quickly done through the RPA of a BI automation. This can include tracking IT asset owners and stats on utilization.

The RPA can also conduct IT maintenance and management of IT assets. This simplifies tedious work, such as patching critical servers. Additionally, it can adjust the necessary IT resources based on on-demand analytics and do so in real time.

Risks of Business Intelligence Automation

As BI Automation remains a new advancement and is still being studied, there may be more to what we know now about BI automation’s risks. However, we’ve narrowed down a general list of these risks.

Failure of Business Process

Transitioning your BI towards automation and working with machines can be an avenue to become more efficient and productive.

However, this is not necessarily guaranteed. Because this shift involved multiple and complex technologies, this might pose challenges in managing information.

More so, because this advancement works in real-time, there is timeliness required to address such problems lest it results in a business process failure.

Indeed, intelligent automation speeds up the process and makes work more efficient, but this does not assure the same result every time. It is important to note that a sophisticated business process strongly depends on predictable data.

This requires when, where, and how data is being delivered. If there are interruptions or changes in the data delivery, you might encounter a break in the downstream process.

With timely action, this problem can be addressed. A robust design and change management program is required to prevent this. This entails carefully planning and mapping the process flow before launching to automation.

Loss of Data

BI automation has dramatically changed the speed and volume of data collection. However, because this entire process is still banked on a machine, certain minor interruptions can create big problems–even as small as someone resetting a password.

A problem like this can hinder you from accessing data and make you lose access to data permanently or be challenging to retrieve.

However, this problem can still be prevented by simply creating a process that quickly alerts with every process and performance problem.

Data Breach into Your Intelligent System

BI automation works through a combination of intelligence technologies. However, since most of these technologies are software, they can be vulnerable to cybercrimes.

Leaking data is a high risk as it can expose data to cybercriminals as simple as you add a new application.

A bot created can also be a new software application. This changes how you view data extracted–be it stored or temporary.

Thus, implementing robust information security is the most significant responsibility you can take to prevent this.

All Your Efforts and Money Wasted

Automating BI is an investment. This means you will spend time and money to make it work and launch it well. However, this can all go to waste with a simple vendor update.

Because of this, you need to research and scout, consult, and read up on all possible vendors involved in your project before you consider which product release, beta programs, and roadmaps to take on as you build your ecosystem.

Additionally, with all this machine work underway, you can never go wrong with human consultation. Talk to people who have been in the industry for a long time and even firms outside who will care about your organizational growth.

Conclusion

Business Intelligence, the Automation process, and data analytics are proven efficient for data collection, automation of recurring tasks, creating appealing data visualization, and synthesizing meaningful insights extracted from data.

Additionally, the COVID pandemic has significantly increased pushing towards automation to lessen menial tasks delivered by humans when more incredible tasks can be done with our minds.

Mike Austin

Guest Author

Mike Austin is a Content Director at Adrack.com. He has worked in the Digital Marketing industry since 2009. As a conversion-driven marketer, he is passionate about helping businesses expand their online visibility and reach their goals.

The information and views set out in this publication are those of the author(s) and do not necessarily reflect the official opinion of Magnimetrics. Neither Magnimetrics nor any person acting on their behalf may be held responsible for the use which may be made of the information contained herein. The information in this article is for educational purposes only and should not be treated as professional advice. Magnimetrics and the author of this publication accept no responsibility for any damages or losses sustained as a result of using the information presented in the publication. Some of the content shared above may have been written with the assistance of generative AI. We ask the author(s) to review, fact-check, and correct any generated text. Authors submitting content on Magnimetrics retain their copyright over said content and are responsible for obtaining appropriate licenses for using any copyrighted materials.

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