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Pyramid Analytics has been recognized as a Visionary [Access the Report.](https://www.pyramidanalytics.com/gartner-magic-quadrant-2023/)

Business Intelligence

What is business intelligence?

Business intelligence (BI) is a process that turns data into insights to help organizations make better business decisions. BI as a practice has existed for decades, but it has evolved to become more sophisticated and effective with the emergence and evolution of analytics technologies. Today, BI is a key part of most enterprise organizations’ decision-making processes.

Industry analysts often group BI with analytics technologies under the category “analytics and business intelligence (ABI),” which Gartner describes as “an umbrella term that includes the applications, infrastructure and tools, and best practices that enable access to and analysis of information to improve and optimize decisions and performance.” Although many in the professional world associate BI with analytics technologies, business intelligence as a process has no specific prerequisites in terms of any analytics technologies it employs.

How does it work?

BI processes involve collecting and storing business data, analyzing that data to extract insights and business value, and communicating those insights to stakeholders. Most modern instances of BI rely on the limited expertise of professionally trained data scientists, data stewards, and other technical experts to manage large amounts of enterprise data, cultivate insights from that data, then deliver those insights in curated formats to the business stakeholders who need them.

In more evolved cases, business intelligence has become more accessible and democratic, enabling non-technical users to bypass technical teams and capture insights from data themselves. Known as decision intelligence (DI), this democratization of data access can support users’ individual decisions in more practical and agile ways. New decision intelligence technologies provide business users access insights via purpose-built, strategically governed, “low-code” or “no-code” self-service environments.

Types of analytics within BI

As indicated, BI is a process with no specific prerequisites for analytics technologies. However, each instance of BI is characterized by one or several types of analytics, each with different levels of sophistication. These include:

  • Descriptive analytics: Descriptive analytics involves examining historical data to understand business trends. Descriptive analytics helps users understand past business performance, such as how organizations deliver on specific KPIs over time.
  • Predictive analytics: Predictive analytics involves identifying patterns in business data and then using those patterns to predict future events, such as emerging challenges or growth. This type of analytics is often used in business forecasting and risk management.
  • Prescriptive analytics: Prescriptive analytics involves examining business data, then determining the best actions in the future based on insights from that data. For example, the BI function within an organization may recommend specific production volumes based on insights from market data. This type of analytics is often used to streamline decisions that will optimize business performance.

As business intelligence continues to evolve, we can expect more sophisticated and effective types of business analytics to emerge. Decision intelligence, for example, can use technology to make traditional BI more powerful and more accessible, and personalized for business use rs.

What are the benefits of BI?

Business intelligence is agnostic regarding the types of data and data sources it employs to deliver insights to business users. Organizations, therefore, can use BI to drive insights within any number of business capacities. Some common business benefits that emerge from modern BI processes include:

  • Enhanced operational efficiency: BI can help business users identify inefficiencies within their business processes by monitoring business data and identifying business trends. This can lead to more streamlined business operations that are more productive and cost-effective.
  • Better customer engagement: Organizations can leverage BI to gain deeper insights into customer preferences. Business users can better understand what their customers want and deliver personalized experiences that keep customers engaged and satisfied.
  • Workforce optimization: BI functions can help HR teams analyze productivity and other workforce data, helping them make more informed business decisions about hiring and workforce optimization.
  • Increased business agility: BI helps business leaders quickly identify business opportunities and respond to market changes flexibly. Organizations can stay ahead of their competition and adapt to business challenges or disruptions more quickly and effectively.

As business intelligence and analytics technologies evolve, we are likely to see even more benefits emerge. This is especially true within instances of decision intelligence, where any business users with access can innovate and discover new applications for BI capabilities.

How can our organization evolve from BI to DI?

Organizational leaders worldwide already use traditional analytics technologies to automate key processes and enhance business decision-making as part of their BI processes. As these technologies become more sophisticated, business leaders interested in adopting them must consider several factors before they begin. Essential questions include:

  • What are my business goals associated with new analytics technology adoption?
  • Who within my organization should have access to analytics tools?
  • What business data will I use to derive business insights from this technology?
  • How can I ensure the security of my data as I provide users with access?
  • How can I enable more people to embrace data to make decisions?
  • How can I reduce TCO by reducing the number of tools?

By examining these questions, organizational leaders can develop successful analytics technology adoption strategies that support competitive BI capabilities. As technologies increasingly support democratized data access, business leaders may find technologies that support decision intelligence are the most competitive, forward-looking investments.

How can Pyramid Analytics help?

Pyramid Analytics supports leading decision intelligence processes with its unique DI platform, purpose-built for dynamic and competitive business environments. Organizations worldwide use our DI tools to democratize user data access in a governed way, driving deeper insights and better decision-making across their organizations.

Contact us today to learn more about how we can help your organization.