Even before the boom of big data and analytics, most businesses still could use intelligent methods to monitor and analyze their performance. These techniques are just as relevant today but united under the umbrella term business intelligence, encompassing everything from data mining and visualization to predictive modeling and advanced statistical analysis. If you’re unsure you understand business intelligence and how it can help your company, read on to learn more about it. We will explain business intelligence and look in more detail at some specific business intelligence techniques you can implement in your organization.
Read on to learn more about strategic business intelligence techniques:
What Is Business Intelligence?
Business intelligence is the art of turning raw data into information you can use to make strategic business decisions. When used correctly, BI can give you a detailed overview of your organization’s performance at every level. It includes everything from sales figures and financial projections to customer satisfaction surveys and marketing campaign results. Thus, BI is the foundation for all data-driven decision-making. It helps make sense of business data, so it’s incredibly significant for any company that wants to thrive in the modern era of data-driven business.
Business intelligence — often abbreviated as BI — is also sometimes referred to as decision support or executive reporting. No matter what you call it, BI aims to transform raw data into actionable insights for decision-makers. This data can come from almost any source, including transactional systems, social media, and IoT devices.
Why is Business Intelligence Important?
First and foremost, BI allows you to make more informed decisions by providing you with the most accurate data possible. It helps you cut down on the reliance on gut feelings and intuition. Instead, it gives you the power to find out what’s happening in your organization. And that’s incredibly important, especially in today’s business world.
Companies often rely on assumptions to make big decisions. While this method might have gotten by in the past, it’s simply unsuitable for the modern era. With the abundance of data available to us, it’s now more important than ever to be data-driven. No matter what industry you’re in, you are more than likely to have access to data that can inform your business decisions. At this point, you might lack the tools to turn this data into useful information. That’s where business intelligence techniques come into the scene.
Types of Business Intelligence Techniques
Business intelligence techniques fall into three categories: data mining, data warehousing, and data visualization.
Data mining is digging through a company’s data to find necessary information, like insights into customer demographics or operational errors.
Data warehousing means collecting raw data and storing it in a centralized database.
Data visualization implies turning collected data into graphs and charts that are easy to understand.
Here’s a closer look at each of these business intelligence techniques.
Data mining is the process of extracting valuable insights from raw data. It’s a common technique in business intelligence, particularly when extracting insights from transactional data. Data mining can help you understand different aspects of your business: from customer demographics to product sales to employee performance. If you work in a field that relies on transactional data, like retail, finance, healthcare, or hospitality, data mining is a particularly suitable business intelligence technique. It can help spot operational errors and customer service issues that might have gone unnoticed and identify purchase trends and patterns.
Data warehousing is a technique that collects raw data from various sources, including sensors and IoT devices, and stores it in a centralized database. This database will usually be structured around a predefined schema that allows you to query the data in various ways to reveal necessary information.
Companies that collect a lot of data might be using data warehousing. They include everything from social media networks to internet service providers. Data warehouses are usually expansive and scalable, allowing organizations to collect as much data as possible. The main purpose of data warehouses is to keep the data ready for further analysis and extraction of insights, like customer demographics and purchase trends.
Data visualization usually implies transforming data into graphs and charts that are easier to understand. This business intelligence technique makes raw data more accessible for non-technical users.
Data visualization can help reveal insights about almost any topic, from product sales to employee performance. When used correctly, data visualization can transform complex and confusing data into information that’s easy to digest. It can be especially helpful for management and executives, who may be overwhelmed by the sheer amount of data available.
Predictive analytics is an advanced statistical analysis that allows you to make predictions based on past data. This technique is common in marketing, where you can use predictive analytics to identify potential customers based on their behavior and demographics. Besides, it’s used in insurance and health care. Predictive analytics is helpful for any organization that wants to maximize its marketing potential — create targeted marketing campaigns and personalized offers, identify potential risks and minimize the likelihood of them occurring.
Advanced Statistical Analysis
Advanced statistical analysis is a business intelligence technique that uses complex mathematical formulas to discover patterns in data. Advanced statistical analysis is best used in conjunction with other business intelligence techniques. It allows you to delve deeper into your data to discover new patterns and connections that you might not have noticed otherwise.
Business intelligence is crucial for turning raw data into useful information that you can use to make strategic business decisions. Any company that wants to thrive in the modern era of data-driven business can profit from it. Business intelligence helps discover insights about almost any topic, from product sales to customer demographics. The only limit is your imagination.