Business intelligence technologies, such as data mining, text analytics, cloud data services, web analytics, predictive technologies, and near real-time monitoring, help companies collect and analyze data faster and more efficiently to make informed decisions. These technologies are beneficial for various industries, including finance, healthcare, manufacturing, retail, telecommunications, transportation, and utilities.
Business intelligence technologies – or BI technologies – are an essential part of doing business in today’s world. Known as decision support technologies, their main goal is to allow companies to collect data faster and more concisely, enabling crucial decisions to be made. This quest for speed and efficiency has become the catalyst for the creation of new and improved types of BI technologies, including data mining and text analytics, cloud data services, web analytics, predictive technologies, and near real-time monitoring. . These technologies help ensure that companies have the ability to acquire and store massive amounts of data, proactively analyze their data, and deliver personalized products and services to customers.
Data mining represents a form of business intelligence research. This version of BI technology helps business owners perform comprehensive data analysis, leading to predictive models that can better highlight specific future trends. Text analytics allows companies to extract key phrases from responses to survey questions. These responses help companies categorize and analyze the results to structure future actions.
Other types of business intelligence technologies are cloud data services and web analytics. Cloud data services refer to using the Internet as a virtual office space to share files and data publicly or privately. Storing and analyzing data in the cloud allows for greater capacity and computing power than some companies offer in-house. Web analytics consider data about visitor behavior on a company’s website, such as time spent on the homepage, click-through rate to additional pages, and purchase frequency.
Basic business intelligence focuses on data regarding the volume of products or services sold, customer demographics, and profit margins. This data collection allows companies to create forecasts for future business trends. Predictive technology, however, offers an enhanced version combining basic data from BI, data mining and statistical analysis. The result is predictive analytics, a more complex form of BI technologies that ventures beyond the “guesses” typically based on general predictions.
Predictive analytics provide more concrete predictions based on statistics and specific outcomes. For example, forecasting in general business intelligence technologies can inform a company that sells sportswear that a particular season accounts for the highest sales volume, based on past experience. The crucial difference with predictive analytics is that the data would indicate customer characteristics and behaviors, their specific clothing choices, and the type of marketing that would appeal to most of them.
Near real-time monitoring is one of the most significant types of business intelligence technologies and is aimed at closing the gap between data acquisition and data analysis. An example of near real-time monitoring includes using transport ticket data to match passengers with the most appropriate flight, bus or train. Another example is using emergency patient data to trigger essential care faster from applicable medical personnel.
Any business owner, executive or manager who wants greater success in their company should consider incorporating business intelligence technologies to improve the quality and efficiency of the business. BI technology enables people to make faster, more informed decisions based on highly accurate statistics. Companies that can benefit from BI technologies include financial services, healthcare, manufacturing, retail, telecommunications, transportation, and utilities.
Asset Smart.
Protect your devices with Threat Protection by NordVPN
