As the internet is used by companies to discern and target potential consumer trends, the desire to collect vast amounts of data has grown exponentially. Making sense and use of the data collected requires a system for collecting, storing and analyzing it.
If you're old enough to remember, or have seen the original "Star Trek" series, you may recall that Captain Kirk and others could merely ask a computer a question, and the computer, after some blinking of lights and strange beeps, would deliver an answer either by voice or print-out.
With Business Intelligence software, an employee at a desk with a computer merely needs to type in a query, and within a much shorter time and without the strange beeps, an answer is displayed.
What Is Business Intelligence?
Business Intelligence, or BI, is the term given software applications that change raw data into meaningful and useful information to help businesses make better decisions. The term Business Intelligence actually came into use around the 1950s. It grew out of early computing technology called 'decision support systems.'
Business Intelligence systems have grown more powerful since then, due to increased data collection and greater storage capacity, and the burgeoning use of smartphones and wearable devices that all help in data collection.
In the 1950s, companies didn't have access to smartphone metadata, internet usage records, social media activity, or "smart home" assistants like Alexa and Echo.
How Does Business Intelligence Work?
The main purpose of Business Intelligence platforms is to sift through data to find patterns and trends.
There are usually four components to BI software:
the reports from which can influence company direction, product line ups and even hiring decisions;
which is the analysis of large sets of data to find patterns and correlations;
Text analytics software,
which sifts through unstructured textual data to find patterns and is used to analyze sentiment in social media posts or online customer feedback, and
, which has its own three main forms:
- Descriptive, which describes data you already have, to look to identify trends and relationships inside of it, like page views, and even sales numbers within a specific department.
- Predictive, which searches for a correlation between a single unit or factor, and the features pertaining to it to find some correlation between different sets of data. This allows companies using it to predict future patterns from past trends, and is according to experts the fastest growing form of analytics.
- And decision analytics, which helps companies make decisions by analyzing not only past data, and extracts trends, but also looks at future conditions such as manufacturing trends, or what the market it going to be like in a few years. Decision analytics even makes predictions on shortages of resources, to help map out the safest course for a company to take over a number of years.
The main way to make use of all the info available is "data visualization," which also is growing sub-field in Business Intelligence. Data visualization is the graphic display of results of your data mining efforts, or analytics, and can update in real time.
There are three main types of data used in Business Intelligence functions:
- Structured, which resides in a fixed form, is labeled, such as with a name and other information collection boxes on websites, or address fields for shipping information, has a header, and can be put into a database program like Excel, and you can query it or search it with a computer, so it can be analyzed.
- Semi-Structured, which has elements of both structured and unstructured data.
- Unstructured, which has information that can't be easily read by computers, and is difficult to organized in traditional databases, because it can't be stored or collated in rows or columns. This is the most common form of data found on the internet.
Data usually resides across different systems, such as CRM programs, marketing automation systems, customer information - such as consumer sentiment - or reviews in social media platforms.
The first step in BI is to take inventory of data your company already produces, and figure out how you can analyze it and how you can cross-reference them.
The more often data is extracted and analyzed, the more up-to-date analytics reports from the data will be.
A method of collecting open-source software utilities to facilitate use of a network of many computers to solve problems that involve massive amounts of data, Apache's Hadoop, is used with Business Intelligence by large customers such as Facebook (FB) - Get Report , which customizes it, and Ebay (EBAY) - Get Report .
Why Is Business Intelligence Important?
- Lowe's (LOW) - Get Report , America's second-largest home improvement store chain, uses BI to optimize its supply chain efficiency and cut down on the rate of fraudulent returns in its store.
- Starbucks (SBUX) - Get Report , through its Loyalty Card Program, has amassed individualized purchase data on millions of customers, and uses BI to predict purchases or offers a customer might be interested in.
- Amazon (AMZN) - Get Reportuses BI to personalize product recommendations and market products. Ever wonder how Amazon is able to offer items "you might be interested in"? Amazon (AMZN) - Get Report uses its BI software for logistical business decisions, too, enabling its massive supply chain to run smoothly, optimizing shipping routes and allocating inventory.
Business Intelligence Trends
The trends in BI seen most important in a survey of 2,679 users, consultants and vendors by BI-Survey.com were master data and data quality management, data discovery, and self-service BI.
According to the survey, "While master data and data quality management builds a strong foundation for handling data, the significance attached to data discovery and self-service BI shows that the empowerment of business users is a consistently strong trend."
The same survey also found that agile BI development and advanced analytics and analytics teams are increasing in importance; agile BI development is connected to a cooperative approach between lines of business and IT, while advanced analytics expresses the need for businesses to use data in a more beneficial way. Advanced analytics also includes machine learning, tightly interconnected to the sphere of artificial intelligence, the survey said.
Meanwhile, real-time analytics and mobile BI appear to be decreasing in importance, the survey discovered. Either current tools and systems aren't able to provide these kinds of applications, or priorities have changed, the survey suggested.
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