“Business intelligence” is an incredibly popular buzzword this year, as businesses try to take advantage of big data analytics and make use of in-house data assets. But business intelligence is, in some ways, a broad and comprehensive heading for a number of different types of tools and processes.
There’s a lot involved in business intelligence. There are different areas of focus, and different types of tools, as well. Here are some of the categories of applications and resources that businesses acquire to handle and interpret business intelligence data.
Databases and Data Containers
One of the most fundamental types of business intelligence tools is the database table, and its use in modern database design.
A database table is essentially the most basic form of data container. It has various fields for a given record, where the business can build out a reliable and consistent positive data resource for groups of individual customers, products, processes or department records.
The spreadsheet, as a type of data container, is one of the earliest forms of business intelligence tool. It’s also extremely primitive in the context of today’s ERP software systems. Data can be held in a spreadsheet, but most companies use more sophisticated business intelligence tools to actually work with the data, and if it’s in a spreadsheet such as MS Excel, they extract it. The same is true of standardized databases – data often goes into and out of the database for specific analytical processes.
Data Mining Tools
Data mining tools can take data into and out of these containers and look for data from other sources. They are often designed to be proactive data aggregation resources and can acquire data from a variety of places within an IT architecture, including locations that planners might see as “silos” where data is walled off from the central data system.
The process of data mining basically gives companies the elements that they use in functional analytic systems. For example, a data mining tool may access two or more databases, or basic spreadsheets, or mailing lists or websites, to come up with data sets that will then be funneled into some other system. In a key sense, data mining takes raw data out of the field and refines it for use by other parts of business intelligence systems. This article goes over some of the ways that data mining supports business intelligence and what role data mining tools play.
Online Analytical Processing
Online analytical processing tools take data that’s considered ‘multidimensional,’ and carve it up into digestible segments. This multidimensional data may come from data mining tools, or it may already be in a normalized container. Either way, this type of online process is part of the reading or parsing of data that occurs for effective business intelligence use.
In some ways, OLAP tools enhance what can be done with traditional database technologies. OLAP systems like Cognos and Infor help companies to do bigger things with big data sets, through an online model.
Visual dashboards are one of the most universally visible business intelligence tools. They’re designed for the end-user. They’re something that an executive might think of when they think about business intelligence.
In a very real sense, visual dashboards present that data to the user in an understandable way. They’re the last-mile delivery system for business intelligence data. One of the best value propositions for business intelligence software companies is that these companies have developed tools that can take the mined and analyze data, and show it in a visual way that the human decision-maker can understand.
An easy example involves the use of geolocational data. If that data is in a spreadsheet, in rows and columns of numbers, it’s simply not available to human readers in a cognitive sense. They can’t look at the screen and see what they’re supposed to be looking at – because the brain isn’t built to process sets of numbers in that way.
By contrast, sophisticated business intelligence dashboards use algorithms to show this data by color and location, or with sophisticated graphs, charts or clusters. This makes the data instantly understandable to the human viewer, and it’s one of the biggest benefits of having a dedicated business intelligence software system at the firm’s disposal.
When it’s not necessary to have visualized data, reporting tools will do the trick. Many of these business intelligence reporting tools are tied to a greater business intelligence system, and are offered by major software companies that also offer other sorts of tools like salesforce automation, customer relationship management and more.
A lot of work goes into the specific functionality, data gathering and presentation of reports. This includes features for compiling and ordering data points, and features that allow users to build customized reports with precise metrics. Other features involve data security, tech support and other assistive aspects of report tools.
Local or geographic information systems in BI are made to utilize geolocational information for BI purposes. These tools, which may work in conjunction with GIS tools, will typically be built for observational capability, and support for raw or unstructured data.
The use of local information systems ties back into the use of visual dashboards and mined data. All of these aspects of business intelligence systems work together to provide results for clients. Look for these types of tools and functions in enterprise business intelligence vendor options when shopping for a solution for a company.