- #BUSINESS INTELLIGENCE APPLICATION DEFINITION MANUAL#
- #BUSINESS INTELLIGENCE APPLICATION DEFINITION SERIES#
Here we start to see the increasing role of high-performance computers, rather than only human capabilities.
Massive quantity and variety of data can lead to an unlimited number of hypotheses to test and can even allow you to process data without having any hypothesis in place to discover new intelligence on the fly. Recently, those needs have started to be addressed with cloud solutions and provision of those assets as XaaS (Everything as a service, let X be Infrastructure, computing platform, etc.) which optimize the cost of ownership and allows for virtually unlimited capacity. When you have a huge volume of data, you need to have effective storage management (online, nearline, offline, etc.) and massive processing power for the exponentially growing calculation load. Having copious data in many different formats such as database, semi-structured, voice, video can cause some unforeseen problems.
#BUSINESS INTELLIGENCE APPLICATION DEFINITION SERIES#
As an example, World Bank Open Data provides 3,000 datasets and 14,000 indicators encompassing microdata, time series statistics, and geospatial data.Ĭheck Out: Top Business Intelligence Companies In EuropeīI has the potential to say a lot, but leadership may not be ready to absorb all this information at onceĬurrent technological developments, both internal and external, mean that organizations can now access enough data to create intelligence in a practical way. Now it is possible to collect real-time data from numerous devices, internal and external websites, curated libraries of government, market and generic data in addition to the traditional line of business applications. The introduction of recent technologies and sources such as the Internet of Things (IoT), Web click tracking, and Open Data sources have simplified the data collection process and satisfied the need for massive volume.
#BUSINESS INTELLIGENCE APPLICATION DEFINITION MANUAL#
Until recent decades, data had predominantly been generated internally through manual effort and has come with a significant associated cost.
Driven with this motivation, BI experts are striving to gather as much data as possible, ideally providing the highest level of granularity. my fridge capacity is three apples so available capacity is one apple, therefore don’t buy more than one apple at the marketĪs the simple example above shows, the more data we have, the more intelligence we can generate. my average daily consumption is one apple, so plan to go to market in two days For example, a single data point indicating that I have two apples is not enough to provide any useful or actionable information, but when I have the second data point everything changes: If we start with one single unique data point, it is not enough to create any intelligence at least two data points are necessary to reach a conclusion. This combination of science and design skills makes BI attractive to creative employees, as well as adding value to the business. BI comes to life with several names such as real-time reporting, online analytical processing, predictive analytics, and data mining.Īlthough the rapid and versatile development of tools has stressed the science side of the process, human aspects such as message selection, presentation of options like colors or icons reflect the design side. Kudret Soyturk, Head of Business Data Intelligence, Atos īusiness Intelligence (BI) is the process of converting data into useful, actionable information for decision-makers in business situations.