Business Intelligence Vocabulary You Must Understand

The significant leap in information technology development we have been witnessing since the last couple of years has resulted in the increased popularity of business intelligence solutions. Companies constantly look for tools that would help them leverage the potential of large volumes of data gathered in heaps by any business. Turning to business intelligence is no longer a novelty in the business world but rather a necessity. In other words, nowadays everyone should get to grips with business intelligence, even if it is only to be able to choose the best self-service business intelligence tool without the need to ask an IT expert for help. We prepared a list of business intelligence vocabulary that we hope will enlighten you and turn the struggle through various BI-specific issues into a pleasant walk.

Analytics

We chose analytics as the first position of our dictionary of business intelligence vocabulary not only because it starts with ‘a’ and looks good in the front. Efficient business analytics is by far the most significant one out of multiple reasons why you need a true self-service BI tool. In the age of Big Data, traditional Excel spreadsheets don’t fulfill the criteria of a comprehensive data analysis. For example, juxtaposing unstructured data from different format databases and then visualizing it on an interactive chart lies far beyond Excel’s capabilities, but is bread and butter for most BI software. Advanced software-based analytics using algorithms helps to arrive at insights that were unreachable before which introduces business decision-making to the new data-driven era.

Big Data

It’s one of the business intelligence buzzwords mentioned everywhere, be it in data analytics, data science or digital automation; so we also couldn’t omit it in our business intelligence vocabulary list. Big data is characterized not only by its big volume, but also by its variety – it includes many different types of data, for example financial transactions, credit card payments, social media uploads, sensor data, video capture, voice recordings etc. The use of big data is complicated further by its velocity, the speed at which new data is generated, and veracity, meaning the biases, noise and abnormality in data that create all that data mess that business intelligence must clean up.

Biometrics

Biometrics generally refers to the study of measurable biological characteristics. In computer security, biometrics refers to authentication techniques that involve measuring physical characteristics of humans that can be automatically checked to prove a person’s identity. By scanning our facial features, irises, retinas, fingerprints, hand geometry, patterns of veins on the back of our hands and recording our voices, different devices are able to identify us with 100% certainty. If this seems a bit far-fetched to you, think about Facebook photo tagging suggestions. Yes, face recognition software is already in use.

Cloud

Cloud is a term that reaches far beyond business intelligence vocabulary. It is an Internet solution we use every day. When you upload your documents, photos or videos to Facebook, LinkedIn, Twitter or Instagram, you hand in your files to those providers to be stored on their servers. If you store your documents and photos online using services such as Dropbox or Google Drive you also send them to the cloud – meaning to an external server. Cloud technology is widely used by businesses as it increases storage capacity without the need to buy new hardware. Cloud computing also makes it possible to analyze the notorious big data – the unlimited capacity of the cloud enables first the storage of all the data and then analyzing it with many computers connected via a network.

Dashboard

A business intelligence dashboard is a visual presentation of organization's well-being. It’s a method of visualizing data with different types of charts and graphs to help users better understand data and draw valuable business insights. By monitoring Key Performance Indicators (KPIs) on KPI dashboards companies can conduct detailed analyses of team and individual performance, refine their business strategies or perform “what-if” analyses to forecast future business processes. There are many vendors of online dashboard software out there that offer tools which will empower you to analyze and present your data in the form of colorful charts created via user-friendly interfaces and with no programming skills required.

Data Mining

Data mining combines the powers of Artificial Intelligence, mathematics and statistics methods to analyze large volumes of historical data with the purpose of identifying patterns and systematic relationships between variables, and then applying the detected patterns to new subsets of data. The ultimate goal of data mining is prediction - and predictive data mining is the most common type of data mining and one that has the most direct business applications. For example, a credit card company may apply predictive data mining, to derive a model that can quickly identify transactions which have a high probability of being fraudulent. Common business applications include the study and forecasting of consumer behavior.

Data Scientist

The most sought for professional in the business world. According to McKinsey Global Institute research organizations will face the shortage of people capable of analyzing big data and translating it into business insights. By 2018, the United States alone could face a shortage of 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions. Although universities have already recognized this trend and try to catch up with data science programs, they still fail at reversing this trend. The problem lies in the very nature of data science profession – it requires skills ranging from computer science, mathematics, statistics, data visualization and communication to business and strategy and there are not so many people who have it all.

Hadoop

You have probably already seen the logo with the cute elephant. What lies behind it? Hadoop is an infrastructure solution for storing and processing data sets that are too big to be stored and crunched on a standard PC. It’s a set of open source programs and procedures which anyone can use as the basis of their big data operations. Hadoop’s processing procedures are called MapReduce. In a nutshell, the process is based on breaking up data into analysis-ready pieces that can be distributed across different computers in different locations and analyzed on the spot. It first distributes the analysis (map) and then collects the results back into one report (reduce). Instead of processing data into one pipe, the process is being distributed and accelerated. Hadoop deserves to be placed on our business intelligence vocabulary list as it is one of the most widely used systems for providing data storage and processing across – it is relatively affordable, efficient and based on many systems linked together, as opposed to expensive, customized solutions. By the way, Hadoop was the name of the toy elephant that belonged to the son of one of the original creators.

Internet of Things

A term to describe the phenomenon that more and more everyday items will collect, analyze and transmit data to increase their usefulness. IoT is not a science fiction idea – just think about how successful personal analytics is. Wearable devices like the FitBit, UpBand and other gadgets collect data on our fitness, including how many steps you make, how well you have slept, how many calories you have consumed etc. We can already buy sensor mats that can monitor baby’s health by tracking breathing patterns and heart rate. Soon we will also drive cars that will... drive themselves. Google in collaboration with Toyota is developing a self-driving car filled with on-board computers, sensors and cameras that will allow it to drive automatically and accident-free.

Software-as-a-Service (SaaS)

It’s a subscription-based software licensing model used by more and more providers, including datapine. Software is provided over the cloud and users access it via their web browsers. Users don’t buy software outright and don‘t have to invest in its installation, infrastructure or maintenance – they only pay for the time spent using it, the amount of data they access or the number of users with granted access. This scheme empowers non-technical users to take the full advantage of the software at hand, it saves money that would otherwise be invested in IT service and gives you more mobility – with cloud-based technology you can work from anywhere and with partners from all over the world.

We hope this list of most common business intelligence vocabulary proved to be useful for you. The world is changing thanks to technology that constantly generates new data. Today the increased capacity to analyze this data can help you gain the winning edge in business and that’s the potential you should not squander. Companies already bring together different and previously inaccessible data sources to make successful business decisions.