We have also optimized the business for:
What does it really mean when we talk about 'data warehouse,' 'in-memory computing,' and 'data sources'?
Click on our BI glossary below to get short, precise definitions of the key concepts that are valuable to know when considering acquiring a BI solution.
Understanding Important BI Terminology
Big data—and systems for managing big data—concerns the extremely large, unstructured volumes of data that are already generated by, for example, social media, intelligent systems, sensors, etc., around the world—and that most industries will need to be able to manage in the future.
The concept of business analytics encompasses a range of solutions and methods that enable in-depth analysis of a business and the simulation and prediction of various future scenarios. The analyses are based on the methodical application of the company's data as well as statistical analyses of that data.
A business intelligence system is a software system that collects and analyzes a company's internal and external data from a wide range of data sources and presents the data as actionable and comprehensible knowledge to support both business-critical decisions at the management level and operational decisions and actions at the employee level.
A dashboard is the primary presentation and control tool in a BI system. The dashboard displays a tailored selection of KPIs, graphs, geographic map overlays, scales, tables, etc., which quickly provide an overview of the company's condition and development. From the dashboard, there is quick access to the data behind the figures, and it is possible to change the display settings on the dashboard with just a few clicks if different perspectives on the numbers or new insights into other areas of the business are desired.
Data mining encompasses technology for managing and reviewing a company's data to identify relationships, patterns, and trends. Data mining is based on statistical and mathematical models as well as automatic recognition and identification of patterns.
Many traditional BI systems use a data warehouse as a 'repository' for data from all your existing business systems (e.g., accounting systems, production management systems, etc.). In the data warehouse, the data is organized to facilitate easier data analysis by the BI system.
The term data sources refers to the various business systems that the company has at its disposal—such as ERP systems, inventory management systems, and various industry-specific systems. All of these systems provide data to the BI solution; therefore, it is crucial that the data sources are free of errors, as this would lead to inaccuracies and uncertainty in the results and reports generated by the BI system.
Drill-down tools are the tools that allow you to dive into the data behind the insights presented in dashboards and reports, uncovering detailed knowledge about the causes and trends (e.g., in the company or in the market) that underlie the results and information presented.
An ERP system (Enterprise Resource Planning) refers to a software system that connects a wide range of important functions within a company—including order processing, sales, purchasing, inventory management, and finance. Among the popular ERP systems in Denmark are SAP, Microsoft, and Oracle.
The term queries refers to the knowledge one wishes to extract in dashboards and reports, as well as the inputs that need to be provided to the BI solution to obtain that knowledge. For example, one might make a query for 'sales in store X in week 42, 2016' or 'costs of production and delivery of product X compared to the price quoted in an offer.' Queries can be predefined and automated, or they can be added over time, often as self-service, allowing the employee in need of specific information to change settings in their dashboard and retrieve the desired knowledge themselves.
Examples of Queries from Sales:
Sales are fundamental to your business. Here are three examples of analyses that help you maintain the right focus concerning your sales. These examples focus on customers, but it is equally important (and easy) to analyze seller performance and product performance:
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Topline performance on customers, sellers, and products—revenue.
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Bottom line performance on customers, sellers, and products—contribution margin or gross profit.
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Topline vs. bottom line performance on customers.
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In-memory computing refers to the handling (e.g., analysis or sorting) of data occurring in a server's RAM (instead of in an extensive database or data warehouse), which enables faster analysis—thereby providing quicker knowledge and insights into the company's key figures and performance—and allows real-time access to the data behind these figures.
KPI stands for Key Performance Indicator and refers to a metric that shows how well a company (or a department within the company) is performing. Examples of KPIs can include cost per acquired customer, upsell per salesperson, contribution margin per product, etc.
The term 'cube,' used by many traditional BI systems, refers to a multidimensional 'box' of data (e.g., product – city – time, which shows the sales of a product in a specific city over a certain time period). It is a way to analyze and visualize specific business data in a comprehensible manner. In many standard BI systems, a number of desired cubes are defined from the outset, and if one wishes to later change a dimension—such as changing from a monthly basis to a weekly basis—it requires the cube to be redefined and regenerated.
Reports encompass the clear presentations of data-driven knowledge generated by the BI solution. Upon request, the reports can be automated, customized, and distributed to relevant employees at desired intervals, ensuring that staff and management always have up-to-date information on which to base decisions and actions.
