EN Glossary.
The main data science, human resources development
and IT terms and definitions
Algorithm
An algorithm is a formal instruction for action to achieve a certain result. It must be formulated in such a way that it works unseen and can be repeated according to a clear scheme. For a computer, the algorithm works like a recipe that it is supposed to follow.
Artificial Intelligence
The field of Artificial Intelligence or AI is concerned with the automation of intelligent behavior and is closely associated with machine learning. Artificial Intelligence is an interdisciplinary field and is divided into weak artificial intelligence, which has already found its way into our everyday lives, and strong artificial intelligence, which is currently still a construct of the science fiction genre.
AI Literacy
is the ability to understand what artificial intelligence is and what it takes to make it work. These skills make it possible to critically evaluate AI technologies, communicate effectively with an AI, work with it, and use it as a practical tool for one's own work.
Backend
The backend of a web application or app provides the actual logic and functionality of the application. This includes receiving, processing and responding to requests from the front end. The task of backend developers is to keep the application up to date and efficient and to implement new functions.
Big Data
Big Data is described as data sets that have the following characteristics:
- a high speed of generation of their data
- a large variety of data (heterogeneity) and high data quality
- a large volume
Big Data therefore also offers great added value for businesses and helps to make trends measurable and to derive forecasts and recommendations for action from them..
Business Analytics
Business analytics describes specific capabilities, technologies, and processes for continuous investigation of business developments from which valuable insights can be derived to improve business decisions.
Business Intelligence (BI)
Business intelligence is the process of processing collected data into meaningful insights. Business Intelligence is a discipline from business informatics and describes the systematic analysis of a company.
Business Intelligence Analyst (BI Analyst)
A business intelligence (BI) analyst extracts insights from company data and uses them to derive recommendations for action. To do this, they use specialized software and IT systems such as Power BI, Tableau or Microsoft Excel.
Clustering
The IT term clustering (also cluster analysis or agglomeration analysis) refers to a method for discovering similarities and patterns in data sets. These groups of similar or identical data and elements are called clusters.
Convolutional Neural Networks (CNNs)
CNNs are a special artificial neural network. CNN stands for Convolutional Neural Network. These are mainly used for unstructured data, especially image and video material.
Customer Analytics
Customer analytics is the data-driven assessment of a specific customer base. This enables the identification of profitable customer relationships and buyer interests in order to create suitable, individual offers.
Data
Data contains information. In computer science, data are digital and binary values and information that are collected through observation, measurement, and statistical surveys, as well as formulable findings.
Data Analysis
Data analysis involves the use of statistical methods to gain insights from collected raw data. These methods include data collection, examination, cleaning, processing, and modeling.
Data Analyst
A Data Analyst collects and processes data and information of all kinds that add value to a company. A Data Analyst visualizes and presents the findings from the data analysis to support decision makers using these insights.
Data Awareness
See Data Literacy
Database
Designates a system for electronic data management. Data is collected and stored here.
Data Driven Management
Data Driven Management means making business decisions based on data and facts.
Data Engineer
The Data Engineer is an important job role in the data environment. Data engineers are primarily tasked with installing and maintaining data pipelines. Data pipelines can be understood here as the automated transfer and processing of data. Data engineers ensure that data quality remains consistently high and that data processing is efficient.
Datafication
Describes the digitization of everyday activities and areas of life and the associated generation of data.
Data Lake
A data lake is a repository where data can be stored in its original form. Unlike the data warehouse, the data stored in the data lake is not ready for analysis, but unsorted or heterogeneous. On the one hand, this allows greater flexibility in handling this data, but on the other hand, it represents a higher threshold for users. This makes the data lake particularly useful for the requirements of data scientists and data analysts.
Data Literacy
Data literacy (also referred to as data awareness) can be translated as basic data competence. This describes the ability to assess and deal with data. This includes understanding why and how data is collected, what added value it offers, and how its evaluation works.
Data Management
Data management (also known as data administration) encompasses all aspects that form the prerequisite for successful data strategies. The goal of data management is to optimally prepare and provide data for processing.
Data Science
Data Science combines scientific and statistical applications to extract knowledge from data. Methods of statistics, higher mathematics, programming and artificial intelligence are used.
Data Scientist
Data Scientist is one of the most sought-after professions and job roles of the new decade. Data Scientists apply scientific methods, as well as methods of machine learning and artificial intelligence, in order to process complex problems relating to data or to develop data products. In addition to programming, they also use the methods of higher mathematics and statistics.
Data, structured and unstructured
Digital information (data) usually has different structures. A distinction is made between structured, semi-structured and unstructured data. Depending on the available form, it is more or less complex to prepare the data for processing.
Data Thinking
Data Thinking combines the methods of Data Science and Design Thinking in order to successfully Develop data products and data strategies. Data Thinking looks at and solves problems by taking the user's point of view.
Data Warehouse
A data warehouse is a central database optimized for data analysis. The data is prepared and follows a defined structure. The structure of the data warehouse simplifies standardized queries, e.g. for the creation of reports. Due to the high degree of preparation and standardization of the data, there is a lower threshold for use, but the application possibilities are less flexible than those of a data lake.
Data visualization
Data visualization (also Data Visualization or Visualization of Data) is the graphical representation of data with the goal of gaining quick insight into and communicating the information resulting from the data.
DAX language
DAX stands for Data Analysis Expressions and is a formula language that allows data to be retrieved and analyzed in tabular form. DAX can be used in Power BI, and other Analysis Services to implement simple and advanced calculations and data analysis.
Deep Learning
Deep Learning is one of the most advanced and complex approaches to Machine Learning. The so-called neural networks consist of algorithms inspired by the structure and function of the brain, but significantly beyond human capabilities. Deep learning models can make their own predictions completely independent of humans. To do this, they analyze data following a logical structure to make the most likely prediction from the results.
Design Thinking
With the help of Design Thinking, approaches to solving problems and approaches to new ideas are to be created. It is an approach that aims to create solutions for user-friendly applications.
Digitization
Digitization is, in simple terms, the conversion of analog content into digital content. This furthermore fulfills the added value that digital data is created in this process, which facilitates collection and processing.
Full Stack Developer
The Full Stack Developer is considered an all-rounder among web developers. Because a full stack developer is active in both the frontend and the backend, they must be proficient in many programming languages and frameworks. Full stack developers not only develop programs or web applications themselves, but often also take on project management tasks or other supporting activities in the IT area.
Framework
A framework is in the software development a basic framework, which indicates the basic structures of a future software product and facilitates the work of a programmer. Frameworks occur frequently in the form of class libraries, which already contain ready-made functions and classes.
Frontend
The frontend represents the data and processes of the backend, e.g. of web applications or apps, in a graphical user interface. The frontend is what you see when you navigate a website. The task of web developers is to make the user interface as user-friendly as possible.
Keras
Keras is an open source library. Keras is used to perform fast implementation of neural networks. Accordingly, Keras is often an important building block in the application of Deep Learning.
Key Performance Indicator (KPI)
KPI is an abbreviation for Key Performance Indicator and refers to key figures that are defined to measure the success of an activity or the performance of a person or a department. They are used in corporate processes to make performance measurable and evaluate it.
Machine Learning
Machine Learning is a field of artificial intelligence, with the goal of enabling the computer to automatically draw data from its environment and make evaluations in order to make better decisions. In doing so, the algorithm learns rules from data on its own, even those that are not explicitly given. How well an artificial intelligence learns depends on the quality and quantity of the data it is provided with for learning. (Principle "garbage in, garbage out").
Matplotlib
Matplotlib is a library of the Python programming language. It is particularly suitable for the visualization of data.
Microcredentials
Microcredentials provide evidence of learning from short, certified courses. Whether knowledge acquired in an online course or in a classroom-based course, microcredentials are recognized as useful credentials and promote the targeted acquisition of new skills and competencies.
OOP - Object Oriented Programming
OOP is a programming style that is well suited, for example, to the production of software that is both complex and must be continuously updated. It involves organizing the code around or through so-called objects, which are then later related to each other. Everything that exists within a program is its own object, containing its unique attributes and behavior. Object-oriented programming is therefore a particularly efficient approach, as the program code can be reused and scaled.
Regression analysis
Regression analysis is the name of a statistical analysis method that is often used in machine learning. It involves the prediction of a continuous target variable from one or more so-called explanatory variables. In the course of a regression analysis, cause-effect relationships can be examined in addition to predictions.
R
R is a programming language that is used especially in the creation of statistical calculations and graphics.
Self-Service BI
Self-Service BI (Business Intelligence) enables business departments to access corporate data and perform analyses independently. Self-service BI solutions enable employees to independently meet their information needs for daily work without having to rely on the IT department every step of the way.
Structured Query Language (SQL)
SQL stands for Structured Query Language and is a language used for communication between relational databases. It is used to query, edit or remove data from databases.
Framework
A framework is in the software development a basic framework, which indicates the basic structures of a future software product and facilitates the work of a programmer. Frameworks occur frequently in the form of class libraries, which already contain ready-made functions and classes.
TensorFlow
Similar to Keras, TensorFlow is a framework for implementing neural networks. Keras acts as an interface and makes it easier to work with TensorFlow.
Trend analysis
By means of a trend analysis, trends can be observed and their causes can be fathomed. Through a trend analysis, one can predict the influence of a trend on a company and relevant markets.
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