12/06/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
Database design is the process of planning, modeling, and implementing a database. It involves the creation of a logical and physical model for the database that includes the data structures, functions, and access rules needed to manage and access the data. It also includes defining the dependencies between the different data components and creating user interfaces that provide the user with easy access to the database.
12/06/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
Data management is the process of managing data, including organizing, storing, managing, using and protecting data. It is a strategic approach to preserving, manipulating, and distributing data to ensure that organizations have the right data at the right time and in the right form. It also involves creating and implementing policies and procedures to manage data to ensure its quality and integrity.
12/06/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
A workflow is a process that structures the operations of an organization or business to accomplish a specific task. It is a systematic process in which actions or steps are performed in a specific order to achieve the end result. Workflows can be used in a variety of industries and businesses to automate processes, reduce costs, and increase efficiency.
12/06/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
1. Data ingestion and analysis: data ingestion is the process of collecting, processing, and analyzing data from various sources to gain useful insights.
2. Data visualization: this is the process of presenting data in visual formats such as charts, graphs, and maps to identify trends and gain insights.
3. Machine learning: machine learning is a branch of artificial intelligence that enables computers to learn from experience without being explicitly programmed.
4. Predictive analytics: predictive analytics is a process of using data to predict possible future events and make decisions based on them.
5. Deep learning: deep learning is a subfield of machine learning in which so-called neural networks are used to solve complex problems.
12/06/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
Data cleansing is a technique used to clean databases to eliminate erroneous, incomplete or inaccurate data. It also includes correcting formatting errors, enabling data integration, removing duplicates, and softening or adjusting non-standard data. Data cleansing is an important part of extract-transform-load (ETL) processes, where data is imported into a database from multiple sources and then stored in a user-friendly format.