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.
12/06/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
Data processing is the process of capturing, storing, manipulating, processing, and presenting data to achieve a specific goal. It is a central component of most modern computer and information systems and helps to facilitate everyday tasks by enabling people to process data in an efficient manner.
12/06/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
Predictive analysis is a process used to predict or forecast future events by using data from the past and current state. It is used to make better decisions by identifying similar trends and developments. It helps companies better understand risk by predicting potential outcomes. It also enables companies to better predict customer behavior and increase sales.
12/06/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
Data governance is a formal approach to managing and controlling data in an organization. It includes policies and processes that govern the collection, processing, storage, and use of data. The goal of data governance is to maximize the value of data for the entire organization. This includes defining, documenting, and monitoring processes around data to achieve recurring, consistent results.
12/06/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
Data integration is a process of consolidating, processing and harmonizing data from different sources to combine them into a coherent information system. The purpose of data integration is to combine all relevant information from different sources to provide a unified understanding of the data set. This allows companies to access and use the data in a unified way in decision making and business process.