What is Data Remediation?
Data remediation: Identifying and correcting errors, inconsistencies and inaccuracies in data to ensure quality and accuracy.
A collection of common terms, themes and topics used in the data management ecosystem.
Data remediation: Identifying and correcting errors, inconsistencies and inaccuracies in data to ensure quality and accuracy.
Data integrity is the process of maintaining the accuracy and completeness of data over its entire life cycle and how it is applied..
ETL refers to the process of extracting data from a source system, transforming it into the desired format, and loading it into a target system.
Data observability is the ability to see and understand data as it flows through an organization, enabling professionals to track metadata issues
This post defines and explains the differences between a Data Lake, Data Warehouse and Data Lakehouse
The Gartner Magic Quadrant provides a graphical depiction of different types of technology providers and their position in fast-growing markets..
Artificial Intelligence is the application of computer science techniques to perform a range of decision-making and prediction activities.
Environmental, Social and Governance refers to a collection of criteria used to evaluate an organisation’s operations and measure their sustainability.
KYC and AML are fundamental components of regulatory compliance in financial institutions, referring to the prevention of money laundering and other financial crimes.
Customer 360 refers to a 360-degree view of a customer’s journey through an organisation, including accounts, interactions and enquiries.
Microsoft Power BI is a technology-enabled business intelligence platform for gathering, analysing and visualizing data.
Metadata is a way to describe and make sense of data. It’s a shorthand representation of the data, which helps data stewards easily understand the information in front of them.
Data profiling is the process of reviewing data, including its source, to provide helpful summaries of information about the data, including potential data quality issues.
Launched in 2010, Microsoft Azure is one of the world’s leading public cloud computing software, offering over 200 preconfigured services including AI, storage, networks and integration.
Self Service Data Governance (SSDG) is an enterprise-wide initiative incorporating data disciplines such as data lineage, data quality and data analytics.
A data catalog is an inventory of an organisation’s data assets, which can be accessed by data stewards and scientists in order to quickly retrieve the information they need.
Data lineage is the process of mapping where your data has originated from and where it ends up. It enabled enterprises to track the flow of data and quickly identify where errors have occurred during the data lifecycle.
Data governance refers to a collection of disciplines working together to achieve effective use, monitoring and reporting of enterprise data.