What is the difference between metadata management and data governance?
Metadata management is the administration of system processes that catalog, profile, and manage the data about the data. Data governance brings together the components of your overall data management strategy (database operations, metadata management, data warehousing, etc.), providing a framework of rules and policies to ensure the quality, integrity, and security of your data as it flows throughout the enterprise system.
Is MANTA an incident resolution tool?
MANTA’s solution allows you to prevent data issues in the design phase or spot such issues in the implementation and testing phase to increase productivity and reduce maintenance costs. With MANTA’s complete lineage, data-related issues can be traced back to the source 90% faster than with the traditional manual approach, so the teams responsible for particular systems can fix any issue in a matter of minutes.
What is the difference between data mapping, data flow, and data lineage?
Data mapping identifies the data source or source system (i.e., terminology, data set, database, etc.) the data is coming from, or being mapped from, and the target repository (i.e., database, data warehouse, data lake, cloud-based system, or application, etc.) it’s going to be or being mapped to.
What is the difference between an ETL pipeline and a data pipeline?
A data pipeline is essentially your data processing infrastructure—the tools and processes used to extract and move data between a source system (or multiple systems) and a targeted repository (i.e., a database, data warehouse, data lake, cloud-based system, or application, etc.) An ETL pipeline is a type of data pipeline. ETL stands for “Extract, Transform, Load,” in which these three database functions are combined into one tool to pull data out of one database and place it into another database or system.
What is SSRS?
SSRS stands for SQL Server Reporting Services, which is a server-based report generating software within the Microsoft SQL Server suite and tools. SSRS connects to SQL databases and provides tools to create, deploy, and manage SQL reports from the database as well as from the analytics center of your data warehouse.
How is data lineage relevant to auditors?
Data lineage provides auditors with a trail of documented data flow by enabling visibility into the flow of data across enterprise systems and throughout the entire data lifecycle. As a result, regulatory reporting can be streamlined and consistent, and security risks or weaknesses will be identified and resolved in order to maintain compliance with government and industry regulations.
How can data lineage help with auditing data standards?
Data lineage provides visibility into the flow of data throughout enterprise systems and ensures a documented data flow trail throughout the data lifecycle. Data lineage is helpful for setting and adhering to auditing standards, as it helps serve multiple purposes, including ensuring compliance with regulatory reporting, identifying data security breaches, and maintaining compliance with government and industry regulations.
How does data provenance compare to data lineage?
Data lineage goes beyond this historical record of data to look at the how and possible impacts of data movements and dependencies. Data lineage provides a full overview of how your data flows throughout the systems of your environment via a detailed map of all direct and indirect dependencies between data entities within the environment. This gives you a greater understanding of the source, structure, and evolution of your data.
What is the most important feature of a data lineage application?
The most important capabilities of a data lineage application are automation and the ability to review how lineage looked in the past and compare two different time slices. Automating data lineage collection is the only way to ensure accurate and up-to-date results. Delivering historical lineage and comparing two different time slices allows you to see how the lineage developed. Such delivery is key to achieving a holistic view of the data landscape.
Is MANTA a root cause analysis tool?
MANTA accelerates root cause analysis significantly. With MANTA's complete lineage, organizations are able to track every data-related issue back to its source 90% faster compared to the traditional manual approach, so the teams in charge of specific systems are able to fix any malfunctioning system quickly.