Data Flows
What is a data origin?
The source of data is the point of origin. This point can be a source database, schema, table, and/or column where the data was housed before being moved to or transformed from other systems.
What is data lineage in a data lake?
A data lake allows for the movement, transformation, and utilization of data by other applications. Data lineage results from these activities, which MANTA's automated data lineage platform can visualize.
What makes a data migration process quick and easy?
Performing data migrations in large legacy environments can be tricky since there are so many unknowns and blind spots. Before initiating a migration project, conduct automated data lineage to ensure you have mapped the migrated systems and understand the data dependencies completely before starting the migration.
What is a data lineage scanner?
A data lineage scanner connects to database repositories, ETL tools, reporting tools, and other types of source technology to document how data flows, transforms, and impacts assets both downstream and upstream as well as where the data is sourced from, making it possible to gain full visibility and control over even the most complex data pipelines.
How do you establish data lineage?
The ways in which each tool establishes data lineage are different. There is a need for technology-specific scanners to parse code (like stored procedures, ETL job definitions, etc.) and identify the structure and movement of information throughout a customer's ecosystem.
What are the steps to implement a new data lineage tool?
In general, the base deployment takes about a week. Scanning the data sources (locations where the data is gathered) takes more time depending on how prepared they are and how complex they are. There are several factors that affect deployment time.
When it comes to MANTA, in general, if all the prerequisites are met, MANTA Flow Server will be installed, then the Single-Sign-On/Lightweight Directory Access Protocol (SSO/LDAP) connections are made, and then the focus shifts to connecting to the data sources that need data lineage.
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.
Is data lineage part of data governance?
Data governance, at its core, is establishing trust in data - the quality and sources of data, the integrity and the use of data, and the security of data during the lifecycle of data within the enterprise. Data lineage plays an important role in your data governance framework and overall data management strategy by providing visibility into how data flows throughout your environment as well as transparency in the sourcing, structure, and evolution of your data.
We have a very large set of data across multiple databases. Can we still do data lineage and visualize data flow easily?
MANTA supports the highest number of native scanners of all the data lineage solutions available on the market. MANTA also offers a unique Open MANTA solution that allows you to benefit from MANTA’s lineage even when there’s no formal scanner available for the desired technology. Combining those capabilities allows MANTA to scan every nook and cranny of your data ecosystem to harvest accurate and up-to-date data lineage across multiple databases and visualize data flows.
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