FAQ

What is MANTA Data Lineage and what does it do?

MANTA data lineage is a detailed map of all data flows, sources, and transformations across your data processing systems. On top of that, MANTA provides a detailed map of all direct and indirect dependencies between data entities in the environment. The map can be adjusted to the needs of any data user, regardless of how tech-savvy they are. Thanks to that, everyone gets full visibility and control of their data pipelines and is empowered to take informed actions with confidence.

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What is the purpose of data lineage?

Data lineage helps you tame data complexity and gives you a full overview of how your data moves across systems, including where it originated, how it transforms along the way, and how it’s interconnected. Such an overview will help you boost your data governance efforts, increase overall trust in data, achieve full regulatory compliance, accelerate root cause and impact analyses, roll out our frequent bug-free releases, painlessly migrate to the cloud, and more. 

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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.

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How do MANTA’s active tags work?

Active tags are fully customizable color-coded attributes that allow you to highlight information relevant to you in the context of the data pipeline. With active tags, you can draw attention to specific characteristics (such as data quality or data privacy issues) and mark them directly in the lineage diagram and repository tree. MANTA also offers default active tags that are flagged for you automatically to bring them to your attention. Default active tags include significant transformations and primary and foreign keys.

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Is MANTA a data impact analysis tool?

With MANTA’s solution, DataOps teams have immediate visibility of how a planned change will influence other parts of the data environment. Having a full overview of data dependencies enables them to check the impacts of all planned changes early in the development process in the design phase. Teams that use MANTA report a significant drop in the number of erroneous releases (below 1%) and improved productivity (by 30-40%) thanks to MANTA’s automated capabilities.

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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.  

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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.

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Does MANTA do dependency analysis?

An invaluable tool for analyzing data dependency is the lineage graph generated by MANTA. You are able to see exactly how each attribute is related to another, how a particular transformation impacts them, or how a particular transformation has affected the data. Knowing the answers to such questions will give you more power and control over dependencies and will enable you to deploy more automated techniques. 

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Should data lineage be part of a data migration strategy?

Migrating from legacy systems or simply adding a new data source to any cloud platform becomes complex without visibility across all data flows to guide the process. Lineage automation helps you gain visibility and avoid the dangers of not knowing by illustrating exactly which data gets used, how it gets used, where it comes from, and how it transforms as it flows across systems.

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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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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.

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Does data lineage help with SQL reporting?

With a detailed map of all direct and indirect dependencies between data entities within your environment, data lineage provides a full overview of how your data flows throughout your environment. As a result, you get a better understanding of the sources, structure, and evolution of your data. The visibility provided by data lineage can reduce SQL errors in reporting, improve understanding of your reporting, and help improve decision-making based on your data. 

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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.  

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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.  

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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.

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How can data lineage improve data quality?

When you have a complete overview of all your data flows, sources, transformations, and dependencies, you have control of your data assets. You can speak to the accuracy and quality of your data and have confidence in your data information and reports. By giving you a full overview of how your data moves across systems, where it originated, how it transforms along the way, and how it’s interconnected, data lineage can help you to ensure the quality of your data, reinforce your overall data management strategy, and increase trust in your data.

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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.

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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.

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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.

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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.

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Nicholas Murphy
Nicholas Murphy
Sales Engineer

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