FAQ
What are SQL reporting services?
What is a good data migration strategy?
What are dependency analysis tools?
What are incident resolution tools?
What are root cause analysis tools?
What is data origin authentication?
How do I fix my broken reports?
Will we need special training to use MANTA data lineage?
Do I need to be CDMP certified to use MANTA?
How can I get started with MANTA?
How long does data migration take with MANTA?
Does MANTA have scanners for database technologies, ETL technologies, and reporting tools and technologies?
Can MANTA scanners be customized?
Can MANTA merge its scanners with our existing scanners?
Does MANTA have its own database scanners?
Does MANTA follow the DAMA data governance framework?
Does MANTA provide documentation regarding server requirements, definitions, and technical specifications?
Can MANTA be used for data migration preparation?
Does MANTA work with various ETL orchestrations?
How can MANTA integrate with my metadata management tool?
Can I integrate MANTA with my profiling tool?
Can I integrate MANTA with my data privacy tool?
How can MANTA integrate with my business intelligence?
Can I integrate MANTA with my CICD pipeline?
What does MANTA support in Snowflake?
How is MANTA’s data lineage different from other data lineage tools on the market?
Does MANTA consider conditional statements, where clauses, and joins?
How do I track data lineage?
How do you implement data lineage?
Will MANTA affect my database?
Is MANTA non-intrusive and non-transformative?
What do we need to get started with the implementation?
What kind of support does MANTA provide during the implementation?
Are a lot of updates and maintenance required?
What kinds of teams need to be involved in the implementation?
What could delay my implementation?
How can we implement MANTA as quickly as possible?
Why is data lineage important?
Data lineage provides a full overview of how your data flows through 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 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 stitching?
The phrase “stitching data lineage” refers to the linking of relationships between assets in different types of technologies. The representation of the relationships between two different resources, or types, is them ‘stitched’ together. For technologies supported out of the box, MANTA can stitch the lineage across different systems in an automated way.
How can data lineage help data scientists make better reports?
Data lineage provides data scientists with greater functionality for locating the appropriate metrics required for their reports, requiring less time and effort. It also affords greater confidence in the metrics being utilized in the reports, as it is possible to visualize the lineage back to the source technologies.
Does data lineage require a data dictionary or glossary?
As a matter of fact, data lineage does not require the use or access to a data dictionary. Data lineage is independent of any of these solutions.
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.
Are there open-source data catalog tools?
There are open-source data catalog tools that "catalog" the data in an organization, its location, and how it can be accessed. When it comes to seeing how your data functions inside your data environment, a data catalog tool is valuable but incomplete.
How can I migrate server and data fast?
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 I understand my legacy/data environment to prepare for my migration?
MANTA can be utilized to better understand how a legacy environment is architected, which helps when preparing for a migration project. Specifically, it allows you to accurately assess the complexity of the to-be-migrated system and its sources and dependencies. It enables the migration team to provide accurate estimates of the time and effort it will take to complete the project. It also allows you to plan the migration phases with respect to the dependencies in the environment.
Does MANTA provide documentation regarding server requirements, definitions, and technical specifications?
Yes, this documentation can be located in the MANTA Knowledge Base.
Does MANTA follow the DAMA data governance framework?
MANTA focuses on data lineage, which is derived from metadata. The data within the connected resources is left untouched during a scan.
How flexible is MANTA when it comes to possible integrations?
Can I integrate MANTA with my CICD pipeline?
Yes, MANTA can be utilized as a component of a CICD pipeline to supplement teams’ development efforts.
How can MANTA integrate with my data intelligence?
You can boost your data intelligence efforts with detailed, accurate, and up-to-date data lineage provided by MANTA. MANTA has a robust API for developing integrations with data intelligence tools.
Can I integrate MANTA with my data privacy tool?
Yes, you can leverage MANTA’s comprehensive data lineage to build trust in data, ensure data security, and adjust your data privacy policies. MANTA has a robust API for developing integrations with data privacy tools.
Can I integrate MANTA with my profiling tool?
You can utilize MANTA’s detailed lineage and unique features for data profiling and achieving better data quality. MANTA has a robust API for developing integrations with data profiling tools.
How can MANTA integrate with my metadata management tool?
MANTA has OOTB connectors to all the major players in the data governance/cataloging space. MANTA also can export its repository to consumable formats for unsupported third-party metadata management applications. Please visit MANTA’s Integrations page to find a full list of supported data governance tools/catalogs.
Does MANTA work with various ETL orchestrations?
There will always be technologies on the market that don’t have supported scanners provided by MANTA. In order for the lineage from unsupported technologies to be represented in MANTA visualization diagrams, MANTA provides a framework called Open MANTA. The Open MANTA framework makes it possible to define and manage lineage generated by unsupported technologies.
Why augment Snowflake with data lineage?
If Snowflake is utilized as a source for reports, applications, or another relational database, then having an up-to-date auditable blueprint of its data lineage is a must. Automated lineage gathering can reduce the time and costs of moving data to Snowflake by boosting business outcomes and migration benefits.
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.
Does data lineage manipulate or modify the data?
MANTA’s data lineage does not manipulate or modify your data. In fact, MANTA does not have access to the actual data at all. MANTA connects to your disparate data resources (such as databases, data warehouses, ETL tools, and BI tools).
What is the difference between MANTA, MANTA Live, MANTA Flow, MANTA Admin UI, and Open MANTA?
MANTA Live, Open MANTA, MANTA Flow, and MANTA Admin UI are different products and applications offered by MANTA.
How long does it take to implement a new data lineage tool?
What is data governance vs metadata management?
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 a data pipeline vs ETL?
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 in SQL server?
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 audit 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.
What is data lineage vs data provenance?
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 data lineage in 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.
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.
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.
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.
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.
How can I improve lineage 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.
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.
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.
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.
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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