MANTA Features

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.

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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.

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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.

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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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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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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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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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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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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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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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