Best Data Lineage Tools 2022

Data lineage is the process of identifying the source of data, recording the transformations and flows of data over time, and visualizing data flow from sources to end users.

Data lineage empowers data scientists, engineers, and data teams with granular visibility of data dynamics to help them and their organizations keep tabs on errors, carry out system migrations, execute process changes with lower risk, and more.

One challenge is documenting all that, and that’s where data lineage tools come in handy.

What is the Best Way to Document Data Lineage?

Data lineage documentation is a resource-intensive process in terms of personnel, funds, time, etc. There are two methods of documenting data lineage; descriptive and automated. Each method has its benefits and drawbacks, and each can be optimal depending on the nature of the data lineage project.

Descriptive data lineage uses a manual process to describe data lineage, and as such it has a large time and effort requirement. That’s where automated data lineage comes in.

Automated data lineage reduces time lost in the collection, storage and processing of chunks of data because it replaces manual processes plus human error with intelligent operations, software and even AI. Automated data lineage eases root cause analysis, helps organizations achieve and maintain compliance, ensures data accuracy and simplifies BI system migration.

Also see the Top Data Catalog Tools & Software

Best Data Lineage Tools

Here are some of the top data lineage tools, based on our analysis and review of the market.

Alation

Alation is an automated data lineage tool that offers a wide range of data intelligence solutions like data search and discovery, data stewardship, data governance, analytics, and transformation. It is AI-driven, with an advanced behavioral analysis engine to generate actionable insights.

Moreover, Alation profiles data and examines usage to ensure users have the accurate insights and offers insight into data usage by users. It also has built-in collaboration capabilities.

Key Differentiators

• Behavioral Intelligence: Alation improves users’ productivity through behavioral intelligence by indexing a broad array of data sources such as cloud data lakes, relational databases, and file systems using machine learning.
• Seamless Collaboration: The collaboration capabilities offered by Alation empower enterprises to make better decisions by providing enterprise-wide access to credible data to foster seamless collaboration on data assets with knowledge capture and integrated communication.
• Deep Connectivity: Alation streamlines analytics by providing connectivity to many popular business intelligence (BI) tools and data sources through an Open Connector SDK (software development kit) and APIs (application programming interfaces).
• Guided Navigation: The quality and confidence of analytics is bettered by surfacing flags, recommendations, and policies as data consumers search using natural language or make queries in Alation’s intelligent SQL editor.

Con: Processing complex queries and large amounts of data impacts performance.

Pricing: Even though Alation offers a weekly live demo, you would have to contact their sales team for pricing information.

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Atlan

Atlan is a modern data workspace that aims to empower data democratization within organizations while maintaining security and governance standards. The platform offers capabilities in areas such as data lineage and governance, data quality and profiling, data cataloging and discovery, and data exploration and integration.

In addition, Atlan has automated data profiling, discovery, an intuitive search interface and more features that help data teams free up huge chunks of their time to improve their productivity and replace tedious manual tasks.

Key Differentiators

• Auto-Classification of PII: Atlan’s algorithms automatically classify personally identifiable information (PII) and sensitive data such as customer names, physical and email addresses, and credit card information.
• Column-Level Access Controls: Atlan empowers users to create granular access controls, ranging from individual columns to BI dashboards, by databases and schemas as well as tag-based data asset grouping.
• Downstream Integrations: With Atlan, customers have access to out-of-the-box integrations with Power BI, Sisense, Tableau, and other popular BI tools.
• SQL Parsing to Automate Lineage: Atlan automatically parses through users’ SQL query logs in their BI tools and data warehouses to create data lineage visuals.

Con: Atlan has limited data transformation nodes.

Pricing: As pricing information is not publicly available, you would have to contact Atlan. They also have a free trial upon request.

OvalEdge

OvalEdge is a data catalog engineered for end-to-end data governance, quick and credible analytics, and privacy compliance. It has a cost-effective on-premises data catalog and governance tool set that crawls the BI platforms, databases, data lakes, and ETL (extract, transform, load) tools of an organization to build an easy-access, smart inventory of their data assets.

Additionally, OvalEdge offers a discovery platform that analysts, regardless of experience, can use to discover data and generate influential insights quickly. It also uses advanced algorithms and machine learning to automatically organize data.

Key Differentiators

• Source Code Parsing: OvalEdge algorithms parse numerous kinds of source code to automatically build data lineage before it is enhanced by experts who learn, validate, and correct the lineage entries.
• Automation: OvalEdge allows its users to access its data lineage by using back-end algorithms to automate various processes.
• Lineage Depiction at Object Level: As OvalEdge considers report files and tables as objects, OvalEdge’s graphical user interface (GUI) depicts the lineage at object level.
• Tracking Data at System Level: OvalEdge enables users to track the flow of data at system level, cutting across ERP systems, data warehouses, and reporting systems.

Con: Some UX (user experience) features can introduce a learning curve to the tool.

Pricing: The Essential package offers manual lineage features and starts at $15,600 per year. The Professional and Enterprise packages offer automated lineage features, but you would have to contact OvalEdge sales.

Collibra

Collibra is a data intelligence company with a cloud-based platform that merges business and IT to impart a data-driven culture to today’s digital enterprise. It has a data dictionary that documents the technical metadata of an organization and its usage. It also describes data structure, relationship to other data, format, origin, and use, providing a searchable repository for users.

Moreover, Collibra Data Lineage automatically maps relationships between applications, systems, and reports to ensure enterprises enjoy a context-rich view of data.

Key Differentiators

• Automated Lineage Extraction: Collibra uses native linear harvesters to allow users to automatically extract and maintain lineage from source systems, ETL tools, BI tools, and SQL dialects and save time that would have gone into manually maintaining and documenting lineage.
• Business Lineage: With an interactive lineage diagram depicting summary lineage, Collibra enables users to trace data flows from source to destination. Users can access data lineage throughout the enterprise to enhance the visibility and credibility of data.
• Detailed Technical Lineage: Users can swiftly understand the effects of potential changes through comprehensive technical lineage at the transformation, table, column, and SQL query levels.
• Indirect Lineage: Collibra allows users to view direct data flows and indirect relationships to provide a full picture of data dependencies.

Cons: The UI (user interface) may be clunky and unintuitive. Additionally, data lineage capabilities need to mature to better handle customer needs.

Pricing: Contact Collibra, as pricing information is not publicly available.

Also read: Top 9 Data Modeling Tools & Software

Octopai

Octopai is an automated data intelligence platform that offers data and analytics teams multilayered data catalog, data discovery, and data lineage, which allow organizations to trace their assets, understand their data flows, and add credibility to their resources. As a cross-platform metadata management automation tool, it enables its users to discover and govern shared metadata.

Additionally, Octopai automatically gathers metadata—from databases, ETL and reporting tools—which is stored in a centralized repository. A smart engine searches all metadata to quickly present results.

Key Differentiators

• Cross-System Lineage: Cross-system lineage employs augmented and automated methods to reflect data flows and dependencies to provide a comprehensive cross-system view of data landscapes. This enables users to understand the impact of a process change, a broken process, as well as high-level data flow visualization.
• End-to-End Column Lineage: End-to-end column lineage shows column-to-column level lineage connecting systems, from the point of entry to the data landscape to reporting and analytics. This helps data teams understand the impact of changes to source system columns and carry out root cause analysis and column-level data-flow visualization.
• Inner-Systems Lineage: Octopai helps users take a deep dive into details of a particular system through inner-systems lineage to provide column-level visibility from understanding the data flow and logic of each column, regardless of the complexity of the object, process, or report.

Cons: The UI may come off as clunky, and the product may present a learning curve for business users.

Pricing: Contact the vendor for current pricing information.

Datameer

Datameer provides a data engineering and analytics life cycle platform that enables data teams to directly transform and model data in their cloud warehouses using either SQL code or a no-code UI to handle complex data analytics projects.

Featuring 70+ source connectors, for ingestion of unstructured, semi-structured and unstructured data, Datameer goes beyond data ingestion to data preparation, exploration and consumption. With its interactive spreadsheet-like interface, Datameer users can blend, transform, and enrich complex data.

Key Differentiators

• Trusted Deployment: Datameer provides automated documentation, metadata enrichment, and a built-in semantic layer to encourage responsible self-service. Datameer maintains lineage and documentation throughout users’ project life cycles.
• SQL and No Code: Datameer fosters collaboration for teams using SQL and no-code to transform, explore, and publish new data models for analytics, machine learning, and reporting. SQL allows users to define transformations in native SQL syntax while no-code uses a library of prebuilt functions and operations to expedite development. Datameer’s modular design enables users to combine both SQL and no code.
• Advanced Capabilities: With other capabilities such as an enterprise-grade platform that scales to satisfy business need, easy data connectivity, dynamic schemas for fast analytic modeling, and an analyst-friendly spreadsheet-like interface, Datameer qualifies as a modern data engineering solution.

Cons: Datameer may experience lags when dealing with large data volumes.

Pricing: Even though Datameer offers a demo and a 14-day free trial, pricing information is only available after contacting Datameer.

Comparison of Data Lineage Tools

Data Lineage Tool	Object Lineage Tracing	Database Change Impact Analysis	High Volume Processing	Predictive analytics
Alation
Atlan
OvalEdge
Collibra
Octopai
Datameer

Choosing Data Lineage Tools

Your choice of data lineage tools will be influenced by several factors. You want a tool with the ability to not only trace but also verify data history, as tractability makes sure you have high-quality data. Immutability should also come into consideration, as it brings credibility to data lineage tools.

Data lineage tools with collaboration features ensure remote teams collaborate on shared data. They also ensure different types of teams across the enterprise are involved in the data journey. Additionally, you should consider how easily integrated the tool is with third-party applications, as there are many tools and stages involved in a data journey.

For your unique use case, always consider the tools with the features that satisfy your needs and are within your budget. Finally, make good use of hands-on demos and free trials, as they provide an opportunity to get first-hand experience of your shortlisted tools.

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