Alternatives to SQLFlow

Accelerate your data journey with AnalyticsCreator—a metadata-driven data warehouse automation solution purpose-built for the Microsoft data ecosystem. AnalyticsCreator simplifies the design, development, and deployment of modern data architectures, including dimensional models, data marts, data vaults, or blended modeling approaches tailored to your business needs. Seamlessly integrate with Microsoft SQL Server, Azure Synapse Analytics, Microsoft Fabric (including OneLake and SQL Endpoint Lakehouse environments), and Power BI. AnalyticsCreator automates ELT pipeline creation, data modeling, historization, and semantic layer generation—helping reduce tool sprawl and minimizing manual SQL coding. Designed to support CI/CD pipelines, AnalyticsCreator connects easily with Azure DevOps and GitHub for version-controlled deployments across development, test, and production environments. This ensures faster, error-free releases while maintaining governance and control across your entire data engineering workflow. Key features include automated documentation, end-to-end data lineage tracking, and adaptive schema evolution—enabling teams to manage change, reduce risk, and maintain auditability at scale. AnalyticsCreator empowers agile data engineering by enabling rapid prototyping and production-grade deployments for Microsoft-centric data initiatives. By eliminating repetitive manual tasks and deployment risks, AnalyticsCreator allows your team to focus on delivering actionable business insights—accelerating time-to-value for your data products and analytics initiatives.

The Alation Agentic Data Intelligence Platform is designed to transform how enterprises manage, govern, and use data for AI and analytics. It combines search, cataloging, governance, lineage, and analytics into one unified solution, turning metadata into actionable insights. AI-powered agents automate critical tasks like documentation, data quality monitoring, and product creation, freeing teams from repetitive manual work. Its Active Metadata Graph and workflow automation capabilities ensure that data remains accurate, consistent, and trustworthy across systems. With 120+ pre-built connectors, including integrations with AWS, Snowflake, Salesforce, and Databricks, Alation integrates seamlessly into enterprise ecosystems. The platform enables organizations to govern AI responsibly, ensuring compliance, transparency, and ethical use of data. Enterprises benefit from improved self-service analytics, faster data-driven decisions, and a stronger data culture. With industry leaders like Salesforce and 40% of the Fortune 100 relying on it, Alation is proven to help businesses unlock the value of their data.

Manta is a unified data lineage platform that serves as the central hub of all enterprise data flows. Manta can construct lineage from report definitions, custom SQL code, and ETL workflows. Lineage is analyzed based on actual code, and both direct and indirect flows can be visualized on the map. Data paths between files, report fields, database tables, and individual columns are displayed to users in an intuitive user interface, enabling teams to understand data flows in context.

Tokern offers an open-source suite designed for data governance, specifically tailored for databases and data lakes. This user-friendly toolkit facilitates the collection, organization, and analysis of metadata from data lakes, allowing users to execute quick tasks via a command-line application or run it as a service for ongoing metadata collection. Users can delve into aspects like data lineage, access controls, and personally identifiable information (PII) datasets, utilizing reporting dashboards or Jupyter notebooks for programmatic analysis. As a comprehensive solution, Tokern aims to enhance your data's return on investment, ensure compliance with regulations such as HIPAA, CCPA, and GDPR, and safeguard sensitive information against insider threats seamlessly. It provides centralized management for metadata related to users, datasets, and jobs, which supports various other data governance functionalities. With the capability to track Column Level Data Lineage for platforms like Snowflake, AWS Redshift, and BigQuery, users can construct lineage from query histories or ETL scripts. Additionally, lineage exploration can be achieved through interactive graphs or programmatically via APIs or SDKs, offering a versatile approach to understanding data flow. Overall, Tokern empowers organizations to maintain robust data governance while navigating complex regulatory landscapes.

Automatically extract and visualize data lineage by mapping the flow of data from its origin to its destination. This comprehensive data lineage management solution gathers and assesses the lineage of critical data, illustrating the data flow and derivation rules from the source to the target. Understanding data lineage involves tracing the journey of data as it is processed, transformed, and utilized, thereby revealing the flow and derivation rules that govern it. The solution offers a multi-tier, column-level data lineage graph alongside a detailed list that tracks data progression from source to target. Users can drill down into data lineage at the business system, table, and column levels for a granular view. Additionally, it provides parsers for various environments to facilitate thorough analysis, including support for Big Data technologies. Utilizing our patented technology, the system conducts path-sensitive dynamic string analysis and data flow analysis within programs, enhancing the understanding of data movement. This capability ensures that organizations maintain a clear view of their data's journey, thereby fostering better data governance and compliance.

To have complete control over your data, harness the power of data discovery, data lineage and a data catalogue. It can quickly navigate through complex data landscapes. Access the most comprehensive automated data lineage and discovery system. This gives you unprecedented visibility and trust in the most complex data environments. Octopai extracts metadata from all data environments. Octopai can instantly analyze metadata in a fast, secure, and easy process. Octopai gives you access to data lineage, data discovery, and a data catalogue, all from one central platform. In seconds, trace any data from end to end through your entire data landscape. Find the data you need automatically from any place in your data landscape. A self-creating, self updating data catalog will help you create consistency across your company.

IBM Manta Data Lineage serves as a robust data lineage solution designed to enhance the transparency of data pipelines, enabling organizations to verify the accuracy of data throughout their models and systems. As companies weave AI into their operations and face increasing data complexity, the significance of data quality, provenance, and lineage continues to rise. Notably, IBM’s 2023 CEO study identified concerns regarding data lineage as the primary obstacle to the adoption of generative AI. To address these challenges, IBM provides an automated data lineage platform that effectively scans applications to create a detailed map of all data flows. This information is presented through an intuitive user interface (UI) and various other channels, catering to both technical experts and non-technical stakeholders. With IBM Manta Data Lineage, data operations teams gain extensive visibility and control over their data pipelines, enhancing their ability to manage data effectively. By deepening your understanding and utilization of dynamic metadata, you can guarantee that data is handled with precision and efficiency across intricate systems. This comprehensive approach not only mitigates risks but also fosters a culture of data-driven decision-making within organizations.

Montara enables BI Teams and Data Analysts to model and transform data using SQL alone, easily and seamlessly, and enjoy benefits such a modular code, CI/CD and versioning, automated testing and documentation. With Montara, analysts are able to quickly understand the impact of changes in models on analysis, reports, and dashboards. Report-level lineage is supported, as well as support for 3rd-party visualization tools like Tableau and Looker. BI teams can also perform ad hoc analysis, create dashboards and reports directly on Montara.

In just 15 minutes, you can set up your automated data catalogue and receive column-level lines, Entity Relationship diagrams, and auto-populated documentation in 24 hours. You can easily tag, find, and add documentation to data so everyone can find the right one for them. Select Star automatically detects your column-level data lineage and displays it. Now you can trust the data by knowing where it came. Select Star automatically displays how your company uses data. This allows you to identify relevant data fields without having to ask anyone else. Select Star ensures that your data is protected with AICPA SOC2 Security, Confidentiality and Availability standards.

Examine the usage of your data assets, focusing on aspects like popularity, utilization, and schema coverage. Gain vital insights into your data assets, including their quality and usage metrics. You can easily locate and filter the necessary data by leveraging metadata tags and descriptions. Additionally, these insights will help you drive data governance and establish clear ownership within your organization. By implementing a streamlined lineage from data lakes to warehouses, you can enhance collaboration and accountability. An automatically generated field-level lineage map provides a comprehensive view of your entire data ecosystem. Moreover, anomaly detection systems adapt by learning from your data trends and seasonal variations, ensuring automatic backfilling with historical data. Thresholds driven by machine learning are specifically tailored for each data segment, relying on actual data rather than just metadata to ensure accuracy and relevance. This holistic approach empowers organizations to better manage their data landscape effectively.

Detect and address code and optimization challenges in real-time, mitigate data incidents before deployment, and oversee data-affecting code modifications comprehensively—from the operational database to the user interface dashboard. With automated, column-level data lineage tracing the journey from the operational database to the reporting layer, every dependency is meticulously examined. Foundational automates the enforcement of data contracts by scrutinizing each repository in both upstream and downstream directions, directly from the source code. Leverage Foundational to proactively uncover code and data-related issues, prevent potential problems, and establish necessary controls and guardrails. Moreover, implementing Foundational can be achieved in mere minutes without necessitating any alterations to the existing codebase, making it an efficient solution for organizations. This streamlined setup promotes quicker response times to data governance challenges.

Aggua serves as an augmented AI platform for data fabric that empowers both data and business teams to access their information, fostering trust while providing actionable data insights, ultimately leading to more comprehensive, data-driven decision-making. Rather than being left in the dark about the intricacies of your organization's data stack, you can quickly gain clarity with just a few clicks. This platform offers insights into data costs, lineage, and documentation without disrupting your data engineer’s busy schedule. Instead of investing excessive time on identifying how a change in data type might impact your data pipelines, tables, and overall infrastructure, automated lineage allows data architects and engineers to focus on implementing changes rather than sifting through logs and DAGs. As a result, teams can work more efficiently and effectively, leading to faster project completions and improved operational outcomes.

Microsoft Purview serves as a comprehensive data governance platform that facilitates the management and oversight of your data across on-premises, multicloud, and software-as-a-service (SaaS) environments. With its capabilities in automated data discovery, sensitive data classification, and complete data lineage tracking, you can effortlessly develop a thorough and current representation of your data ecosystem. This empowers data users to access reliable and valuable data easily. The service provides automated identification of data lineage and classification across various sources, ensuring a cohesive view of your data assets and their interconnections for enhanced governance. Through semantic search, users can discover data using both business and technical terminology, providing insights into the location and flow of sensitive information within a hybrid data environment. By leveraging the Purview Data Map, you can lay the groundwork for effective data utilization and governance, while also automating and managing metadata from diverse sources. Additionally, it supports the classification of data using both predefined and custom classifiers, along with Microsoft Information Protection sensitivity labels, ensuring that your data governance framework is robust and adaptable. This combination of features positions Microsoft Purview as an essential tool for organizations seeking to optimize their data management strategies.

Creating and overseeing a thoroughly documented data project requires significant time and extensive manual coding, but that is no longer the case. We are confident in our ability to help you improve data transformation efficiency, and we can back that promise with results. Our column-aware architecture facilitates the reuse of data patterns and efficient change management on a large scale. By enhancing visibility around change management and impact analysis, we ensure safer and more predictable data operations. Coalesce offers specially curated packages containing best-practice templates that can automatically generate native-SQL for Snowflake™. If you have specific requirements, rest assured that our templates are fully customizable to suit your needs. Navigating through your data pipeline is a breeze with Coalesce, as every screen and button has been thoughtfully designed for easy access to all necessary tools. With Coalesce, your data team gains enhanced control over projects, allowing for features like side-by-side code comparison and immediate visibility into project and audit histories. Additionally, we guarantee that table-level and column-level lineage information is continuously updated and readily available, ensuring that your data remains accurate and reliable. Ultimately, Coalesce empowers your team to optimize workflows and focus on delivering insights rather than getting bogged down in administrative tasks.

Blindata encompasses all the essential components of a comprehensive Data Governance program. Its features, including the Business Glossary, Data Catalog, and Data Lineage, work together to provide a cohesive and thorough perspective on your data. The Data Classification module assigns semantic significance to the data, while the Data Quality, Issue Management, and Data Stewardship modules enhance data reliability and foster trust. Additionally, specific functionalities for privacy compliance are available, such as a registry for processing activities, centralized management of privacy notes, and a consent registry that incorporates Blockchain for notarization. The Blindata Agent facilitates connections to various data sources, enabling the collection of metadata, including data structures like Tables, Views, and Fields, as well as data quality metrics and reverse lineage. With a modular design and fully API-driven architecture, Blindata supports seamless integration with vital business systems, including DBMS, Active Directory, e-commerce platforms, and various Data Platforms. This versatile solution can be deployed as a Software as a Service (SaaS), installed on-premises, or acquired through the AWS Marketplace, making it accessible for a wide range of organizational needs. Its flexibility ensures that businesses can tailor their Data Governance approach to meet specific requirements effectively.

Dataplex Universal Catalog provides enterprise-wide visibility and governance for structured, semi-structured, and unstructured data. Its AI-powered semantic search allows users to query data in natural language, eliminating the need for complex search syntax. The platform enriches metadata with business context through glossaries, ownership attributes, and key usage details, supporting informed decision-making. It offers automated metadata ingestion, classification, and enrichment, reducing manual data management tasks. With built-in lineage tracking, organizations can trace data origins, transformations, and dependencies across multiple sources. BigQuery integration brings these governance capabilities directly into the analytics workflow, enhancing productivity. By connecting with BigLake, Dataplex extends governance to open lakehouses with Apache Iceberg and other engines. The result is a secure, scalable foundation for managing data-to-AI lifecycles across cloud-native and open-source ecosystems.

Efficiently scan and catalog metadata, uncover and characterize data, while offering comprehensive lineage tracking over millions of datasets. Organize and classify data assets across diverse environments to enhance their value and facilitate reuse. Perform automated scanning across multi-cloud environments, business intelligence tools, ETL processes, and external metadata catalogs, along with various data types. Utilize AI-driven capabilities for domain discovery, data similarity assessment, business term linkages, and tailored recommendations. Monitor data movement with precision, ranging from overarching system perspectives to detailed column-level lineage, accompanied by thorough impact assessments. Access the Data Asset Analytics dashboard to gain insights into asset utilization, enrichment processes, and collaborative efforts. Examine data quality protocols, scorecards, metric clusters, and profiling statistics within their relevant contexts. Engage with shared data intelligence through certifications, ratings and feedback, a Q&A feature, and timely change alerts. What truly distinguishes Informatica is its extensive and robust suite of enterprise-grade data management solutions, ensuring comprehensive support for diverse data needs. With such capabilities, organizations can navigate their data landscapes more effectively and make informed decisions.

Kylo serves as an open-source platform designed for effective management of enterprise-level data lakes, facilitating self-service data ingestion and preparation while also incorporating robust metadata management, governance, security, and best practices derived from Think Big's extensive experience with over 150 big data implementation projects. It allows users to perform self-service data ingestion complemented by features for data cleansing, validation, and automatic profiling. Users can manipulate data effortlessly using visual SQL and an interactive transformation interface that is easy to navigate. The platform enables users to search and explore both data and metadata, examine data lineage, and access profiling statistics. Additionally, it provides tools to monitor the health of data feeds and services within the data lake, allowing users to track service level agreements (SLAs) and address performance issues effectively. Users can also create batch or streaming pipeline templates using Apache NiFi and register them with Kylo, thereby empowering self-service capabilities. Despite organizations investing substantial engineering resources to transfer data into Hadoop, they often face challenges in maintaining governance and ensuring data quality, but Kylo significantly eases the data ingestion process by allowing data owners to take control through its intuitive guided user interface. This innovative approach not only enhances operational efficiency but also fosters a culture of data ownership within organizations.

This is the essential tool for metadata management. In just 5 minutes, automatically populate your entire catalogue! Data Discovery. Data Discovery. Find the data you need from any part of your data ecosystem, starting with the database and ending with the specific values for each field. Automated documentation of your data from existing data storage. First-class support for unstructured and tabular data. Automated data governance actions. Data Lineage. Data Lineage. Explore your data lineage to understand where your data is coming from and where it is headed. View the impact analysis of changes. See all up- and downstream impacts. Visualize connections and relationships. API AccessNew. Tree Schema API allows you to manage your data lineage in code and keep your catalog current. Integrate Data Lineage in CICD pipelines Capture values & description within your code Analyze the impact of breaking changes. Data Dictionary. Know the key terms and lingo which drive your business. Define the context and scope of keywords

Dawiso is a comprehensive platform designed to simplify data management by integrating governance with usability for the entire organization. Central to Dawiso is its AI-powered data catalog, which empowers teams to quickly discover and understand trusted data across various systems, reports, and business applications. The platform’s flexible governance capabilities, alongside intuitive documentation apps, make it easy for both technical and non-technical users to collaborate effectively. Dawiso increases confidence in data through visual data lineage that clearly maps connections and dependencies across sources and systems. It supports regulatory compliance with customizable workflows, role-based access controls, and detailed metadata capture. By providing business-friendly tools and structured governance, Dawiso bridges communication gaps and streamlines data-driven decision-making. The platform promotes transparency, security, and usability in data management. Overall, Dawiso is built to enhance collaboration and trust in organizational data assets.

Castor serves as a comprehensive data catalog aimed at facilitating widespread use throughout an entire organization. It provides a holistic view of your data ecosystem, allowing you to swiftly search for information using its robust search capabilities. Transitioning to a new data framework and accessing necessary data becomes effortless. This approach transcends conventional data catalogs by integrating various data sources, thereby ensuring a unified truth. With an engaging and automated documentation process, Castor simplifies the task of establishing trust in your data. Within minutes, users can visualize column-level, cross-system data lineage. Gain an overarching perspective of your data pipelines to enhance confidence in your data integrity. This tool enables users to address data challenges, conduct impact assessments, and ensure GDPR compliance all in one platform. Additionally, it helps in optimizing performance, costs, compliance, and security associated with your data management. By utilizing our automated infrastructure monitoring system, you can ensure the ongoing health of your data stack while streamlining data governance practices.

Kensu provides real-time monitoring of the complete data usage quality, empowering your team to proactively avert data-related issues. Grasping the significance of data application is more crucial than merely focusing on the data itself. With a unified and comprehensive perspective, you can evaluate data quality and lineage effectively. Obtain immediate insights regarding data utilization across various systems, projects, and applications. Instead of getting lost in the growing number of repositories, concentrate on overseeing the data flow. Facilitate the sharing of lineages, schemas, and quality details with catalogs, glossaries, and incident management frameworks. Instantly identify the underlying causes of intricate data problems to stop any potential "datastrophes" from spreading. Set up alerts for specific data events along with their context to stay informed. Gain clarity on how data has been gathered, replicated, and altered by different applications. Identify anomalies by analyzing historical data patterns. Utilize lineage and past data insights to trace back to the original cause, ensuring a comprehensive understanding of your data landscape. This proactive approach not only preserves data integrity but also enhances overall operational efficiency.

Uncover the hidden order within your intricate data landscape and consistently know where to seek solutions. Datakin seamlessly tracks data lineage, presenting your entire data ecosystem through an engaging visual graph. This visualization effectively highlights the upstream and downstream connections associated with each dataset. The Duration tab provides an overview of a job’s performance in a Gantt-style chart, complemented by its upstream dependencies, which simplifies the identification of potential bottlenecks. When it's essential to determine the precise moment a breaking change occurs, the Compare tab allows you to observe how your jobs and datasets have evolved between different runs. Occasionally, jobs that complete successfully may yield poor output. The Quality tab reveals crucial data quality metrics and their fluctuations over time, making anomalies starkly apparent. By facilitating the swift identification of root causes for issues, Datakin also plays a vital role in preventing future complications from arising. This proactive approach ensures that your data remains reliable and efficient in supporting your business needs.

The need for insights derived from data and for innovative solutions has reached unprecedented levels. In the current landscape of global business, maintaining a competitive advantage relies heavily on the capacity to utilize reliable data for making strategic and informed decisions. Sadly, despite the vast amounts of data that many organizations gather, it often goes underutilized because business leaders struggle to locate it or lack the understanding and trust necessary to leverage it effectively. ASG Data Intelligence (ASG DI) addresses this issue of data skepticism through its metadata-centric platform, which enhances the intelligence of technical data by providing comprehensive views of the data lifecycle and its transformations, alongside contextual business relevance. By empowering users across various roles—such as data scientists, analysts, and marketers—data can be harnessed to its full potential when it is accessible, comprehensible, and dependable. Establishing confidence in data is essential, and this is achieved by enhancing the understanding of its origins, the processes it undergoes, and the business context in which it operates. Consequently, organizations can transform their approach to data and drive greater innovation and efficiency.

Explore the exceptional features offered by Global IDs, which provide a comprehensive range of Enterprise Data Solutions including data governance, compliance, cloud migration, rationalization, privacy, analytics, and more. The Global IDs EDA Platform includes essential functionalities such as automated discovery and profiling, data classification, data lineage, and data quality, all aimed at ensuring that data is transparent, reliable, and understandable throughout the ecosystem. Additionally, the architecture of the Global IDs EDA platform is built for seamless integration, enabling access to all its functionalities through APIs. This platform effectively automates data management for organizations of varying sizes and diverse data environments. By utilizing Global IDs EDA, businesses can significantly enhance their data management practices and drive better decision-making.

Oracle Enterprise Metadata Management (OEMM) serves as a robust platform for managing metadata. It is capable of harvesting and cataloging metadata from a wide array of sources, such as relational databases, Hadoop, ETL processes, business intelligence systems, and data modeling tools, among others. Beyond merely acting as a repository for metadata, OEMM facilitates interactive searching and browsing of the data, while also offering features like data lineage tracking, impact analysis, and both semantic definition and usage analysis for any asset in its catalog. With its sophisticated algorithms, OEMM integrates metadata from various providers, creating a comprehensive view of the data journey from its origin to its final report or back. The platform's compatibility extends to numerous metadata sources, including data modeling tools, databases, CASE tools, ETL engines, data warehouses, BI systems, and EAI environments, among many others. This versatility ensures that organizations can effectively manage and utilize their metadata across diverse environments.

Decube is a comprehensive data management platform designed to help organizations manage their data observability, data catalog, and data governance needs. Our platform is designed to provide accurate, reliable, and timely data, enabling organizations to make better-informed decisions. Our data observability tools provide end-to-end visibility into data, making it easier for organizations to track data origin and flow across different systems and departments. With our real-time monitoring capabilities, organizations can detect data incidents quickly and reduce their impact on business operations. The data catalog component of our platform provides a centralized repository for all data assets, making it easier for organizations to manage and govern data usage and access. With our data classification tools, organizations can identify and manage sensitive data more effectively, ensuring compliance with data privacy regulations and policies. The data governance component of our platform provides robust access controls, enabling organizations to manage data access and usage effectively. Our tools also allow organizations to generate audit reports, track user activity, and demonstrate compliance with regulatory requirements.

The contemporary data workspace transforms the accessibility of your data assets, making everything from data tables to BI reports easily discoverable. With our robust search algorithms and user-friendly browsing experience, locating the right asset becomes effortless. Atlan simplifies the identification of poor-quality data through the automatic generation of data quality profiles. This includes features like variable type detection, frequency distribution analysis, missing value identification, and outlier detection, ensuring you have comprehensive support. By alleviating the challenges associated with governing and managing your data ecosystem, Atlan streamlines the entire process. Additionally, Atlan’s intelligent bots analyze SQL query history to automatically construct data lineage and identify PII data, enabling you to establish dynamic access policies and implement top-notch governance. Even those without technical expertise can easily perform queries across various data lakes, warehouses, and databases using our intuitive query builder that resembles Excel. Furthermore, seamless integrations with platforms such as Tableau and Jupyter enhance collaborative efforts around data, fostering a more connected analytical environment. Thus, Atlan not only simplifies data management but also empowers users to leverage data effectively in their decision-making processes.

Rapidly establish cloud environments tailored for spontaneous development, testing, and enhanced productivity for IT and business personnel. Mitigate the risks and expenses associated with managing your data lake by adopting robust data governance practices that include comprehensive end-to-end data lineage for business users. Achieve greater cost efficiency by providing clean, reliable, and timely data for your data lakes, data warehouses, or big data initiatives, while also consolidating applications and phasing out legacy databases. Benefit from automatic schema propagation to accelerate job creation, implement type-ahead search features, and maintain backward compatibility, all while following a design that allows for execution across varied platforms. Develop data integration workflows and enforce governance and quality standards through an intuitive design that identifies and recommends usage trends, thus enhancing user experience. Furthermore, boost visibility and information governance by facilitating complete and authoritative insights into data, backed by proof of lineage and quality, ensuring that stakeholders can make informed decisions based on accurate information. With these strategies in place, organizations can foster a more agile and data-driven culture.

SAP Information Steward software facilitates data profiling, monitoring, and the management of information policies. Acting as the information governance component of the SAP Business Technology Platform, it enables organizations to foresee risks and enhance business results. By integrating data profiling, data lineage, and metadata management, users can achieve ongoing visibility into the reliability of their enterprise data framework. This allows for a deeper comprehension of data quality throughout the data management ecosystem, while providing access to analytical metrics through user-friendly dashboards and scorecards. To advance enterprise information management efforts, it offers unwavering validation rules and guidelines to support analysts, data stewards, and IT professionals alike. With the ability to discover, evaluate, define, oversee, and enhance the quality of your enterprise data assets through data profiling and metadata management, all functions are available in a single solution. Moreover, organizations can simulate potential cost reductions stemming from enhanced data quality by conducting what-if analyses, thus paving the way for informed decision-making. Ultimately, this software not only streamlines processes but also reinforces the significance of maintaining high-quality data.

Limited insight into your data can expose your organization to significant risks. 1touch.io leverages a distinctive network analytics strategy, integrating advanced machine learning and artificial intelligence techniques, along with unmatched accuracy in data lineage, to continuously uncover and catalog all sensitive and protected information into a PII Inventory and a Master Data Catalog. By automatically identifying and analyzing data usage and lineage, we eliminate the need for organizations to be aware of the existence or location of their data. Our sophisticated multilayer machine learning analytic engine enhances our capability to "interpret and comprehend" the data, seamlessly connecting all elements to create a comprehensive overview in both the PII Inventory and the Master Catalog. This process not only facilitates the discovery of both known and unknown sensitive data within your network, leading to immediate risk mitigation, but it also streamlines your data flow, allowing for a clearer understanding of data lineage and business processes, which is essential for meeting crucial compliance standards. By staying ahead of potential data vulnerabilities, organizations can better protect themselves in an increasingly complex regulatory landscape.

Talend Data Catalog provides your organization with a single point of control for all your data. Data Catalog provides robust tools for search, discovery, and connectors that allow you to extract metadata from almost any data source. It makes it easy to manage your data pipelines, protect your data, and accelerate your ETL process. Data Catalog automatically crawls, profiles and links all your metadata. Data Catalog automatically documents up to 80% of the data associated with it. Smart relationships and machine learning keep the data current and up-to-date, ensuring that the user has the most recent data. Data governance can be made a team sport by providing a single point of control that allows you to collaborate to improve data accessibility and accuracy. With intelligent data lineage tracking and compliance tracking, you can support data privacy and regulatory compliance.

The Collibra Data Intelligence Cloud serves as your comprehensive platform for engaging with data, featuring an exceptional catalog, adaptable governance, ongoing quality assurance, and integrated privacy measures. Empower your teams with a premier data catalog that seamlessly merges governance, privacy, and quality controls. Elevate efficiency by enabling teams to swiftly discover, comprehend, and access data from various sources, business applications, BI, and data science tools all within a unified hub. Protect your data's privacy by centralizing, automating, and streamlining workflows that foster collaboration, implement privacy measures, and comply with international regulations. Explore the complete narrative of your data with Collibra Data Lineage, which automatically delineates the connections between systems, applications, and reports, providing a contextually rich perspective throughout the organization. Focus on the most critical data while maintaining confidence in its relevance, completeness, and reliability, ensuring that your organization thrives in a data-driven world. By leveraging these capabilities, you can transform your data management practices and drive better decision-making across the board.

Experience the implications of data-related problems without the need to execute SQL queries. Our approach involves a thorough analysis of your logs and metadata to uncover issues such as freshness and volume discrepancies, changes in table schemas, and errors within pipelines, along with their potential impacts on your business operations. Masthead continuously monitors all tables, processes, scripts, and dashboards in your data warehouse and integrated BI tools, providing immediate alerts to data teams whenever failures arise. It reveals the sources and consequences of data anomalies and pipeline errors affecting consumers of the data. By mapping data problems onto lineage, Masthead enables you to resolve issues quickly, often within minutes rather than spending hours troubleshooting. The ability to gain a complete overview of all operations within GCP without granting access to sensitive data has proven transformative for us, ultimately leading to significant savings in both time and resources. Additionally, you can achieve insights into the expenses associated with each pipeline operating in your cloud environment, no matter the ETL method employed. Masthead is equipped with AI-driven recommendations designed to enhance the performance of your models and queries. Connecting Masthead to all components within your data warehouse takes just 15 minutes, making it a swift and efficient solution for any organization. This streamlined integration not only accelerates diagnostics but also empowers data teams to focus on more strategic initiatives.

In 30 minutes, you can monitor your entire warehouse. Automated warehouse-to-BI lineage can identify downstream impacts. Trust can be lost in seconds and regained in months. With modern data-era observability, you can have peace of mind. It can be difficult to get the coverage you need with code-based tests. They take hours to create and maintain. Metaplane allows you to add hundreds of tests in minutes. Foundational tests (e.g. We support foundational tests (e.g. row counts, freshness and schema drift), more complicated tests (distribution shifts, nullness shiftings, enum modifications), custom SQL, as well as everything in between. Manual thresholds can take a while to set and quickly become outdated as your data changes. Our anomaly detection algorithms use historical metadata to detect outliers. To minimize alert fatigue, monitor what is important, while also taking into account seasonality, trends and feedback from your team. You can also override manual thresholds.

Organizations are increasingly focused on becoming more data-driven, implementing dashboards, analytics, and data pipelines throughout the contemporary data landscape. However, many organizations face significant challenges with data reliability, which can lead to misguided business decisions and a general mistrust in data that negatively affects their financial performance. Addressing intricate data challenges is often a labor-intensive process that requires collaboration among various teams, all of whom depend on informal knowledge to painstakingly reverse engineer complex data pipelines spanning multiple platforms in order to pinpoint root causes and assess their implications. Pantomath offers a solution as a data pipeline observability and traceability platform designed to streamline data operations. By continuously monitoring datasets and jobs within the enterprise data ecosystem, it provides essential context for complex data pipelines by generating automated cross-platform technical pipeline lineage. This automation not only enhances efficiency but also fosters greater confidence in data-driven decision-making across the organization.

HCL CDP stands as a robust solution that aggregates customer information from various sources, offering a comprehensive 360-degree perspective for enhanced insights. Its adaptability in architecture, thorough data lineage features, and adherence to privacy regulations position it as a preferred choice for contemporary businesses. 1. Effortless Scalability: HCL CDP can seamlessly adjust to increasing data volumes, maintaining optimal performance as companies grow, handle additional customer interactions, and merge diverse data sources. 2. Transparency & Compliance: The platform ensures complete visibility in data processing, monitoring data flow to meet requirements of GDPR, CCPA, and other regulations, while its zero-copy data framework boosts security by allowing data access without creating duplicates. 3. Versatile Deployment Options: Featuring choices for on-premise, cloud, and hybrid deployment, HCL CDP grants organizations the flexibility to expand without being tied to a specific vendor. 4. Integration Flexibility: HCL CDP integrates effortlessly with various CRM and marketing automation tools, as well as analytics platforms, making it adaptable to different technological ecosystems. By leveraging such capabilities, businesses can unlock the full potential of their customer data to drive strategic decisions.

Adele is a user-friendly platform that streamlines the process of transferring data pipelines from outdated systems to a designated target platform. It gives users comprehensive control over the migration process, and its smart mapping features provide crucial insights. By reverse-engineering existing data pipelines, Adele generates data lineage maps and retrieves metadata, thereby improving transparency and comprehension of data movement. This approach not only facilitates the migration but also fosters a deeper understanding of the data landscape within organizations.

SYNQ serves as a comprehensive data observability platform designed to assist contemporary data teams in defining, overseeing, and managing their data products effectively. By integrating ownership dynamics, testing processes, and incident management workflows, SYNQ enables teams to preemptively address potential issues, minimize data downtime, and expedite the delivery of reliable data. With SYNQ, each essential data product is assigned clear ownership and offers real-time insights into its operational health, ensuring that when problems arise, the appropriate individuals are notified with the necessary context to quickly comprehend and rectify the situation. At the heart of SYNQ lies Scout, an autonomous data quality agent that is perpetually active. Scout not only monitors data products but also recommends testing strategies, performs root-cause analysis, and resolves issues effectively. By linking data lineage, historical issues, and contextual information, Scout empowers teams to address challenges more swiftly. Moreover, SYNQ seamlessly integrates with existing tools, earning the trust of prominent scale-ups and enterprises including VOI, Avios, Aiven, and Ebury, thereby solidifying its reputation in the industry. This robust integration ensures that teams can leverage SYNQ without disrupting their established workflows, further enhancing their operational efficiency.

The Bloomberg Enterprise Catalog offers a meticulously organized collection of more than 40,000 data fields, centralizing a wide range of enterprise datasets such as reference, regulatory, pricing, ESG, and alternative data, along with real-time market feeds, funds details, and investment research, all available through a single, API-compatible source that features customizable dashboards and integration connectors. Users are empowered to conduct natural-language and field-specific searches, subscribe to desired datasets, and visualize aspects like data lineage, usage metrics, and quality scores, with historical coverage that spans decades, facilitating back-testing, trend analysis, regulatory compliance, and model validation. Data is accessible through desktop interfaces, terminals, or RESTful APIs, and integrates effortlessly with business intelligence tools, cloud storage solutions, and data lakes, providing a variety of delivery options that range from tick-level pricing to larger aggregated statistics. To ensure high standards, the system incorporates rigorous quality controls, standardized identifiers, and enterprise-grade service level agreements (SLAs) that guarantee consistency, accuracy, and uptime, thereby enhancing user confidence in their data-driven decisions. This comprehensive approach not only streamlines data management but also supports organizations in harnessing the full potential of their data assets.

ER/Studio Enterprise Team Edition allows data modelers and architects the ability to share data models and metadata throughout an enterprise. It offers a complete solution to enterprise architecture and data governance.

Amazon QLDB is a fully managed ledger database that offers a transparent, immutable, and cryptographically verifiable transaction log governed by a central trusted authority. This powerful tool allows users to monitor every change made to application data while preserving a complete and verifiable history of alterations over time. Typically, ledgers serve to document the economic and financial activities within an organization. Many businesses create applications with ledger-like features to ensure they have an accurate record of their data history; this includes tracking the flow of credits and debits in banking transactions, validating the data lineage for insurance claims, or following the movement of goods in a supply chain. By utilizing Amazon QLDB, organizations can avoid the intricate development challenges associated with creating their own ledger-like systems, streamlining their processes and enhancing data integrity. This innovative database solution ultimately empowers businesses to focus on their core activities while ensuring robust data management.

Dataform provides a platform for data analysts and engineers to create and manage scalable data transformation pipelines in BigQuery using solely SQL from a single, integrated interface. The open-source core language allows teams to outline table structures, manage dependencies, include column descriptions, and establish data quality checks within a collective code repository, all while adhering to best practices in software development, such as version control, various environments, testing protocols, and comprehensive documentation. A fully managed, serverless orchestration layer seamlessly oversees workflow dependencies, monitors data lineage, and executes SQL pipelines either on demand or on a schedule through tools like Cloud Composer, Workflows, BigQuery Studio, or external services. Within the browser-based development interface, users can receive immediate error notifications, visualize their dependency graphs, link their projects to GitHub or GitLab for version control and code reviews, and initiate high-quality production pipelines in just minutes without exiting BigQuery Studio. This efficiency not only accelerates the development process but also enhances collaboration among team members.

Successful enterprises often share key characteristics: enhancing operational efficiencies, managing risks, increasing revenue, and driving rapid innovation. Data360 Analyze provides the quickest means to consolidate and structure extensive datasets, revealing crucial insights across various business divisions. Users can effortlessly access, prepare, and analyze high-quality data via its user-friendly web-based interface. Gaining a comprehensive grasp of your organization's data environment can illuminate various data sources, including those that are incomplete, erroneous, or inconsistent. This platform enables the swift identification, validation, transformation, and integration of data from all corners of your organization, ensuring the delivery of precise, pertinent, and reliable information for thorough analysis. Moreover, features like visual data examination and tracking empower users to monitor and retrieve data at any stage of the analytical workflow, fostering collaboration among stakeholders and enhancing confidence in the data and findings produced. In doing so, organizations can make more informed decisions based on trustworthy insights derived from robust data analysis.

Locus offers an efficient platform for in-depth analysis of geospatial data, catering to a diverse audience that ranges from marketers who may struggle with technology to data scientists and analysts performing complex queries, as well as executives seeking critical metrics for future success. This approach ensures a highly secure and smooth method for linking various data sources or your data lake to LOCUS. Additionally, the Connection Hub features integrated data lineage governance and transformation tools, enhancing compatibility with resources like LOCUS Notebook and LOCUS QL. EQ utilizes a directed acyclic graph processor built on the well-known Apache Airflow framework, designed to optimize geospatial workflows. The DAG Builder is specifically crafted to effectively manage and streamline your geospatial processes with over twenty built-in assistance stages, making it a versatile tool in the data analysis arsenal. In this way, Locus not only simplifies data interaction but also empowers users to make informed decisions based on comprehensive insights.