Best Data Lineage Tools for Microsoft Power BI

Microsoft Purview is a unified data governance service that helps you manage and govern your on-premises, multicloud, and software-as-a-service (SaaS) data. You can easily create a comprehensive, up-to date map of your data landscape using automated data discovery, sensitive classification, and end to end data lineage. Data consumers can find trustworthy, valuable data. Automated data discovery, lineage identification and data classification across on and off-premises, multicloud, as well as SaaS sources. For more effective governance, a unified map of all your data assets and their relationships. Semantic search allows data discovery using technical or business terms. Get insight into the movement and location of sensitive data in your hybrid data landscape. Purview Data Map will help you establish the foundation for data usage and governance. Automate and manage metadata from mixed sources. Use built-in and customized classifiers to classify data and Microsoft Information Protection sensitive labels to protect it.

Datameer is your go-to data tool for exploring, preparing, visualizing, and cataloging Snowflake insights. From exploring raw datasets to driving business decisions – an all-in-one tool.

Y42 is the first fully managed Modern DataOps Cloud for production-ready data pipelines on top of Google BigQuery and Snowflake.

Unlike most data management systems, PHEMI Health DataLab is built with Privacy-by-Design principles, not as an add-on. This means privacy and data governance are built-in from the ground up, providing you with distinct advantages: Lets analysts work with data without breaching privacy guidelines Includes a comprehensive, extensible library of de-identification algorithms to hide, mask, truncate, group, and anonymize data. Creates dataset-specific or system-wide pseudonyms enabling linking and sharing of data without risking data leakage. Collects audit logs concerning not only what changes were made to the PHEMI system, but also data access patterns. Automatically generates human and machine-readable de- identification reports to meet your enterprise governance risk and compliance guidelines. Rather than a policy per data access point, PHEMI gives you the advantage of one central policy for all access patterns, whether Spark, ODBC, REST, export, and more

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.

Secoda AI can help you generate documentation and queries from your metadata. This will save your team hundreds of hours of tedious work. Secoda AI will also generate documentation and queries based on your metadata. This will save your team hundreds of tedious hours and redundant data requests. Search across all columns, dashboards and metrics, as well as tables, dashboards and tables. AI-powered searches allow you to ask any question and receive a contextual response quickly. Answer questions. Our API allows you to integrate data discovery into your workflow, without disrupting the flow. Perform bulk updates, tag PII, manage tech debt and more. Eliminate manual errors and have complete trust in your knowledge base.

Multi-cloud data security with a single pane of glass Industry's first SaaS access governance solution. Cloud is fragmented and data is scattered across different systems. Sensitive data is difficult to access and control due to limited visibility. Complex data onboarding hinders data scientist productivity. Data governance across services can be manual and fragmented. It can be time-consuming to securely move data to the cloud. Maximize visibility and assess the risk of sensitive data distributed across multiple cloud service providers. One system that enables you to manage multiple cloud services' data policies in a single place. Support RTBF, GDPR and other compliance requests across multiple cloud service providers. Securely move data to the cloud and enable Apache Ranger compliance policies. It is easier and quicker to transform sensitive data across multiple cloud databases and analytical platforms using one integrated system.

AnalyticsCreator lets you extend and adjust an existing DWH. It is easy to build a solid foundation. The reverse engineering method of AnalyticsCreator allows you to integrate code from an existing DWH app into AC. So, more layers/areas are included in the automation. This will support the change process more extensively. The extension of an manually developed DWH with an ETL/ELT can quickly consume resources and time. Our experience and studies found on the internet have shown that the longer the lifecycle the higher the cost. You can use AnalyticsCreator to design your data model and generate a multitier data warehouse for your Power BI analytical application. The business logic is mapped at one place in AnalyticsCreator.

Bluetab Solutions developed Truedat, an open-source data governance business solution tool. It was created to help our clients become data-driven businesses. We assist in defining business processes, roles and responsibilities. We can also help you put these processes into action. Integration and customization of truedat’s open-source components to support data governance processes. We guarantee the maintenance and support of the solution modules we have installed. Based on our extensive experience, we have created a solution that addresses the need for Data Governance. This allows you to manage complex and changing data architectures. Truedat is becoming more important due to the increasing migration of enterprise IT platforms into cloud, multi-cloud, hybrid architectures. This increases the complexity, sources, and types of data. Our Data Governance consulting and development experience spans more than 8 years.

Automate the automatic coverage of thousands of tables using ML-based anomaly detection. 50+ custom metrics are also available. Monitoring of metadata and data. Comprehensive mapping of all dependencies between assets from ingestion to reporting. Collaboration between data consumers and data engineers is enhanced and productivity is increased. Sifflet integrates seamlessly with your data sources and preferred tools. It can run on AWS and Google Cloud Platform as well as Microsoft Azure. Keep an eye on your data's health and notify the team if quality criteria are not being met. In a matter of seconds, you can set up the basic coverage of all your tables. You can set the frequency, criticality, and even custom notifications. Use ML-based rules for any anomaly in your data. There is no need to create a new configuration. Each rule is unique because it learns from historical data as well as user feedback. A library of 50+ templates can be used to complement the automated rules.

Dremio provides lightning-fast queries as well as a self-service semantic layer directly to your data lake storage. No data moving to proprietary data warehouses, and no cubes, aggregation tables, or extracts. Data architects have flexibility and control, while data consumers have self-service. Apache Arrow and Dremio technologies such as Data Reflections, Columnar Cloud Cache(C3), and Predictive Pipelining combine to make it easy to query your data lake storage. An abstraction layer allows IT to apply security and business meaning while allowing analysts and data scientists access data to explore it and create new virtual datasets. Dremio's semantic layers is an integrated searchable catalog that indexes all your metadata so business users can make sense of your data. The semantic layer is made up of virtual datasets and spaces, which are all searchable and indexed.