Azure Purview is Microsoft's cloud-native data governance service that provides unified data discovery, cataloging, and classification across hybrid and multi-cloud environments. It automates the extraction of metadata at scale and identifies data lineage between sources. The service includes a data map, data catalog, and data insights. The data map automates metadata scanning and lineage tracking. The data catalog enables effortless discovery and browsing of classified data. Data insights provides governance reporting across the data estate.
Organizations are grappling to manually classify and create an inventory for distributed and heterogeneous data assets to deliver value. However, the new Azure service for enterprises – Azure Synapse Analytics is poised to help organizations and fill the gap between data warehouses and data lakes.
Want to see a high-level overview of the products in the Microsoft data platform portfolio in Azure? I’ll cover products in the categories of OLTP, OLAP, data warehouse, storage, data transport, data prep, data lake, IaaS, PaaS, SMP/MPP, NoSQL, Hadoop, open source, reporting, machine learning, and AI. It’s a lot to digest but I’ll categorize the products and discuss their use cases to help you narrow down the best products for the solution you want to build.
Azure Data Factory | Moving On-Premise Data to Azure Cloud | Microsoft Azure ...Edureka!
** Microsoft Azure Certification Training : https://www.edureka.co/microsoft-azure-training **
This Edureka "Azure Data Factory” tutorial will give you a thorough and insightful overview of Microsoft Azure Data Factory and help you understand other related terms like Data Lakes and Data Warehousing.
Following are the offering of this tutorial:
1. Why Azure Data Factory?
2. What Is Azure Data Factory?
3. Data Factory Concepts
4. What is Azure Data Lake?
5. Data Lake Concepts
6. Data Lake Vs Data Warehouse
7. Demo- Moving On-Premise Data To Cloud
Check out our Playlists: https://goo.gl/A1CJjM
Azure Synapse Analytics is Azure SQL Data Warehouse evolved: a limitless analytics service, that brings together enterprise data warehousing and Big Data analytics into a single service. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources, at scale. Azure Synapse brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate business intelligence and machine learning needs. This is a huge deck with lots of screenshots so you can see exactly how it works.
Part 3 - Modern Data Warehouse with Azure SynapseNilesh Gule
Slide deck of the third part of building Modern Data Warehouse using Azure. This session covered Azure Synapse, formerly SQL Data Warehouse. We look at the Azure Synapse Architecture, external files, integration with Azuer Data Factory.
The recording of the session is available on YouTube
https://www.youtube.com/watch?v=LZlu6_rFzm8&WT.mc_id=DP-MVP-5003170
Azure Synapse Analytics is Azure SQL Data Warehouse evolved: a limitless analytics service, that brings together enterprise data warehousing and Big Data analytics into a single service. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources, at scale. Azure Synapse brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate business intelligence and machine learning needs. This is a huge deck with lots of screenshots so you can see exactly how it works.
Azure Days 2019: Business Intelligence auf Azure (Marco Amhof & Yves Mauron)Trivadis
In dieser Session stellen wir ein Projekt vor, in welchem wir ein umfassendes BI-System mit Hilfe von Azure Blob Storage, Azure SQL, Azure Logic Apps und Azure Analysis Services für und in der Azure Cloud aufgebaut haben. Wir berichten über die Herausforderungen, wie wir diese gelöst haben und welche Learnings und Best Practices wir mitgenommen haben.
Organizations are grappling to manually classify and create an inventory for distributed and heterogeneous data assets to deliver value. However, the new Azure service for enterprises – Azure Synapse Analytics is poised to help organizations and fill the gap between data warehouses and data lakes.
Want to see a high-level overview of the products in the Microsoft data platform portfolio in Azure? I’ll cover products in the categories of OLTP, OLAP, data warehouse, storage, data transport, data prep, data lake, IaaS, PaaS, SMP/MPP, NoSQL, Hadoop, open source, reporting, machine learning, and AI. It’s a lot to digest but I’ll categorize the products and discuss their use cases to help you narrow down the best products for the solution you want to build.
Azure Data Factory | Moving On-Premise Data to Azure Cloud | Microsoft Azure ...Edureka!
** Microsoft Azure Certification Training : https://www.edureka.co/microsoft-azure-training **
This Edureka "Azure Data Factory” tutorial will give you a thorough and insightful overview of Microsoft Azure Data Factory and help you understand other related terms like Data Lakes and Data Warehousing.
Following are the offering of this tutorial:
1. Why Azure Data Factory?
2. What Is Azure Data Factory?
3. Data Factory Concepts
4. What is Azure Data Lake?
5. Data Lake Concepts
6. Data Lake Vs Data Warehouse
7. Demo- Moving On-Premise Data To Cloud
Check out our Playlists: https://goo.gl/A1CJjM
Azure Synapse Analytics is Azure SQL Data Warehouse evolved: a limitless analytics service, that brings together enterprise data warehousing and Big Data analytics into a single service. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources, at scale. Azure Synapse brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate business intelligence and machine learning needs. This is a huge deck with lots of screenshots so you can see exactly how it works.
Part 3 - Modern Data Warehouse with Azure SynapseNilesh Gule
Slide deck of the third part of building Modern Data Warehouse using Azure. This session covered Azure Synapse, formerly SQL Data Warehouse. We look at the Azure Synapse Architecture, external files, integration with Azuer Data Factory.
The recording of the session is available on YouTube
https://www.youtube.com/watch?v=LZlu6_rFzm8&WT.mc_id=DP-MVP-5003170
Azure Synapse Analytics is Azure SQL Data Warehouse evolved: a limitless analytics service, that brings together enterprise data warehousing and Big Data analytics into a single service. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources, at scale. Azure Synapse brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate business intelligence and machine learning needs. This is a huge deck with lots of screenshots so you can see exactly how it works.
Azure Days 2019: Business Intelligence auf Azure (Marco Amhof & Yves Mauron)Trivadis
In dieser Session stellen wir ein Projekt vor, in welchem wir ein umfassendes BI-System mit Hilfe von Azure Blob Storage, Azure SQL, Azure Logic Apps und Azure Analysis Services für und in der Azure Cloud aufgebaut haben. Wir berichten über die Herausforderungen, wie wir diese gelöst haben und welche Learnings und Best Practices wir mitgenommen haben.
Enroll in our Azure Data Engineering Course in Hyderabad to gain in-depth knowledge of Microsoft Azure's powerful data processing capabilities. Learn essential skills such as data ingestion, storage, and analytics using Azure services. Our hands-on training, led by industry experts, will equip you with the expertise needed to design and implement robust data solutions. Prepare for a successful career in data engineering with our specialized course in the heart of Hyderabad. Enroll in our Azure Data Engineering Course in Hyderabad to gain in-depth knowledge of Microsoft Azure's powerful data processing capabilities. Learn essential skills such as data ingestion, storage, and analytics using Azure services. Our hands-on training, led by industry experts, will equip you with the expertise needed to design and implement robust data solutions. Prepare for a successful career in data engineering with our specialized course in the heart of Hyderabad. Enroll in our Azure Data Engineering Course in Hyderabad to gain in-depth knowledge of Microsoft Azure's powerful data processing capabilities. Learn essential skills such as data ingestion, storage, and analytics using Azure services. Our hands-on training, led by industry experts, will equip you with the expertise needed to design and implement robust data solutions. Prepare for a successful career in data engineering with our specialized course in the heart of Hyderabad. Enroll in our Azure Data Engineering Course in Hyderabad to gain in-depth knowledge of Microsoft Azure's powerful data processing capabilities. Learn essential skills such as data ingestion, storage, and analytics using Azure services. Our hands-on training, led by industry experts, will equip you with the expertise needed to design and implement robust data solutions. Prepare for a successful career in data engineering with our specialized course in the heart of Hyderabad.
Big Data and Data Warehousing Together with Azure Synapse Analytics (SQLBits ...Michael Rys
SQLBits 2020 presentation on how you can build solutions based on the modern data warehouse pattern with Azure Synapse Spark and SQL including demos of Azure Synapse.
Comparing Microsoft Big Data Platform TechnologiesJen Stirrup
In this segment, we look at technologies such as HDInsight, Azure Databricks, Azure Data Lake Analytics and Apache Spark. We compare the technologies to help you to decide the best technology for your situation.
Turn Data into Business Value – Starting with Data Analytics on Oracle Cloud ...Lucas Jellema
Data Science, Business Intelligence, Data Lake, Machine Learning and AI. Diverse terminology with a common goal: leverage data to realize business value. Through consolidated insight and automated processing, predictions, recommendations and actions. Using visualizations, dashboards, reports, alerts, machine learning models. Based on data. Data retrieved from raw sources into a data lake, wrangled into cleansed, enriched, anonymized and aggregated data sets and turned into business intelligence or used for training machine learning models, that in turn power Smart Applications. This session walks the audience through the start to end data flow on Oracle Autonomous Data Warehouse, Analytics Cloud, Big Data Cloud & Data Integration Platform.
Azure Synapse is Microsoft's new cloud analytics service offering that combines enterprise data warehouse and Big Data analytics capabilities. It offers a powerful and streamlined platform to facilitate the process of consolidating, storing, curating and analysing your data to generate reliable and actionable business insights.
Enroll in our Azure Data Engineering Course in Hyderabad to gain in-depth knowledge of Microsoft Azure's powerful data processing capabilities. Learn essential skills such as data ingestion, storage, and analytics using Azure services. Our hands-on training, led by industry experts, will equip you with the expertise needed to design and implement robust data solutions. Prepare for a successful career in data engineering with our specialized course in the heart of Hyderabad.
How to Architect a Serverless Cloud Data Lake for Enhanced Data AnalyticsInformatica
This presentation is geared toward enterprise architects and senior IT leaders looking to drive more value from their data by learning about cloud data lake management.
As businesses focus on leveraging big data to drive digital transformation, technology leaders are struggling to keep pace with the high volume of data coming in at high speed and rapidly evolving technologies. What's needed is an approach that helps you turn petabytes into profit.
Cloud data lakes and cloud data warehouses have emerged as a popular architectural pattern to support next-generation analytics. Informatica's comprehensive AI-driven cloud data lake management solution natively ingests, streams, integrates, cleanses, governs, protects and processes big data workloads in multi-cloud environments.
Please leave any questions or comments below.
Azure Key Vault, Azure Dev Ops and Azure Synapse - how these services work pe...Erwin de Kreuk
Can we store our Connectionstrings or BlobStorageKeys or other Secretvalues somewhere else then in Azure Synapse Pipelines? Yes you can! You can store these valuable secrets in Azure Key Vault(AKV).
• But how can we achieve this in Azure Synapse Analytics?
• How do we deploy our Synapse Pipelines in Azure Dev Ops to Test, Acceptance and Production environments with these Secrets ?
• Can this be setup dynamically?
During this session I will give answers on all these questions. You will learn how to setup your Azure Key Vault, connect these secrets in Azure Synapse Analytics and finally deploy these secrets dynamically in Azure Dev Ops. As you can see a lot to talk about during this session.
Lake Database Database Template Map Data in Azure Synapse AnalyticsErwin de Kreuk
Database templates in Synapse Analytics are blueprints which can be used by organizations to plan, architect and design solutions.
How can we use these Database Templates in a day-to-day business, in order to speed up to automate this process?
Map data tool can help us with that
Dealing with different Synapse Roles in Azure Synapse Analytics Erwin de KreukErwin de Kreuk
Azure Synapse Analytics is Microsoft's analytical engine that brings together data integration, enterprise data warehousing and big data analytics. It uses a holistic approach which means that different user personas will use Azure Synapse.
• How do you deal with these different user personas and the different roles within Azure Synapse Analytics? For example, what is a Data Scientist or Data Engineer allowed to do and what not?
• What roles do we need to store the code in DevOps, to debug a pipeline or to execute a Notebook?
I would like to take you through some practical examples on how you can best set up these roles for your Azure Synapse environment.
Is there a way that we can build our Azure Synapse Pipelines all with paramet...Erwin de Kreuk
Is there a way that we can build our Synapse Data Pipelines all with parameters all based on MetaData? Yes there's and I will show you how to. During this session I will show how you can load Incremental or Full datasets from your sql database to your Azure Data Lake. The next step is that we want to track our history from these extracted tables. We will do using Delta Lake. The last step that we want, is to make this data available in Azure SQL Database or Azure Synapse Analytics. Oh and we want to have some logging as well from our processes A lot to talk and to demo about during this session.
Is there a way that we can build our Azure Data Factory all with parameters b...Erwin de Kreuk
Is there a way that we can build our Data Factory all with parameters all based on MetaData? Yes there's and I will show you how to. During this session I will show how you can load Incremental or Full datasets from your sql database to your Azure Data Lake. The next step is that we want to track our history from these extracted tables. We will do this with Azure Databricks using Delta Lake. The last step that we want, is to make this data available in Azure SQL Database or Azure Synapse Analytics. Oh and we want to have some logging as well from our processes A lot to talk and to demo about during this session.
SQL KONFERENZ 2020 Azure Key Vault, Azure Dev Ops and Azure Data Factory how...Erwin de Kreuk
Can we store our Connectionstrings or BlobStorageKeys or other Secretvalues somewhere else then in Azure Data Factory(ADF)? Yes you can! You can store these valuable secrets in Azure Key Vault(AKV).
But how can we achieve this in ADF? And finally how do we deploy our DataFactories in Azure Dev Ops to Test, Acceptance and Production environments with these Secrets ? Can this be setup dynamically?
During this session I will give answers on all of these questions. You will learn how to setup your Azure Key Vault, connect these secrets in ADF and finally deploy these secrets dynamically in Azure Dev Ops. As you can see a lot to talk about during this session.
DatamindsConnect2019 Azure Key Vault, Azure Dev Ops and Azure Data Factory ho...Erwin de Kreuk
Can we store our Connectionstrings or BlobStorageKeys or other Secretvalues somewhere else then in Azure Data Factory(ADF)? Yes you can! You can store these valuable secrets in Azure Key Vault(AKV).
But how can we achieve this in ADF? And finally how do we deploy our DataFactories in Azure Dev Ops to Test, Acceptance and Production environments with these Secrets ? Can this be setup dynamically?
During this session I will give answers on all of these questions. You will learn how to setup your Azure Key Vault, connect these secrets in ADF and finally deploy these secrets dynamically in Azure Dev Ops. As you can see a lot to talk about during this session.
Help, I need to migrate my On Premise Database to Azure, which Database Tier ...Erwin de Kreuk
During this session we will walk you through all the different Tiers in Azure, DTU, Vcore, Serverless and Managed Instance and will provide examples when to use which Tier.
We will also show you the Microsoft Data Migration Assesment (DMA). This tool will help you to decide which tier you should choose. So if you need help or just interested in the different Azure Database Tiers then visit our session
DataSaturdayNL 2019 Azure Key Vault, Azure Dev Ops and Azure Data Factory h...Erwin de Kreuk
Can we store our Connectionstrings or BlobStorageKeys or other Secretvalues somewhere else then in Azure Data Factory(ADF)? Yes you can! You can store these valuable secrets in Azure Key Vault(AKV). But how can we achieve this in ADF? And finally how do we deploy our DataFactories in Azure Dev Ops to Test, Acceptance and Production environments with these Secrets ? Can this be setup dynamically? During this session I will give answers on all of these questions. You will learn how to setup your Azure Key Vault, connect these secrets in ADF and finally deploy these secrets dynamically in Azure Dev Ops. As you can see a lot to talk about during this session.
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
6. InSpark
Data governance is becoming increasingly
interdisciplinary
What data do I have?
Where did the data originate?
Can I trust it?
DISCOVERY
What’s my exposure to risk?
Is my usage compliant?
How do I control access & use?
What is required by regulation X?
COMPLIANCE
ChiefDataOfficer
8. InSpark
Data Map
Multicloud
On-prem
Data Insights
Azure Purview
Data Catalog
SaaS
Data Map
Automate and manage metadata at scale
Data Catalog
Enable effortless discovery for data
consumers
Data Insights
Assess data usage across your
organization
9. InSpark
Unified data governance to
maximize the business
value of data
Azure Purview
Reimagine data
governance in the cloud
Set the foundation for
effective data governance
Maximize business value
of data for data
consumers
Gain insight into data use
across the estate
10. InSpark
Manage and govern operational,
transactional and analytical data
Cloud-native, purpose-built
service to address discovery and
compliance needs
Fully managed, serverless, PaaS
service
Eliminate manual, ad-hoc and
homegrown solutions
Reimagine data
governance in the cloud
11. InSpark
Automate discovery of data in on-
premises, multicloud and SaaS
sources
Classify data at scale to specify
sensitivity, compliance, industry,
business and company-specific
value
Know where data came from and
what was derived from it with
data lineage
Set the foundation for
effective data governance
12. InSpark
Connect business and technical
data analysts, data scientists, and
data engineers to a trusted data
catalog
Enable users to quickly find data
and view its lineage and
sensitivity
Deliver a curated and consistent
glossary of business terms and
definitions
Maximize business value
of data for data
consumers
13. InSpark
Understand at a glance how data
is being created and used across
your data estate
Visually assess the state of data
assets, scans, business glossary
and sensitive data
Gain insight into data use
across the estate
14. InSpark
Azure Purview Features
Azure Purview
Azure Purview Platform
Azure Purview Studio
Automated Scanning & Classification
• Dedicated per customer on shared infra
• Provisioned default capacity with option to add-on capacity
Data Map
• Serverless, pay per use
• Includes connectors, scanning of sources, processing into data assets, lineage capture, classification
• Search, browse, asset details
• Automated meta-data and lineage extraction
• Automated classification based on content inspection
• Private Endpoint
• Management center
On-prem & Multi-cloud Operational, Analytical, SaaS
Azure Purview Catalog included with Platform (C0)
Power BI
SQL Server on-prem
Azure Synapse
Azure Data Services
M365 Compliance Cen
Open APIs
(Apache Atlas 2.0)
15. InSpark
Azure Purview Features
Azure Purview
Azure Purview Platform
Azure Purview Studio
Azure Purview Catalog (C1)
Automated Scanning & Classification
• Dedicated per customer on shared infra
• Provisioned default capacity with option to add-on capacity
Data Map
• Serverless, pay per use
• Includes connectors, scanning of sources, processing into data assets, lineage capture, classification
• Search, browse, asset details
• Automated meta-data and lineage extraction
• Automated classification based on content inspection
• Private Endpoint
• Management center
On-prem & Multi-cloud Operational, Analytical, SaaS
• Business Glossary templates
• Lineage visualization & workflows
Azure Purview Catalog included with Platform (C0)
Data Producers &
Consumers
Open APIs
(Apache Atlas 2.0)
Power BI
SQL Server on-prem
Azure Synapse
Azure Data Services
M365 Compliance Cen
16. InSpark
Azure Purview Features
Azure Purview
Azure Purview Platform
Azure Purview Studio
Azure Purview Catalog (C1)
Automated Scanning & Classification
• Dedicated per customer on shared infra
• Provisioned default capacity with option to add-on capacity
Data Map
• Serverless, pay per use
• Includes connectors, scanning of sources, processing into data assets, lineage capture, classification
• Search, browse, asset details
• Automated meta-data and lineage extraction
• Automated classification based on content inspection
• Private Endpoint
• Management center
On-prem & Multi-cloud Operational, Analytical, SaaS
Azure Purview Data Insights (D1)
• Business Glossary templates
• Lineage visualization & workflows
Azure Purview Catalog included with Platform (C0)
• Catalog Insights (Asset, Scan, Glossary)
• Sensitive Information Types & Labeling insights
Data Producers &
Consumers
Data Officers &
Security Officers
Open APIs
(Apache Atlas 2.0)
Power BI
SQL Server on-prem
Azure Synapse
Azure Data Services
M365 Compliance Cen
17. InSpark
• No access to Purview Portal
• Can Manage all aspects of Scanning
• Ideal role for programmatic processes, such as service principals
• Can register Data Sources
Azure Purview - Roles
Data Source Administrator
18. InSpark
• Has access to Purview Portal
• Can read all content in Azure Purview
Azure Purview - Roles
Data Reader
Data Source Administrator
19. InSpark
• Has access to Purview Portal
• Can read all content in Azure Purview
• Can edit assets, classification and glossary terms
• Can apply classifications and glossary terms to assets.
• Can not Register Data Sources, only read
Azure Purview - Roles
Data Reader
Data Curator
Data Source Administrator
21. InSpark
Azure Purview Studio Updates Accounts Notifications
Feedback
Metrics
Search Bar
Usefull Links
Recently
Accessed Entities
Search Bar
Key Actvities
22. InSpark
• Quick Actions, recently accessed items, owned Items, search bar and
Documentation
Azure Purview Studio - Activity hubs
• Create collections, register data sources and setup Scans
• Manage Glossary Items, search, manage terms templates and custom
attributes, import and export Terms using csv
• Insights on your data
• Meta Data Management-classifications-resource sets, data sources, integration
runtime, Alerts, Security, ADF and data share Connections
26. InSpark
Purview Data Map
Unify and make data meaningful
Automated metadata scanning and
lineage identification of hybrid
data stores
100+ built-in and custom classifiers
Microsoft Information Protection
sensitivity labels
27. InSpark
Purview Data Map
Automated metadata scanning and
lineage identification of hybrid
data stores
100+ built-in and custom classifiers
Microsoft Information Protection
sensitivity labels
Unify and make data meaningful
28. InSpark
Azure Purview Data Catalog
Enable effortless discovery
Semantic search and
browse
Business glossary and
workflows
Data lineage with sources,
owners, transformations,
and lifecycle
37. InSpark
Azure Purview
Features in Public Preview
Purview Data Map
Available
Now
Coming
Soon
Automated scanning of hybrid sources AWS S3
Classification
Microsoft Information Protection Sensitivity Labels
support
Apache Atlas API support
Purview Data Catalog
Semantic Search and Browse
Business Glossary Hierarchical
Data Lineage
Purview in Azure Synapse workspaces
Purview data insights
Assets and Scans Reports
Glossary reports
Classification and Labelling Reports
Asset-level drill down by sensitivity
Data Sources
Azure Synapse
Azure DataBricks
SAP EEC / Hana
Teradata
Hive Metastore
Data Lineage
Notebook support
Delta Lake Support