Modern data estates are spread across data located on premises, on the edge and in one or more public clouds, spread across various sources like multiple relational databases, file and storage systems, and no-SQL systems, both operational and analytic; this phenomenon is referred to as data sprawl. Data administrators who wish to enforce compliance across the entire organization have to inventory their data, identify what parts of it are sensitive, and govern the sensitive data appropriately --- across the entirety of their sprawling data estate. Today, governance of data is completely siloed; each of the data subsystems has its own (and varied) governance features. Policies applied to sensitive data are applied piece-meal by iterating over all the data sources in a custom language specific to each source. This makes data governance cumbersome, error-prone (because a given policy must be manually enforced across different subsystems, inconsistencies can easily arise), and expensive. This paper presents Microsoft Purview , a service for unified governance of the entire data estate of an organization from a single central pane of glass. The Purview service consists of three parts: (1) a Data Map or metadata catalog that is populated by automated scanning of data sources in the organization, (2) a system to store and manage sensitivity classification of data, and (3) a policy system that enables data security officers to author and implement policies that span the entire organization, e.g., a policy that says, "Non-full-time employees should be denied access to data classified as PII (Personally Identifiable Information.") Purview transforms data governance across a complex data estate by offering the ability to govern centrally and automating data discovery, classification and policy enforcement. While other commercial catalog systems also build a global catalog, Purview is unique in its support for policies. It is also distinguished by covering both structured and unstructured data, thanks to its deep integration with Office 365 and its governance framework; indeed, "Microsoft Purview" represents a new unified offering that combines Office 365 governance and what was formerly a service for governing structured data called "Azure Purview". By integrating with Office 365's Rights Management Service, Purview offers central governance over structured data stored in databases and stores, reports in systems such as Power BI, as well as document data stored in Office 365. The Purview vision is to make the metadata in the Data Map increasingly richer through further automation and curation support and to use this 360 degree view of the data estate to support a wide range of governance policies, ranging from access control to lifecycle management (e.g., retention, deletion, restricting data movement). This paper covers the design and implementation challenges in building the Purview service for Attribute-Based Access Control (ABAC) policies, focusing specifically on a detailed description of its integration with Azure SQL Database. We illustrate the power of unifying Office 365 governance with structured data governance through Purview policies that enforce consistent access control even as data flows between Office 365 and structured data engines like Azure SQL Database. We also describe the results of our empirical evaluation of the performance overheads imposed by Purview.

SQL Ledger is a new technology that allows cryptographically verifying the integrity of relational data stored in Azure SQL Database and SQL Server. This is achieved by maintaining all historical data in the database and persisting its cryptographic (SHA-256) digests in an immutable, tamper-evident ledger. Digests representing the overall state of the ledger can then be extracted and stored outside of the RDBMS to protect the data from any attacker or high privileged user, including DBAs, system and cloud administrators. The ledger and the historical data are managed transparently, offering protection without any application changes. Historical data is maintained in a relational form to support SQL queries for auditing, forensics and other purposes. SQL Ledger provides cryptographic data integrity guarantees while maintaining the power, flexibility and performance of a commercial RDBMS. In contrast to Blockchain solutions that aim for full integrity, SQL Ledger offers a form of integrity protection known as Forward Integrity. The proposed technology is significantly cheaper and more secure than traditional solutions that establish trust based on audits or mediators, but also has substantial advantages over Blockchain solutions that are complex to deploy, lack data management capabilities and suffer in terms of performance due to their decentralized nature.

This paper presents Always Encrypted, a recently released feature of Microsoft SQL Server that uses column granularity encryption to provide cryptographic data protection guarantees. Always Encrypted can be used to outsource database administration while keeping the data confidential from an administrator, including cloud operators. The first version of Always Encrypted was released in Azure SQL Database and as part of SQL Server 2016, and supported equality operations over deterministically encrypted columns. The second version, released as part of SQL Server 2019, uses an enclave running within a trusted execution environment to provide richer functionality that includes comparison and string pattern matching for an IND-CPA-secure (randomized) encryption scheme. We present the security, functionality, and design of Always Encrypted, and provide a performance evaluation using the TPC-C benchmark.

The next decade will bring radical changes to the way we do information processing, as applications composed of many cooperating distributed subsystems, exploiting different computational paradigms, become more common. This situation increases substantially demands in the area of system management, correctness analysis, understanding, debugging and performance evaluation. Managed Object-based Distributed Monitoring System (MODIMOS) is a project aimed at development of an adaptable platform for visualization of distributed applications, built of interoperating heterogeneous components. MODIMOS is expandable, allowing to add new monitored environments. It employs various management mechanisms to cope with gathered information size and complexity.