How do we set about improving the quality of data governance within an organization? What are the priorities? Data Governance is generally considered to mean providing clear roles, responsibilities, policies, principles, and organizational structures that can ensure that data is managed well, in a way that benefits the whole organization. Where do you start? Read more
Every organization must perform data governance. This requires planning, oversight, and control over the management, security, resilience and quality of data and over the use of data by the organization. In larger organizations, it can be a complex task. William Brewer explains what's involved. Read more
SQL Data Catalog 2.0 provides a simple, policy-driven approach to data protection, through data masking. It can now automatically generate the static masking sets that Data Masker will use to protect your entire database, directly from the data classification metadata held within the catalog. Read more
SQL Data Catalog's new data scanning feature uses regular expressions and data dictionaries to identify where sensitive and personal data is stored in your databases. Read more
A data catalog allows an organization to discover and record the facts about its data, where that data is held and how it used. William Brewer explains the details. Read more
William Brewer explains how to make data governance a continuous organizational activity, based on well-established standards and practices, rather than a knee-jerk response, and which skills and tools will help you achieve compliance, including SQL Data Catalog for discovery and classification of data held in SQL Server. Read more
Chris Unwin describes a classification-driven static data masking process, using SQL Data Catalog to classify all the different types of data, its purpose and sensitivity, and then command line automation to generate the masking set that Data Masker for SQL Server can use to protect this data. Read more
Richard Macaskill shows how to use Docker Compose to get SQL Data Catalog up and running in a container, in your SQL Server test lab, and then use it to evaluate its data discovery and categorization capabilities on a containerized SQL Server instance. Read more
Josh Smith shows how to use SQL Data Catalog to perform a 'first cut' data classification for one your SQL Server databases, identifying all columns that are likely to hold personal or otherwise sensitive data. Read more
In the event of a breach of personal data, any organization must produce proof that they understand what data they hold and where, and how it is being used, and that they have enforced the required standards for access control and security. To make all this possible, it is essential to build a complete model of the data and its lineage, and a data catalog is the first step in this process. Read more
If you plan to make production data available for development and test purposes, you'll need to understand which columns contain personal or sensitive data, create a data catalog to record those decisions, devise and implement a data masking, and then provision the sanitized database copies. Richard Macaskill show how to automate as much of this process as possible. Read more
Nowadays, it isn’t just banks and multinational corporations who have to be rigorous about data. Even modest organisations who would previously been unable to afford the storage, tooling and processing power required, now have sophisticated data processing capabilities within their reach. Like the superhero of the comics, with such power comes responsibility; companies soon reach Read more