Karen Lopez

Information & Communications Technology

SQL Server Database Design Db2 database lifecycle management Azure SQL Database Databases Cloud Computing on the Azure Platform Azure Data Platform Azure CosmosDB Data Management Data Modeling Azure Data Catalog Data Security Data Protection Data Privacy Compliance NASA Open Data Big Data Database Administration Data Science & AI Microsoft Data Platform Security & Compliance

Toronto, Ontario, Canada

Karen Lopez

Data Evangelist for InfoAdvisors, Space Enthusiast, & NASA Datanaut

Karen is a senior project manager and architect with an extensive background in development processes and information management. She specializes in taking practical approaches to systems development. She has 20+ years of public speaking (keynotes, speeches, and demonstrations). She wants attendees to have fun, gain insights and take away inspiration for working with new technologies and methods.

She's known for her slightly irreverent and practical approach to IT training and speaking. She wants you to be part of #TEAMDATA.

Current sessions

Leveraging Data Value with Azure Data Catalog

Microsoft Azure Data Catalog is all about helping people discover, understand, and use data sources, and helping organizations to get more value from their existing data. Maintaining an accurate inventory of your data, its location, and the kinds of data you are collecting is key to data protection, compliance, and regulatory obligations.
In this session we will look at:
- Reverse engineering data sources
- Enhancing understanding of data in those sources
- Tagging
- Metadata
- Data profiling
- Data stewardship and governance
- Costs, benefits, and risks of data cataloging

Also includes 10 Tips to make your enterprise data more valuable for everyone.


The Tricky Part of Doing Tricky Things in your Database

We've mastered the basics of basic database design patterns, but what happens when you or a teammate wants to use THIS ONE WEIRD TRICK to improve on your database design? Have you just discovered a brilliant new trick that no one else has ever thought of? Or will your new design cost you more, take on more risk and cause all kinds of pain for both IT and your business users?

We'll demo tricks that we've seen in our database design reviews and show you how they work and talk about the trade-offs for using them. You' learn about: Building a database engine inside your database, Implementing Hierarchies, Dealing with data structures that don't do as well in RDBMSs, Generating code out of the database, Optimizing the developer versus the data or the app, Using design patterns that don't reflect modern architectures and tools, …and a lot more.

RDBMS agnostic or specific.


Advanced Data Modeling: Data Modeling for Security, Privacy, and Compliance

Modern database systems have introduced more support for security, privacy, and compliance over the last few years. We expect this to increase as compliance issues such as GDPR and other data compliance challenges arise. In this session, Karen will be discussing the newer features from a data modelers/database designers' point of view, including:

Data Masking
End-to-End encryption
Row Level Security
New Data Types
Data Categorization and Classification

We'll look at the new database and modeling tool features, why you should consider them, where they work, where they don't. We will also discuss how to negotiate on behalf of data protection in a world of Agile, MVP, Lean and DevOps.

This session can be given in 1-4 hour sessions. Hands-on labs can be added for full-day sessions.


Database Design Contentious Issues

A highly interactive and popular session where attendees evaluate the options and best practices of common and advanced design issues.
Bring your votes, your debates, and your opinions.


How Successful IT Professionals Are Using AI to be Better at Their Jobs

From bots to self-driving cars, we hear about use of artificial intelligence to do jobs that humans don't want to do any longer. But what about use cases that still involve human decisions and actions?

Modern IT tools and processes are increasingly seeing the benefits of added artificial intelligence technologies. In this session we will discuss:

- How AI and Machine Learning (ML) features supplement modern IT tasks
- Organizations that are currently using AI to make better use of IT resources
- How modern IT tool vendors are leveraging AI services and features to make their products better


Graph DB Support in SQL Server

Graph databases solve complex relationship problems that relational databases struggle to support. Relational databases are optimized for capturing data and answering transactional data questions. Graph databases are highly optimized for answering questions about data relationships. Do you, as a data professional, understand which data stories need which type of technology?

- Master Data
- Networks & Infrastructure
- Forensics
- Customer Behaviors
- Trees and Hierarchies

You will learn:
- Which data stories are the right fit for your relational stores and which are the right fit for graph databases
- Options for bringing this data together for more intelligent data solutions
- How graph data is persisted and queried in SQL Server and Azure SQL DB


Migrating Data and Databases to Microsoft Azure

As the concept of Hybrid Datacenter becomes more mainstream data professionals will need to understand how to effectively manage and migrate data from Earthed to Cloud servers. In this session we will review how to decided if Iaas or PaaS is right for you, how to prepare your data for migration to Azure, and how to migrate your data in an efficient manner. Leave this session knowing how to best plan and execute your Azure data migration projects.


A Database Designer's Favourite New SQL Server Features

SQL Server includes multiple features that focus on data security, privacy and developer productivity. In this session we will review the best features from a database designer's and developer's point of view.

- Always Encrypted
- Dynamic Data Masking
- Temporal Tables
- Graph Data & Processing
...and more

We'll look at the new features, why you should consider them, where they work, where they don't, who needs to be involved in using them, and what changes, if any, need to be made to applications or tools that you use with SQL Server.

You will learn:

- The pros and cons of implementing each feature
- How implementing these new features may impact existing applications
- 10 tips for enhancing SQL Server security and privacy protections


Advanced Accidental Database Design

In this advanced workshop we cover enhancements in SQL Server 2017 for building databases in an enterprise environment on modern project teams.

With demonstrations and several exercises, this workshop uses group labs to cover advanced database design skills…but this isn’t your average "Here's how to create a table, now go build a database" course. Our goal is to cover new features in SQL Server that are relevant to modern enterprise development practices. We’ll talk about some of the pain points designers feel as well as the costs, benefits, and risks associated with design choices.

Discussion topics will include:

• Advanced database design process
• Security/Encryption/Data masking/Audit
• Advanced Table design Topics {Temporal/In-Memory/Compression}
• Understanding when to scale out versus scale up, and how
• Other Advanced Topics

Attendees will leave this session with an understanding of the following:
• Advanced database architecture design process for modern enterprise development projects
• New and advanced features available in SQL Server 2017
• How to decide which design features are the right design choices for your needs

The day will include lecture style format as well as interactive discussions and exercises.

Level - 300 (Intermediate)
Track - DBA
Other speakers: Karen Lopez

Attendee prerequisites:
Hands-on experience with SQL Server (any version) basic design concepts including normalization, constraints, indexes, datatypes and integrity features.
Basic understanding of database administration concepts.
Familiarity with basic Azure and Data Platform features.


Who's Pissing in Your Data Lake?

The new data terms of Data Lake, Data Reservoir, and Data Swamp have left me with more questions than answers. In this presentation, Karen discusses the types of data anomalies that organizations can run into when they use external data, the wrong datasets for the right reasons and the right datasets for the wrong reasons. She uses her own data to show you the impact of bad design decisions, incomplete testing, and other common mistakes.

These errors in design, oversights and old school, traditional practices can impact the success of your projects, even if you don't use any data lakes.

This session isn't really about data lakes, per se. It's about data quality and project processes.


Blockchain for the DBA & Data Professional

With all the hype around blockchain, why should a DBA or other data professional care? In this session, we will cover the basics of blockchain as it applies to data and database processes:
- Immutability
- Verification
- Distribution
- Cryptography
- Transactions
- Trust

We will look at current offerings for blockchain features in Azure and in database and data stores. Finally, we'll help you identify the types of business requirements that need blockchain technologies.


SQL Data Discovery and Classification

SQL Server Management Studio (SSMS) recently introduced SQL Data Discovery and Classification. This new feature allows teams to find and categorize sensitive data. SSMS looks at the names of columns to help you find where your most vulnerable data resides.

We'll look at a new feature of SQL Server that supports maintaining the classification in auditing logs for columns.

For SQL DB and Azure Data Warehouse, we'll look at Advanced Data Security to classify and record data classifications. Finally, we'll quickly look at how these classifications can feed into Azure SQL Database Auditing.


Protecting Data with Data Masking in SQL Server and SQL DB

Dynamic Data Masking has been available since SQL Server 2016. In 2019, we now have an option for static data masking. But there are trade-offs with using both. In this session we will discuss:

- Overview of Data Protection with Data Masking
- Dynamic Data Masking
- Static Data Masking
- Security vs. Privacy
- Pros and Cons of Data Masking


What's New in SQL Server & SQL DB Graph Processing?

Microsoft first introduced graph database features in SQL Server 2016. In SQL Server 2017, this feature set was extended to support more powerful graph persistence and processing.

- CREATE syntax
- MATCH
- MERGE
- Constraints

We'll look at the new features and how you can take advantage of them in both SQL Server 2017 and SQL DB.


Who's Pissing in Your Data Lake Now?

The new data terms of Data Lake, Data Reservoir, and Data Swamp have left me with more questions than answers. In this presentation, Karen discusses the types of data anomalies that organizations can run into when they use external data, the wrong datasets for the right reasons and the right datasets for the wrong reasons. Karen uses real-life examples of her own data to show the impact of bad data decisions.

This session will include recommendations for how to avoid or fix these data quality issues in SQL Server and SQL DB.

These errors in design, oversights and old school, traditional practices can impact the success of your projects, even if you don't use any data lakes.


Advanced Data Protection: Security and Privacy in SQL Server

In this advanced workshop, we cover data security and privacy protection for SQL Server and Azure SQL Database. With demonstrations and several exercises, this workshop uses group labs to cover database and data protection techniques, including threat analysis and remediation.


Introduction to Azure Data Platform for Data Professionals

We will look at the core services of Microsoft Azure Data Platform offerings. Topics that may be included are:

Azure SQL DB
Azure Data Factory
Azure Databricks
Azure Synapse (formerly Azure Data Warehouse)
Azure Cosmos DB
Azure Storage
Azure Stream Analytics
Azure Monitoring
Azure Defender/Security

We'll wrap up with the ways data professionals can get hands-on training and usage credits to learn on their own.

With so many topics to cover, we may cut topics based on audience interest.


Introduction to Azure Data Platform for Data Professionals

We will look at the core services of Microsoft Azure Data Platform offerings. Topics that may be included are:

Azure SQL DB
Azure Data Factory
Azure Databricks
Azure Synapse (formerly Azure Data Warehouse)
Azure Cosmos DB
Azure Storage
Azure Stream Analytics
Azure Monitoring
Azure Defender/Security

We'll wrap up with the ways data professionals can get hands-on training and usage credits to learn on their own.

With so many topics to cover, we may cut topics based on audience interest.