13th August 2018

Our 2018 Session Line Up

  • AD 2018. 2 AM. A New Disaster just began.

    2AM. We sleeping well. And our mobile ringing and ringing. Message: DISASTER! In this session (on slides) we will NOT talk about the potential disaster (Business Continuity Management); we talk about: What happened NOW? What tasks should have been finished BEFORE! Is virtual or physical SQL Server matter?

    We talk about systems, databases, peoples, encryption, passwords, certificates and users. In this session (on few demos) I’ll show which part of our SQL Server Environment is critical and how to be prepared for the disaster. With some papers, I’ll show you how to be BEST prepared for Early Morning Disaster.

    • DBA
  • Azure Data Lake - The Services. The U-SQL. The C#.

    How do we implement Azure Data Lake?
    How does a lake fit into our data platform architecture? Is Data Lake going to run in isolation or be part of a larger pipeline?
    How do we use and work with USQL?
    Does size matter?!

    The answers to all these questions and more in this session as we immerse ourselves in the lake, that’s in a cloud.

    We'll take an end to end look at the components and understand why the compute and storage are separate services.

    For the developers, what tools should we be using and where should we deploy our USQL scripts. Also, what options are available for handling our C# code behind and supporting assemblies.

    We’ll cover everything you need to know to get started developing data solutions with Azure Data Lake.

    • BI
  • Azure database perfomance

    The popular image of cloud services is both attractive and enticing. You get access to an unlimited amount of hardware at a reasonable price. Your systems can run seamlessly and at peak performance anywhere in the world, and It is natural to assume that the performance of cloud services is identical and stable, regardless of whether it’s located in Asia, Europe or North America To confirm if this is really the case or not, we conducted two tests periods in Azure. One in December 2016 and one in March 2018. Three Service tiers were tested: Basic 5 DTU, Standard S3 100 DTU and Premium P2 250 DTU. The tests have been done at three locations: West Europe, West Japan and West US. We will present the test methods and harness uses, and the results and findings. Based on our measurements we have seen: - Significant variations in performance between the different geographical locations - Significant variations in performance for the same database at different times - Surprisingly poor perfor

    • Azure
  • Containers and Clones: Provision GIANT databases on tiny HDDs

    Shared dev databases are the root cause of so much pain. With this in mind, people are moving to dedicated dev databases for each developer. However, provisioning dev environments is often a slow, complicated and manual process. Often devs simply don’t have the diskspace. And then there is the GDPR.

    You can solve many of the these problems with virtualisation technologies like containers and clones - but there are various options and they don't all play nicely together.

    In this session we'll introduce you to Docker containers, Redgate Clones and WinDocks and explain the pros and cons of each technology. We'll also spend a bit of time discussing how to integrate masking rules to keep sensitive data out of the dev domain.

    Are you on #teamClone or #teamContainer?

    • DBA
  • Datawarehouse Lightning Performance with Columnstore!

    During this session we will be talking about Columnstore Indexes and how to use them. We will be showing you tips & tricks on how to get the performance you want out of Columnstore.
    We will show you the concepts on how to efficiently load data to your Columnstore tables, how to get your Columnstore properly created, and some dangers with performance you might face when working with Columnstore Indexes as seen in the field!
    After this session things like segment elimination, auto adjust buffer size, Delta Store,... will no longer be a mysterious concept for you & you will be ready to start implementing the different flavors of Columnstore Indexes in your environment.

    • BI
  • dbatools - PowerShell and SQL Server Working Together

    The dbatools module now has over 300 commands and anyone who wants to start is overloaded with amount of functionality in this module.
    There are not enough hours in the day to get everything done as a DBA. We need to automate our repetitive tasks to free up time for the important and more fun tasks.
    In this session I'll show you a set of commands which will help you start automating your tasks.

    • DBA
  • Getting started with Machine learning in Python

    Everyone needs to start learning machine learning, by 2020 80% of all applications will be powered by a form Artificial Intelligence (Machine learning - don’t worry the robots are not rising). Machine learning is no longer just for data scientists, everyone working with data need to have a basic awareness of machine learning. If you work with data, you should be investing in machine learning.

    In this session we will look at Python as a language and explore its packages for interactive machine learning. Terms like SkLearn, Pandas, SciPy, Pickle will become familiar to you by the end of this session. You won't be an expert in machine learning but you will know how to get started with Python. This session will touch on Python for SQL Server, but our focus will be developing models using Python.

    • Analytics
  • Intro to Query Store

    In this session, we will look at the new Query Store feature in SQL Server 2016 and 2017. Query Store tracks changes in execution plans, allowing you to easily view performance differences and revert to older plans with a few clicks of the mouse in 2016.

    Then in 2017, Microsoft added wait stats per query plan and Automatic Tuning capabilities. Allowing DBAs more tools to troubleshoot fires with and a way to automatically resolve issues.

    In this session, we will walk through the features of Query Store, so you can understand how to use them in SQL Server 2016 and 2017.

    • DBA
  • Maintain a Database Project, and Continuous Delivery using Microsoft Data Tools in practical terms

    A task seems to be easy. Maintenance a project of a database in the code repository, treat as master-version and do deployment evenly and frequently. Simple? Seemingly. The things become more complex as fast as a number of objects in database growing. While instead of one database, we have over a dozen. When databases have got the references to each other. And how about dictionary tables? Where to keep them and how to script? Additional issues are coming whilst we would like to control instance-level objects.
    All these topics I will explain in the session focused on practical aspects of work with Microsoft Visual Studio Data Tools.

    • DBA
  • Modern Data Warehousing - A template for Lambda BI in Azure

    Technology changes quickly - patterns and approaches less so. As we move towards distributed cloud architectures we will employ a range of disparate tools, the patterns that were designed for single box solutions may not be appropriate any more.

    This session will take you through the patterns and processes that underpin the Lambda architecture, providing advice and guidance on the tool sets and integration points between them.

    We will follow the movement of data through batch and speed layers via Azure Data Lake Store & Analytics, Data Factory, SQL Datawarehouse and Streamining Analytics, before looking briefly at Azure Analysis Services with PowerBI. This is a largely theory-based session to prime you for the future

    • Analytics
  • Persistence is Futile - Implementing Delayed Durability in SQL Server

    The concurrency model of most Relational Database Systems are defined by the ACID properties but as they aim for ever-increasing transactional throughput, those rules are bent, ignored, or even broken. In this session, we will investigate how SQL Server implements transactional durability in order to understand how Delayed Durability bends the rules to remove transactional bottlenecks and achieve improved throughput. We will take a look at how this can be used to compliment In-Memory OLTP performance, and how it might impact or compromise other things. Attend this session and you will be assimilated!

    • DBA
  • Power BI and PowerShell - A Match Made in Heaven

    Power BI is the shiny new tech for processing and visualizing data in the Microsoft Data Platform. However, the plumbing in the background does need managing (even if it is cloud-based and supposedly automagic).

    In this session we will take a look at how to manage your datasets, security, monitor licensing and more, all through the ultimate administration interface: PowerShell!

    You'll leave the session with an overview of the management capabilities of Power BI and couple that knowledge with the awesome power (and automation possibilities) of PowerShell

    • BI
  • Slacking for the DBA

    No, not that sort of slacking. The Slack.com type of slacking. We'll be ignoring the gifs and looking at how using Slack, PoshBot, dbatools and a little bit of PowerShell glue you can build a simple solution that enables you to quickly respond to and fix problems from anywhere without having to carry anything more specialised than your smart phone. And we'll see how you can then extend that to allow you to hand off tasks to other users and teams in a safe secure manner.

    • DBA
  • SQL Server on Linux - Lets get started...

    In this session we discuss what SQL Server on Linux is, who should use it and why... We will talk about the difference between running Linux on a machine or using Docker.

    Then we kick into the demos.....
    Let’s install SQL Server on Ubuntu, connect to it using SQL Operations Studio (open source database management tool) and SQL Server Management studio.

    We will also install SQL Server in a docker container.

    We will have a look at backups/restores and mirgrating to SQL Server on Linux.

    No penguins were harmed in the writing of this presentation.

    • DBA
  • Towards Personal Data Science with Power BI

    Microsoft states that Power BI is "a suite of business analytics tools to analyze data and share insights." Does this mean Power BI can also be used for more than just building pretty dashboards?
    In this session we’ll explore how BI and Data Science are related and how Power BI can not only be used to democratize BI across the enterprise, but also to democratize Data Science!
    No previous knowledge is required because after a 5 minute data science jump start, we dive into a demo scenario using Azure Machine Learning and Power BI! Throughout the story accompanying the demo's, it will become clear how you too can get start practicing Personal Data Science. Or as Gartner calls it: Citizen Data Science


    At the end of the session, not only will you know the differences, and resemblances, between the BI and data science processes, you'll also be able to follow the general data science process and know in what ways Personal Data Science is an extension of Personal BI (aka: Self Service BI)
    Attendees will know where Power BI can fit into the data science process (hint: not only at the end)
    Attendees will know how to apply above principles to generate re-usable output in a personal data science process

    • Analytics
  • What are Azure SQL Database Managed Instances?

    The range of options for storing data in Microsoft Azure keeps growing, the most notable recent addition is the Managed Instance. But what is it, and why is it there? Join John as he walks through what they are
    and how you might start using them.

    Managed Instances add a new option for running workloads in the cloud. Allowing near parity with a traditional on-premises SQL Server. Including SQL Agent, Cross Database Queries, Service Broker, CDC, and many more. Overcoming many of the challenges to using Azure SQL Databases.

    But, what is the reality, how do we make use of it, and are there any gotcha’s that we need to be aware of? This is what we will cover, going beyond the hype and looking at how we can make use of this new
    technology.

    • Azure
  • AD 2018. 2 AM. A New Disaster just began.

    2AM. We sleeping well. And our mobile ringing and ringing. Message: DISASTER! In this session (on slides) we will NOT talk about the potential disaster (Business Continuity Management); we talk about: What happened NOW? What tasks should have been finished BEFORE! Is virtual or physical SQL Server matter?

    We talk about systems, databases, peoples, encryption, passwords, certificates and users. In this session (on few demos) I’ll show which part of our SQL Server Environment is critical and how to be prepared for the disaster. With some papers, I’ll show you how to be BEST prepared for Early Morning Disaster.

    • DBA
  • Azure Data Lake - The Services. The U-SQL. The C#.

    How do we implement Azure Data Lake?
    How does a lake fit into our data platform architecture? Is Data Lake going to run in isolation or be part of a larger pipeline?
    How do we use and work with USQL?
    Does size matter?!

    The answers to all these questions and more in this session as we immerse ourselves in the lake, that’s in a cloud.

    We'll take an end to end look at the components and understand why the compute and storage are separate services.

    For the developers, what tools should we be using and where should we deploy our USQL scripts. Also, what options are available for handling our C# code behind and supporting assemblies.

    We’ll cover everything you need to know to get started developing data solutions with Azure Data Lake.

    • BI
  • Azure database perfomance

    The popular image of cloud services is both attractive and enticing. You get access to an unlimited amount of hardware at a reasonable price. Your systems can run seamlessly and at peak performance anywhere in the world, and It is natural to assume that the performance of cloud services is identical and stable, regardless of whether it’s located in Asia, Europe or North America To confirm if this is really the case or not, we conducted two tests periods in Azure. One in December 2016 and one in March 2018. Three Service tiers were tested: Basic 5 DTU, Standard S3 100 DTU and Premium P2 250 DTU. The tests have been done at three locations: West Europe, West Japan and West US. We will present the test methods and harness uses, and the results and findings. Based on our measurements we have seen: - Significant variations in performance between the different geographical locations - Significant variations in performance for the same database at different times - Surprisingly poor perfor

    • Azure
  • Be a dynamic SQL dynamo!

    This session will cover the basics of dynamic SQL; how, why and when you may wish to use it with demos of use cases and scenarios where it can really save the day (trying to perform a search with a variable number of optional search terms, anyone?). We will also cover the performance and security impacts touching on the effect on query plans, index usage and security (SQL injection!) along with some best practices.

    • Other
  • Beyond Visualisation, Beyond Power BI

    Have you embarked on your Power BI odyssey? Are you finding the limitations and inefficiency of Power BI?
    Attend this session to get an overview of Pyramid 2018, a true Enterprise Class self-service analytic platform.
    Instantly query relational, multi-dimensional, in memory analytic models. Write your analytic data models to Pyramid in memory, SSAS Tabular or relational data engines. Create complex multidimensional calculations, dynamic named sets and real KPIs using visual tools. Instantly share and publish your content. Add Machine Learning scripts to your data preparation flows visually with no coding. 
    All this and more with Pyramid 2018.

    • DBA
  • dbatools - PowerShell and SQL Server Working Together

    The dbatools module now has over 300 commands and anyone who wants to start is overloaded with amount of functionality in this module.
    There are not enough hours in the day to get everything done as a DBA. We need to automate our repetitive tasks to free up time for the important and more fun tasks.
    In this session I'll show you a set of commands which will help you start automating your tasks.

    • DBA
  • DevOps, Dev Data and the GDPR: 5 Solutions

    It’s an age-old problem: developers want prod data for dev and test purposes.

    It helps them to write better code and to test it effectively. Self-service access to usable test-data aligns well with DevOps principles that encourage teams to adopt a shift-left mentality to testing.

    Unfortunately, in the age of data breaches and the GDPR it’s simply illegal to give developers access to some types of sensitive production data.

    So what do you do?

    In this session I’ll talk about the GDPR, anonymisation, pseudonymisation and 5 techniques you can use to provide appropriate data that is as “production-like” as possible (within the legal and technical constraints). I’ll demo these techniques both in raw T-SQL and using some of the Microsoft and third party tools that are available to make the task easier.

    After this session you’ll be equipped to discuss the problem with your colleagues in an informed manner and you’ll be able to suggest several solutions and their relative pros and cons.

    • DBA
  • Getting started with Machine learning in Python

    Everyone needs to start learning machine learning, by 2020 80% of all applications will be powered by a form Artificial Intelligence (Machine learning - don’t worry the robots are not rising). Machine learning is no longer just for data scientists, everyone working with data need to have a basic awareness of machine learning. If you work with data, you should be investing in machine learning.

    In this session we will look at Python as a language and explore its packages for interactive machine learning. Terms like SkLearn, Pandas, SciPy, Pickle will become familiar to you by the end of this session. You won't be an expert in machine learning but you will know how to get started with Python. This session will touch on Python for SQL Server, but our focus will be developing models using Python.

    • Analytics
  • Intro to Query Store

    In this session, we will look at the new Query Store feature in SQL Server 2016 and 2017. Query Store tracks changes in execution plans, allowing you to easily view performance differences and revert to older plans with a few clicks of the mouse in 2016.

    Then in 2017, Microsoft added wait stats per query plan and Automatic Tuning capabilities. Allowing DBAs more tools to troubleshoot fires with and a way to automatically resolve issues.

    In this session, we will walk through the features of Query Store, so you can understand how to use them in SQL Server 2016 and 2017.

    • DBA
  • Maintain a Database Project, and Continuous Delivery using Microsoft Data Tools in practical terms

    A task seems to be easy. Maintenance a project of a database in the code repository, treat as master-version and do deployment evenly and frequently. Simple? Seemingly. The things become more complex as fast as a number of objects in database growing. While instead of one database, we have over a dozen. When databases have got the references to each other. And how about dictionary tables? Where to keep them and how to script? Additional issues are coming whilst we would like to control instance-level objects.
    All these topics I will explain in the session focused on practical aspects of work with Microsoft Visual Studio Data Tools.

    • DBA
  • Migrating to Azure Managed Instances!

    During this session we will be migrating an on-prem instance to a azure managed instance. We will be looking into the considerations you have to make at the start, and how you can effectively size your managed instance. We will show you what pitfalls you might meet when moving the instance to the cloud & how you can fix them. We will also touch upon how the DR & High availability and how this fits into Managed instances.
    After this session you will be ready to start using Azure Managed Instances to move your on-prem instances.

    • Azure
  • Modern Data Warehousing - A template for Lambda BI in Azure

    Technology changes quickly - patterns and approaches less so. As we move towards distributed cloud architectures we will employ a range of disparate tools, the patterns that were designed for single box solutions may not be appropriate any more.

    This session will take you through the patterns and processes that underpin the Lambda architecture, providing advice and guidance on the tool sets and integration points between them.

    We will follow the movement of data through batch and speed layers via Azure Data Lake Store & Analytics, Data Factory, SQL Datawarehouse and Streamining Analytics, before looking briefly at Azure Analysis Services with PowerBI. This is a largely theory-based session to prime you for the future

    • Analytics
  • Power BI and PowerShell - A Match Made in Heaven

    Power BI is the shiny new tech for processing and visualizing data in the Microsoft Data Platform. However, the plumbing in the background does need managing (even if it is cloud-based and supposedly automagic).

    In this session we will take a look at how to manage your datasets, security, monitor licensing and more, all through the ultimate administration interface: PowerShell!

    You'll leave the session with an overview of the management capabilities of Power BI and couple that knowledge with the awesome power (and automation possibilities) of PowerShell

    • BI
  • Slacking for the DBA

    No, not that sort of slacking. The Slack.com type of slacking. We'll be ignoring the gifs and looking at how using Slack, PoshBot, dbatools and a little bit of PowerShell glue you can build a simple solution that enables you to quickly respond to and fix problems from anywhere without having to carry anything more specialised than your smart phone. And we'll see how you can then extend that to allow you to hand off tasks to other users and teams in a safe secure manner.

    • DBA
  • SQL Containers in the Cloud! An intro to running Docker in Azure

    As containers are becoming more and more prevalent, this session provides an introduction to the different options of running containers in Azure.

    I'll cover the following different options for running Docker in Azure:
    The Azure Container Registry
    Azure Container Instances
    Azure Container Services (AKS)

    This session is aimed at SQL Server DBAs and Developers who have some experience with Docker (Docker for Windows) and want to know the different options that are available in Azure.

    Each topic will be backed up with live demos which will show how simple it is to get up and running with these technologies.

    • DBA
  • SQL Server on Linux - Lets get started...

    In this session we discuss what SQL Server on Linux is, who should use it and why... We will talk about the difference between running Linux on a machine or using Docker.

    Then we kick into the demos.....
    Let’s install SQL Server on Ubuntu, connect to it using SQL Operations Studio (open source database management tool) and SQL Server Management studio.

    We will also install SQL Server in a docker container.

    We will have a look at backups/restores and mirgrating to SQL Server on Linux.

    No penguins were harmed in the writing of this presentation.

    • DBA
  • Temporal Tables in the Data Warehouse

    Temporal tables, introduced with SQL Server 2016 have a number of useful applications within the data warehouse.
    This session provides an introduction to temporal tables, runs through a number of use cases, shows how temporal tables can simplify the code needed in comparison to traditional solutions and finally takes a brief look at performance in comparison to their alternatives.

    • BI
  • Towards Personal Data Science with Power BI

    Microsoft states that Power BI is "a suite of business analytics tools to analyze data and share insights." Does this mean Power BI can also be used for more than just building pretty dashboards?
    In this session we’ll explore how BI and Data Science are related and how Power BI can not only be used to democratize BI across the enterprise, but also to democratize Data Science!
    No previous knowledge is required because after a 5 minute data science jump start, we dive into a demo scenario using Azure Machine Learning and Power BI! Throughout the story accompanying the demo's, it will become clear how you too can get start practicing Personal Data Science. Or as Gartner calls it: Citizen Data Science


    At the end of the session, not only will you know the differences, and resemblances, between the BI and data science processes, you'll also be able to follow the general data science process and know in what ways Personal Data Science is an extension of Personal BI (aka: Self Service BI)
    Attendees will know where Power BI can fit into the data science process (hint: not only at the end)
    Attendees will know how to apply above principles to generate re-usable output in a personal data science process

    • Analytics
  • A Whirlwind Tour Of Azure SQLDB

    Azure SQL Database is a general-purpose relational database service in Microsoft Azure. With Microsoft's cloud-first strategy, the newest capabilities of SQL Server are released first to Azure SQL Database and then to SQL Server itself. During this presentation you will get understand the importance of security, high availability and how best to use the various tools available to you for performance monitoring of this cloud-first solution. You will also learn about the different service tiers and performance levels that are specific to Azure SQL Database and find out about the different methods that you could use to migrate your database to Azure.

    • Azure
  • AD 2018. 2 AM. A New Disaster just began.

    2AM. We sleeping well. And our mobile ringing and ringing. Message: DISASTER! In this session (on slides) we will NOT talk about the potential disaster (Business Continuity Management); we talk about: What happened NOW? What tasks should have been finished BEFORE! Is virtual or physical SQL Server matter?

    We talk about systems, databases, peoples, encryption, passwords, certificates and users. In this session (on few demos) I’ll show which part of our SQL Server Environment is critical and how to be prepared for the disaster. With some papers, I’ll show you how to be BEST prepared for Early Morning Disaster.

    • DBA
  • Automating Power BI Deployments

    If you ever had to deploy or migrate Power BI, you know there's no out-of-the-box process provided by Microsoft. The manual workarounds we see in the field range from ok to problematic.
    This does not fit at all with the DevOps mentality and there's a plethora of reasons to want to change this and actually do CI/CD for Power BI Projects.
    In this session we'll go through a solution you can implement to fully automate the deployment of Power BI throughout environments from source control to Development up to Production.

    At the end of the session, you'll have the tools and knowledge to adapt this process to your own environment.

    • BI
  • Azure Data Lake - The Services. The U-SQL. The C#.

    How do we implement Azure Data Lake?
    How does a lake fit into our data platform architecture? Is Data Lake going to run in isolation or be part of a larger pipeline?
    How do we use and work with USQL?
    Does size matter?!

    The answers to all these questions and more in this session as we immerse ourselves in the lake, that’s in a cloud.

    We'll take an end to end look at the components and understand why the compute and storage are separate services.

    For the developers, what tools should we be using and where should we deploy our USQL scripts. Also, what options are available for handling our C# code behind and supporting assemblies.

    We’ll cover everything you need to know to get started developing data solutions with Azure Data Lake.

    • BI
  • Containers and Clones: Provision GIANT databases on tiny HDDs

    Shared dev databases are the root cause of so much pain. With this in mind, people are moving to dedicated dev databases for each developer. However, provisioning dev environments is often a slow, complicated and manual process. Often devs simply don’t have the diskspace. And then there is the GDPR.

    You can solve many of the these problems with virtualisation technologies like containers and clones - but there are various options and they don't all play nicely together.

    In this session we'll introduce you to Docker containers, Redgate Clones and WinDocks and explain the pros and cons of each technology. We'll also spend a bit of time discussing how to integrate masking rules to keep sensitive data out of the dev domain.

    Are you on #teamClone or #teamContainer?

    • DBA
  • dbatools - PowerShell and SQL Server Working Together

    The dbatools module now has over 300 commands and anyone who wants to start is overloaded with amount of functionality in this module.
    There are not enough hours in the day to get everything done as a DBA. We need to automate our repetitive tasks to free up time for the important and more fun tasks.
    In this session I'll show you a set of commands which will help you start automating your tasks.

    • DBA
  • ETL orchestration in TSQL

    There are many techniques for orchestrating ETL processes, but the difference between good ones and great ones is how they perform when things go wrong. Desirable behaviours – like fault tolerance, quick fault finding and easy resume after error – often aren't available and sometimes seem hard to achieve. In my session I'll present an approach to doing this using only TSQL and the SQL Server Agent, and which also enables parallel processing, adapts to evolving workloads and provides a wide variety of monitoring and diagnostic information.

    • BI
  • Intro to Query Store

    In this session, we will look at the new Query Store feature in SQL Server 2016 and 2017. Query Store tracks changes in execution plans, allowing you to easily view performance differences and revert to older plans with a few clicks of the mouse in 2016.

    Then in 2017, Microsoft added wait stats per query plan and Automatic Tuning capabilities. Allowing DBAs more tools to troubleshoot fires with and a way to automatically resolve issues.

    In this session, we will walk through the features of Query Store, so you can understand how to use them in SQL Server 2016 and 2017.

    • DBA
  • Introduction to M

    When you’re loading data into Power BI, Excel and SSAS Tabular there’s a lot you can achieve in the Power Query Editor just by using the user interface. However, everything you do in the Query Editor is converted to code in a language called M and in more advanced data loading scenarios you’ll need to know how to write M code. In this session you’ll learn what kind of scenarios you’ll need to use M as well as the fundamentals of the language. You’ll also see several practical examples of how to use it.

    • BI
  • Migrating to Azure Managed Instances!

    During this session we will be migrating an on-prem instance to a azure managed instance. We will be looking into the considerations you have to make at the start, and how you can effectively size your managed instance. We will show you what pitfalls you might meet when moving the instance to the cloud & how you can fix them. We will also touch upon how the DR & High availability and how this fits into Managed instances.
    After this session you will be ready to start using Azure Managed Instances to move your on-prem instances.

    • Azure
  • Patterns and Best Practices in SSIS

    Writing SSIS ETL packages is easy, right ? But how do you maintain them though upgrades and changes ?
    In this session, we'll take a look at good practice, patterns, anti-patterns, and a few tricks to make your ETL fly and be free ....!

    • BI
  • Python Pipeline Primer: Data Engineering with Azure DataBricks

    Azure DataBricks brings a Platform-as-a-Service offering of Apache Spark, which allows for blazing fast data processing, interactive querying and the hosting of machine learning models all in one place! But most of the buzz is around what it means for Data Science & AI - what about the humble data engineer who wants to harness the in-memory processing power within their ETL pipelines? How does it fit into the Modern Data Warehouse? What does data preparation look like in this new world?

    This session will run through the best practices of implementing Azure DataBricks as your data ingestion, transformation and curation tool of choice. We will:

    • Introduce the Azure DataBricks service
    • Introduce Python and why it is the language of choice for Data Engineering on DataBricks
    • Discuss the various hosting & compute options available
    • Demonstrate a sample data processing task
    • Compare and contrast against alternative approaches using SSIS, U-SQL and HDInsight
    • Demonstrate how to manage and orchestrate your processing pipelines
    • Review the wider architectures and additional extension patterns

    The session is aimed at Data Engineers & BI Professionals seeking to put the Azure DataBricks technology in the right context and learn how to use the service. We will not be covering the python programming language in detail.

    • Analytics
  • SQL Server hates you(?) - what the DBAs never told the developers

    Have you had performance tank despite the code working fine in another environment? Maybe heard that some SQL is bad but not why? If so, this is the session for you!
    This session will start with a walkthrough of some of the basic settings in SQL Server and how they affect you as a developer. It follows with key tips on what settings to change, why some code will wreak havoc on your performance and how isolation levels matter (and why NOLOCK can be an exceptionally bad idea!) The session is led by a 20-year DBA veteran who decided to try to help developers understand performance issues by seeing things from his perspective.
    If you want to explore how default settings kill your performance, investigate why harmless SQL might not be quite so harmless and gain insight into how isolation levels affect function and performance, then this session will provide you with the tools to think outside the box and incorporate database engine knowledge into your developer prowess!

    • DBA
  • SQL Server on Linux - Lets get started...

    In this session we discuss what SQL Server on Linux is, who should use it and why... We will talk about the difference between running Linux on a machine or using Docker.

    Then we kick into the demos.....
    Let’s install SQL Server on Ubuntu, connect to it using SQL Operations Studio (open source database management tool) and SQL Server Management studio.

    We will also install SQL Server in a docker container.

    We will have a look at backups/restores and mirgrating to SQL Server on Linux.

    No penguins were harmed in the writing of this presentation.

    • DBA
  • Temporal Tables in the Data Warehouse

    Temporal tables, introduced with SQL Server 2016 have a number of useful applications within the data warehouse.
    This session provides an introduction to temporal tables, runs through a number of use cases, shows how temporal tables can simplify the code needed in comparison to traditional solutions and finally takes a brief look at performance in comparison to their alternatives.

    • BI
  • AD 2018. 2 AM. A New Disaster just began.

    2AM. We sleeping well. And our mobile ringing and ringing. Message: DISASTER! In this session (on slides) we will NOT talk about the potential disaster (Business Continuity Management); we talk about: What happened NOW? What tasks should have been finished BEFORE! Is virtual or physical SQL Server matter?

    We talk about systems, databases, peoples, encryption, passwords, certificates and users. In this session (on few demos) I’ll show which part of our SQL Server Environment is critical and how to be prepared for the disaster. With some papers, I’ll show you how to be BEST prepared for Early Morning Disaster.

    • DBA
  • Automating Power BI Deployments

    If you ever had to deploy or migrate Power BI, you know there's no out-of-the-box process provided by Microsoft. The manual workarounds we see in the field range from ok to problematic.
    This does not fit at all with the DevOps mentality and there's a plethora of reasons to want to change this and actually do CI/CD for Power BI Projects.
    In this session we'll go through a solution you can implement to fully automate the deployment of Power BI throughout environments from source control to Development up to Production.

    At the end of the session, you'll have the tools and knowledge to adapt this process to your own environment.

    • BI
  • Azure Data Lake - The Services. The U-SQL. The C#.

    How do we implement Azure Data Lake?
    How does a lake fit into our data platform architecture? Is Data Lake going to run in isolation or be part of a larger pipeline?
    How do we use and work with USQL?
    Does size matter?!

    The answers to all these questions and more in this session as we immerse ourselves in the lake, that’s in a cloud.

    We'll take an end to end look at the components and understand why the compute and storage are separate services.

    For the developers, what tools should we be using and where should we deploy our USQL scripts. Also, what options are available for handling our C# code behind and supporting assemblies.

    We’ll cover everything you need to know to get started developing data solutions with Azure Data Lake.

    • BI
  • Building your Big Data and Advanced Analytics Pipeline on Azure using Azure Data Factory

    In this session, we will focus on Azure Data Factory's orchestration capabilities and how it could meet the ETL needs for Big Data and Advanced Analytics projects. We will see some end-to-end demos on how Customer's leverage Azure Data Factory's Control flow and Data flow in their Data pipelines. Security and Performance will be the major consideration in this session.

    • Azure
  • Datawarehouse Lightning Performance with Columnstore!

    During this session we will be talking about Columnstore Indexes and how to use them. We will be showing you tips & tricks on how to get the performance you want out of Columnstore.
    We will show you the concepts on how to efficiently load data to your Columnstore tables, how to get your Columnstore properly created, and some dangers with performance you might face when working with Columnstore Indexes as seen in the field!
    After this session things like segment elimination, auto adjust buffer size, Delta Store,... will no longer be a mysterious concept for you & you will be ready to start implementing the different flavors of Columnstore Indexes in your environment.

    • BI
  • dbatools - PowerShell and SQL Server Working Together

    The dbatools module now has over 300 commands and anyone who wants to start is overloaded with amount of functionality in this module.
    There are not enough hours in the day to get everything done as a DBA. We need to automate our repetitive tasks to free up time for the important and more fun tasks.
    In this session I'll show you a set of commands which will help you start automating your tasks.

    • DBA
  • DevOps, Dev Data and the GDPR: 5 Solutions

    It’s an age-old problem: developers want prod data for dev and test purposes.

    It helps them to write better code and to test it effectively. Self-service access to usable test-data aligns well with DevOps principles that encourage teams to adopt a shift-left mentality to testing.

    Unfortunately, in the age of data breaches and the GDPR it’s simply illegal to give developers access to some types of sensitive production data.

    So what do you do?

    In this session I’ll talk about the GDPR, anonymisation, pseudonymisation and 5 techniques you can use to provide appropriate data that is as “production-like” as possible (within the legal and technical constraints). I’ll demo these techniques both in raw T-SQL and using some of the Microsoft and third party tools that are available to make the task easier.

    After this session you’ll be equipped to discuss the problem with your colleagues in an informed manner and you’ll be able to suggest several solutions and their relative pros and cons.

    • DBA
  • Getting started with Machine learning in Python

    Everyone needs to start learning machine learning, by 2020 80% of all applications will be powered by a form Artificial Intelligence (Machine learning - don’t worry the robots are not rising). Machine learning is no longer just for data scientists, everyone working with data need to have a basic awareness of machine learning. If you work with data, you should be investing in machine learning.

    In this session we will look at Python as a language and explore its packages for interactive machine learning. Terms like SkLearn, Pandas, SciPy, Pickle will become familiar to you by the end of this session. You won't be an expert in machine learning but you will know how to get started with Python. This session will touch on Python for SQL Server, but our focus will be developing models using Python.

    • Analytics
  • Intro to Query Store

    In this session, we will look at the new Query Store feature in SQL Server 2016 and 2017. Query Store tracks changes in execution plans, allowing you to easily view performance differences and revert to older plans with a few clicks of the mouse in 2016.

    Then in 2017, Microsoft added wait stats per query plan and Automatic Tuning capabilities. Allowing DBAs more tools to troubleshoot fires with and a way to automatically resolve issues.

    In this session, we will walk through the features of Query Store, so you can understand how to use them in SQL Server 2016 and 2017.

    • DBA
  • Introduction to M

    When you’re loading data into Power BI, Excel and SSAS Tabular there’s a lot you can achieve in the Power Query Editor just by using the user interface. However, everything you do in the Query Editor is converted to code in a language called M and in more advanced data loading scenarios you’ll need to know how to write M code. In this session you’ll learn what kind of scenarios you’ll need to use M as well as the fundamentals of the language. You’ll also see several practical examples of how to use it.

    • BI
  • Patterns and Best Practices in SSIS

    Writing SSIS ETL packages is easy, right ? But how do you maintain them though upgrades and changes ?
    In this session, we'll take a look at good practice, patterns, anti-patterns, and a few tricks to make your ETL fly and be free ....!

    • BI
  • SQL Containers in the Cloud! An intro to running Docker in Azure

    As containers are becoming more and more prevalent, this session provides an introduction to the different options of running containers in Azure.

    I'll cover the following different options for running Docker in Azure:
    The Azure Container Registry
    Azure Container Instances
    Azure Container Services (AKS)

    This session is aimed at SQL Server DBAs and Developers who have some experience with Docker (Docker for Windows) and want to know the different options that are available in Azure.

    Each topic will be backed up with live demos which will show how simple it is to get up and running with these technologies.

    • DBA
  • SQL Server hates you(?) - what the DBAs never told the developers

    Have you had performance tank despite the code working fine in another environment? Maybe heard that some SQL is bad but not why? If so, this is the session for you!
    This session will start with a walkthrough of some of the basic settings in SQL Server and how they affect you as a developer. It follows with key tips on what settings to change, why some code will wreak havoc on your performance and how isolation levels matter (and why NOLOCK can be an exceptionally bad idea!) The session is led by a 20-year DBA veteran who decided to try to help developers understand performance issues by seeing things from his perspective.
    If you want to explore how default settings kill your performance, investigate why harmless SQL might not be quite so harmless and gain insight into how isolation levels affect function and performance, then this session will provide you with the tools to think outside the box and incorporate database engine knowledge into your developer prowess!

    • DBA
  • SQL Server on Linux - Lets get started...

    In this session we discuss what SQL Server on Linux is, who should use it and why... We will talk about the difference between running Linux on a machine or using Docker.

    Then we kick into the demos.....
    Let’s install SQL Server on Ubuntu, connect to it using SQL Operations Studio (open source database management tool) and SQL Server Management studio.

    We will also install SQL Server in a docker container.

    We will have a look at backups/restores and mirgrating to SQL Server on Linux.

    No penguins were harmed in the writing of this presentation.

    • DBA
  • Teach your old server new tricks with Aireforge

    Discover new and unexpected ways to improve the performance, stability and security of your database in this session for database professionals of all levels.

    Uncover tips, tricks and myths around the administration and development of SQL Server and Azure. Learn some of the top causes of common issues and how to find solutions.

    • DBA
  • Temporal Tables in the Data Warehouse

    Temporal tables, introduced with SQL Server 2016 have a number of useful applications within the data warehouse.
    This session provides an introduction to temporal tables, runs through a number of use cases, shows how temporal tables can simplify the code needed in comparison to traditional solutions and finally takes a brief look at performance in comparison to their alternatives.

    • BI
  • What are Azure SQL Database Managed Instances?

    The range of options for storing data in Microsoft Azure keeps growing, the most notable recent addition is the Managed Instance. But what is it, and why is it there? Join John as he walks through what they are
    and how you might start using them.

    Managed Instances add a new option for running workloads in the cloud. Allowing near parity with a traditional on-premises SQL Server. Including SQL Agent, Cross Database Queries, Service Broker, CDC, and many more. Overcoming many of the challenges to using Azure SQL Databases.

    But, what is the reality, how do we make use of it, and are there any gotcha’s that we need to be aware of? This is what we will cover, going beyond the hype and looking at how we can make use of this new
    technology.

    • Azure
  • Writing Your Own Encryption Routines in SQL... and Then Cracking Them

    SQL Server gives us plenty of options when it comes to encrypting our data. But have you ever wanted to write your own encryption routines, perhaps you think that what SQL Server offers us doesn’t quite fit the bill for you?

    I’m going to look into the basics of how encryption works and then we’ll learn how we can go about writing our own encryption routines within SQL Server. When we’re happy that those routines are secure, we’ll look at ways that we can go about cracking those routines.

    Writing our own encryption within SQL might sound like a good idea and could even be something that you’ve tried out yourself but there’s a chance you might change your mind when you see how easily amateur cryptography can be broken.

    • Other
  • AD 2018. 2 AM. A New Disaster just began.

    2AM. We sleeping well. And our mobile ringing and ringing. Message: DISASTER! In this session (on slides) we will NOT talk about the potential disaster (Business Continuity Management); we talk about: What happened NOW? What tasks should have been finished BEFORE! Is virtual or physical SQL Server matter?

    We talk about systems, databases, peoples, encryption, passwords, certificates and users. In this session (on few demos) I’ll show which part of our SQL Server Environment is critical and how to be prepared for the disaster. With some papers, I’ll show you how to be BEST prepared for Early Morning Disaster.

    • DBA
  • Azure Data Lake - The Services. The U-SQL. The C#.

    How do we implement Azure Data Lake?
    How does a lake fit into our data platform architecture? Is Data Lake going to run in isolation or be part of a larger pipeline?
    How do we use and work with USQL?
    Does size matter?!

    The answers to all these questions and more in this session as we immerse ourselves in the lake, that’s in a cloud.

    We'll take an end to end look at the components and understand why the compute and storage are separate services.

    For the developers, what tools should we be using and where should we deploy our USQL scripts. Also, what options are available for handling our C# code behind and supporting assemblies.

    We’ll cover everything you need to know to get started developing data solutions with Azure Data Lake.

    • BI
  • Containers and Clones: Provision GIANT databases on tiny HDDs

    Shared dev databases are the root cause of so much pain. With this in mind, people are moving to dedicated dev databases for each developer. However, provisioning dev environments is often a slow, complicated and manual process. Often devs simply don’t have the diskspace. And then there is the GDPR.

    You can solve many of the these problems with virtualisation technologies like containers and clones - but there are various options and they don't all play nicely together.

    In this session we'll introduce you to Docker containers, Redgate Clones and WinDocks and explain the pros and cons of each technology. We'll also spend a bit of time discussing how to integrate masking rules to keep sensitive data out of the dev domain.

    Are you on #teamClone or #teamContainer?

    • DBA
  • dbatools - PowerShell and SQL Server Working Together

    The dbatools module now has over 300 commands and anyone who wants to start is overloaded with amount of functionality in this module.
    There are not enough hours in the day to get everything done as a DBA. We need to automate our repetitive tasks to free up time for the important and more fun tasks.
    In this session I'll show you a set of commands which will help you start automating your tasks.

    • DBA
  • Developing SQL Code to keep your DBA happy

    In this hour long session we will attempt to include lots of advice and guidance on how to write code that will easily get approved by your DBA prior to release to production. We’ll cover Unit tests, Continuous Integration, Source Control and some coding best practice.
    This will be quite a fast paced session but will aim to give you a taster of what you should include to increase the acceptance rate of your code by the approvers and how to ensure your code does what it should and that future changes don’t break it.

    • Other
  • DevOps, CI and the Data Warehouse [EN]

    DevOps and continuous integration provide huge benefits to data warehouse development. However, most BI professionals have little exposure to the tools and techniques involved. John will be showing how you can use Visual Studio Team Services (VSTS) to build and test your data warehouse code and how to use Octopus Deploy to deploy everything to UAT and production.

    This is a demo heavy session which will introduce you to exactly how powerful DevOps can be in practice and will cover:

    * Setting up Visual Studio Team Services to act as your build server
    * How to use Octopus Deploy to deploy your entire data warehouse
    * Developing a build-centric PowerShell script with psake
    * Building and deploying SQL Server Data Tools projects with DAC Publish profiles
    * Writing and running automated unit tests
    * The many problems of automating tabular model deployments

    Please visit John's blog for practical tips on how to apply DevOps techniques to your Data Warehouse: https://devops-your-dwh.com/

    • BI
  • Enhancing relational models with graph processing In SQL Server 2017.

    Analysing highly connected data using SQL is hard! Relational databases were simply not designed to handle this, but graph databases were. Built from the ground up to understand interconnectivity, graph databases enable a flexible performant way to analyse relationships, and one has just landed in SQL Server 2017! SQL Server supports two new table types NODE and EDGE and a new function MATCH, which enables deeper exploration of the relationships in your data than ever before.

    In this session, we seek to explore, what is a graph database, why you should be interested, what query patterns does they solve and how does SQL Server compare with competitors. We will explore each of these based on real data shredded from IMDB.

    • Analytics
  • Intro to Query Store

    In this session, we will look at the new Query Store feature in SQL Server 2016 and 2017. Query Store tracks changes in execution plans, allowing you to easily view performance differences and revert to older plans with a few clicks of the mouse in 2016.

    Then in 2017, Microsoft added wait stats per query plan and Automatic Tuning capabilities. Allowing DBAs more tools to troubleshoot fires with and a way to automatically resolve issues.

    In this session, we will walk through the features of Query Store, so you can understand how to use them in SQL Server 2016 and 2017.

    • DBA
  • Introduction to M

    When you’re loading data into Power BI, Excel and SSAS Tabular there’s a lot you can achieve in the Power Query Editor just by using the user interface. However, everything you do in the Query Editor is converted to code in a language called M and in more advanced data loading scenarios you’ll need to know how to write M code. In this session you’ll learn what kind of scenarios you’ll need to use M as well as the fundamentals of the language. You’ll also see several practical examples of how to use it.

    • BI
  • Migrating to Azure Managed Instances!

    During this session we will be migrating an on-prem instance to a azure managed instance. We will be looking into the considerations you have to make at the start, and how you can effectively size your managed instance. We will show you what pitfalls you might meet when moving the instance to the cloud & how you can fix them. We will also touch upon how the DR & High availability and how this fits into Managed instances.
    After this session you will be ready to start using Azure Managed Instances to move your on-prem instances.

    • Azure
  • Patterns and Best Practices in SSIS

    Writing SSIS ETL packages is easy, right ? But how do you maintain them though upgrades and changes ?
    In this session, we'll take a look at good practice, patterns, anti-patterns, and a few tricks to make your ETL fly and be free ....!

    • BI
  • Python Pipeline Primer: Data Engineering with Azure DataBricks

    Azure DataBricks brings a Platform-as-a-Service offering of Apache Spark, which allows for blazing fast data processing, interactive querying and the hosting of machine learning models all in one place! But most of the buzz is around what it means for Data Science & AI - what about the humble data engineer who wants to harness the in-memory processing power within their ETL pipelines? How does it fit into the Modern Data Warehouse? What does data preparation look like in this new world?

    This session will run through the best practices of implementing Azure DataBricks as your data ingestion, transformation and curation tool of choice. We will:

    • Introduce the Azure DataBricks service
    • Introduce Python and why it is the language of choice for Data Engineering on DataBricks
    • Discuss the various hosting & compute options available
    • Demonstrate a sample data processing task
    • Compare and contrast against alternative approaches using SSIS, U-SQL and HDInsight
    • Demonstrate how to manage and orchestrate your processing pipelines
    • Review the wider architectures and additional extension patterns

    The session is aimed at Data Engineers & BI Professionals seeking to put the Azure DataBricks technology in the right context and learn how to use the service. We will not be covering the python programming language in detail.

    • Analytics
  • SQL Server on Linux - Lets get started...

    In this session we discuss what SQL Server on Linux is, who should use it and why... We will talk about the difference between running Linux on a machine or using Docker.

    Then we kick into the demos.....
    Let’s install SQL Server on Ubuntu, connect to it using SQL Operations Studio (open source database management tool) and SQL Server Management studio.

    We will also install SQL Server in a docker container.

    We will have a look at backups/restores and mirgrating to SQL Server on Linux.

    No penguins were harmed in the writing of this presentation.

    • DBA
  • Writing Your Own Encryption Routines in SQL... and Then Cracking Them

    SQL Server gives us plenty of options when it comes to encrypting our data. But have you ever wanted to write your own encryption routines, perhaps you think that what SQL Server offers us doesn’t quite fit the bill for you?

    I’m going to look into the basics of how encryption works and then we’ll learn how we can go about writing our own encryption routines within SQL Server. When we’re happy that those routines are secure, we’ll look at ways that we can go about cracking those routines.

    Writing our own encryption within SQL might sound like a good idea and could even be something that you’ve tried out yourself but there’s a chance you might change your mind when you see how easily amateur cryptography can be broken.

    • Other
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