Speaker

Yitzhak David

Yitzhak David

DBA BDA POWER BI NOSQL K8s

Nahariyya, Israel

David Yitzhak, Team leader of Big Data and Nosql databases
David Yitzhak has over 24 years of experience with SQL Server, Oracle, and Sybase. He is an applicative & infrastructure DBA for relational and Nosql solutions (MongoDB, Redis), Hadoop CDH and Spark. David is a specialist in HA and DRP solutions, tuning, Machine learning , security, High Performance Computing, replication (Oracle & SQL Server), BI infrastructure and system engineering. David Yitzhak holds 3 Degrees from Technicon (Israel Institute of Technology): BSC Information System , MBA and ME (System engineering) and research associate in one of the enterprise Organization. He presents in Oracle open world 2010, Organize Oracle ILOUG for 3 years , SQL Server forums, Microsoft BI forums, Sqlsaturday 2016/17/18/19/20 , DATA SATURDAY , Power Camps , 3rd Israeli Conference on open source Software Architecture, One of PASS Global Hebrew Virtual Group manager, written a dozen of professional articles .

Area of Expertise

  • Media & Information

Topics

  • DBA
  • sql server
  • Oracle Database
  • mongodb
  • Redis
  • power bi
  • Microsoft Power BI
  • SQL Server Data Tools
  • SQL Server Big Data Clusters
  • SQL Server Report Server
  • SQL Server Integration Services
  • SQL Server Machine Learning Services
  • database security
  • High Availability
  • Big Data Machine Learning AI and Analytics
  • Big Data Analytics
  • Kubernetes
  • Docker
  • Hadoop
  • Oracle
  • performance tuning
  • Autmoation with PowerShell

T-SQL Window Functions in SQL Server 2019/22

I am also Oracle DBA so when SQL Server 2012 supported window functions I publish before everyone first article about SQL Server and windows function in SQL Server magazine.
In this session you will become an expert who can use window functions to solve T-SQL query problems. Replace slow cursors and self-joins with queries that are easy to write and perform better. I will cover the latest performance enhancements through SQL Server 2019 & 2022.
Window functions are useful in analytics and business intelligence reporting. Once you begin using window functions, such as ROW_NUMBER and LAG, you will discover many ways to use them. You will approach SQL Server queries in a different way, thinking about sets of data instead of individual rows. Your queries will run faster and easier to maintain.
If time permits: Data with time: system-version tables, Optimization intervals queries and time series data with moving averages and windows functions
This is a maximum demo session with minimum theory!

https://www.analytics.gt/t-sql-window-functions-in-sql-server-2019-itshak-david/

SQL Server Advanced Data Types: JSON with SQL 2019/22 polybase and Power BI from zero to a hero

I this session I will demystify the complex data types that are available to developers in modern SQL Server 2019:
How to write T-SQL to better understand this complex data types available in SQL Server and how to use these complex structures appropriately.
• Understanding Json
• Constructing JSON
• FOR JSON AUTO
• FOR JSON PATH
• Shredding JSON Data: OPENJSON( )
• Working with the JSON Data Type & Indexing JSON Data
Quick instruction to MongoDB and using SQL with open source NoSQL Booster to query MongoDB
Should I use MongoDB Json or SQL Json? Pro/Const
Connect and query JSON data using SQL 2019 polybase and T SQL only from native document DBs: MongoDB and Cosmos DB to build your organization data lake with min effort and without ETL\ELT in real time.
If time permits: SQL 2022 T SQL JSON extensions
This is a demo session only with minimum theory & lessons from the fields!
https://www.youtube.com/watch?v=BKsngBKCfNA

SQL Server 2019/22 on Containers and Kubernetes(k8s) from Zero to a Hero!

If containers are the new virtual machines, then Kubernetes are the new servers. Kubernetes is an important technology to the future of containerized applications, especially running enterprise workloads like SQL Server .In this session :
Containers Explained
Docker architecture
Installation choices
State of Windows & Linux SQL Server Containers
Demo SQL Linux Containers
How to uninstall Docker Machine under Windows 10
docker run hello-world
Exploring Docker Hub
Docker image
Docker ps
Stop running containers, remove all containers and images
Docker Inspect
Distribution Hash
Image Manifest
Running SQL Server on Linux images Container
Union Filesystem
Running SQL Server on Linux images Container
docker exec command
Runtime options with Memory, CPUs, and GPUs
copy backup file to container
Copy a file out of the container
Exploring the Container Logs
Docker Networking for SQL Server DBAs
Smart SQL Server 2019 In-Place Upgrade
If time permits:
SQL Server and Kubernetes VS Windows Clustering
Getting Started with Kubernetes on Docker Desktop
kubectl command to interact with K8s Cluster
SQL Server Docker desktop and Kubernetes without persistency Demo
Helm Chart o SQL Server Availability Groups on k8s
This is a demo session only with minimum theory & lessons from the fields!
https://www.youtube.com/watch?v=BKsngBKCfNA

SQL Server 2019/22 on Kubernetes (k 8s) from Zero to a Hero!

If containers are the new virtual machines, then Kubernetes are the new servers. Kubernetes is an important technology to the future of containerized applications, especially running enterprise workloads like SQL Server.
• Kubernetes Architecture
• The Kubernetes API
• Installing Kubernetes in short ( Because nobody will use the open source version and DBAs do not want to become sysadmins !)
• Using kubectl to Interact with Your Cluster: Operations, Resources, Kubectl Context, Exposing Services Cluster
• Persistent Data in Kubernetes.
• SQL Server in Kubernetes
• Deploying SQL Server on Kubernetes without & with persistency in Docker Desktop k8s for simplicity
• Defining SQL Server YAML Deployment
• Pod Lifecycle and Data Persistency
• Upgrading SQL Server
• Running SQL Server on Kubernetes in Production
• Advanced Disk Topologies
• Resource Management (Limits and Requests)
• Backup (and Restore)
• Monitoring SQL Server on Kubernetes
o Grafana for Performance Monitoring System Metrics
o SQL Server Metrics 162
o Kibana for Log Aggregation and Management
If time permits:
• Windows Clustering & AlwaysOn vs Kubernetes Clustering
• Azure Arc–Enabled Data Services and High Availability
Please watch my previous session from pass summit 2021: SQL Server 2019/22 on Containers and Kubernetes(k8s) from Zero to a Hero!
This is a maximum demo session with minimum theory!
https://www.youtube.com/watch?v=BKsngBKCfNA

SQL Server 2019 on Linux & Windows containers from zero to an hero

SQL Server 2019 on Linux & Windows containers . Full demo session. Become an expert with all the hidden secrets

SQL 2019 /22 AlwaysOn lessons from the fields

A practical guide for DBAs who need to implement high availability and disaster recovery for their SQL Server workload as follows:

• High availability concepts and methodologies,
• Cover how to create Windows clusters, and how to create SQL Server
• AlwaysOn Failover Clustered Instances.
• A typical use cases for AlwaysOn Availability Groups:
• Clusterless and domain-independent availability groups and configuring
• Availability Groups on Azure IaaS and Basic Availability Groups for SQL Server Standard Edition.
• The operational side of AlwaysOn : administration, monitoring, and troubleshooting of the technology.
• Windows Clustering & AlwaysOn vs Kubernetes Clustering
• If time permits: SQL 2022 HAG enhancements between on Prime and azure .
This is a maximum demo session with minimum theory!
https://www.youtube.com/watch?v=BKsngBKCfNA

Self AI in Power BI Desktop Using R and Python

If you are a BI developer, business analyst, data scientist who wants to push Power BI and transform it from being just a BI tool into an advanced data analytics tool, then this is session. R and Python languages are powerful complements to Power BI. They enable advanced data transformation techniques that are difficult to perform in Power BI in its default configuration, but become easier through the application of data wrangling features that languages such as R and Python support. I will cover:
• Adding Smart Visualizations: Trendline & Dax, Forecast , Adding a Custom Visualization from app Store , Forecasting with ARIMA& TBATS , Time Series Decomposition Chart, Scatter Chart with Trendline , Clustering with Outliers and more …
• Executing R and Python Visualizations
• Getting Power BI Ready for R & Python: Install R & Python, Load the required packages, one editor to use them all: R Studio
• Creating R Custom Visuals in Power BI Using ggplot2
• R, Python Script Visual: Table, Trendline, Time-Series Decomposition, Scatter with Trendline, Scatter with Spline, Clustering, Correlation Plot
• Load &Transforming Data into the Power BI Data Model Using R and Python
• Reading SQL Server Data using R & Python

• If time Permit Use SQL 2019 2022 Polybase with Power Bi, R and Python to explore Hadoop, Oracle, MongoDB and SQL server data sets with 1 T-SQL Query to build your organization data lake with min effort and without ETL\ELT in real time .
This is a maximum demo session with minimum theory!
https://www.youtube.com/watch?v=BKsngBKCfNA

Query Store for SQL Server 2019/22 from zero to a hero & lessons learned from the fields.

Query Store is an important and recent feature in SQL Server that provides insight into the details of query execution and how that execution has changed over time. Query Store helps to identify queries that aren’t performing well, or that have regressed in their performance. Query Store provides detailed information and wait stats that you need to resolve root causes, and it allows you to force the use of a known good execution plan. With SQL Server 2017 and later you can automate the correction of regressions in performance.
You'll Learn:
• Best practices in implementing Query Store on production servers
• Detect and correct regressions in query performance
• Lower the risk of performance degradation following an upgrade
• Use tools and techniques to get the most from Query Store
• Automate regression correction and other uses of Query Store.
• If time permits: SQL Server 2022 new feature: QS for secondary Replica, QS hints, PSP optimization, MGF, CE feedback, DOP Feedback
This is a demo session only with minimum theory & lessons from the fields!
https://www.youtube.com/watch?v=BKsngBKCfNA

Data virtualization with SQL Server 2019/22 PolyBase and integration with Power BI.

In this session we will learn about the improvements to PolyBase in SQL Server 2019/22, which allows you to extend the querying capability to data sources like SQL Server, Oracle, MongoDB, Redis, Hadoop CDH, and other data sources. You also get insights on the design, capabilities, and performance advantages of PolyBase, save ETL Processes as follows:
• Installing and Configuring PolyBase Windows & Linux & Docker
• Built-In Integrations: SQL Server, Oracle, MongoDB, Cloudera Hadoop (, which acquired Hortonworks), Integrating via ODBC: Apache Spark, Apache Hive, Redis and More
• Use SQL 2019 2022 Polybase with Power Bi, R and Python to explore Hadoop, Oracle, MongoDB and SQL server data sets with 1 T-SQL Query to build your organization data lake with min effort and without ETL\ELT in real time.
• Monitor PolyBase with Dynamic Management Views.
• Using Predicate Pushdown to Enhance Query Performance
• Build Mongo DB organization assessment reports with SSRS and Polybase
• If time permits: SQL server 2022: Data lake virtualization and object storage
This is a demo session only with minimum theory & lessons from the fields!
https://www.youtube.com/watch?v=BKsngBKCfNA

Oracle and Nosql SQL Databases for Developer Security officers

Learn basic term and how work easily with Oracle on windows, MongoDB on windows, Redis on Docker DB, and how to audit & Monitor then them and secure them from SQL and JSON injection.
• DB-Engines Ranking
• NOSQL Databases Introduction
• MongoDB for Developer & Security Officers
• MongoDB Features
• Data Types in MongoDB
• Install MongoDB on Windows
• Install MongoDB Compass
• Connect to MongoDB Server with Visual Studio Code
• Connect to MongoDB Server with NoSqlBooster
• MongoDB Basic CRUD Operations
• SQL Query with NoSQLBooster for MongoDB
• MongoDB Security
• Azure Cosmos DB's API for MongoDB
• Get started with databases on Windows Subsystem for Linux
• Redis Enterprise
• Getting Started with Redis Enterprise using Docker
• FLUSHDB FLUSHALL
• Data structure storage
• Redis Security
• CDH Hadoop Audit TLS
• Redis for Developer & Security Officers
• SQL JSon Injection for Developer Security Officers
• The Anatomy of an Attack
• SQL Queries Versus Data : Overview
• Circumventing Website Logins
• Identifying the Risk in Code
• Characters that are often used in SQL injection attacks.
• Types of SQL Injection
• Defending Against Attacks
• Summery Questions
If time permits:
• Use SQL 2019 2022 Polybase with Power Bi, R and Python to explore Hadoop, Oracle, MongoDB and SQL server data sets with 1 T-SQL Query to build your organization data lake with min effort and without ETL\ELT in real time
This is the basic of basic for every security offices and summarize of years of experience with simple basic tools which give you the power to discover unauthorized access.
This is Only demo session and minimal, theory

Columnstore Indexes in SQL Server 2019/22 with Analytics, OLAP Workloads, Polybase and Power BI

A clustered columnstore index (CCI) is usually the best choice providing optimal query performance for almost large tables. I am using columnstore indexes (CSI) since SQL 2012 and have written several articles.
I will demonstrate real time life scenarios of using CCI to store analytic data efficiently like : analytics, data science , experiments results , Data warehouse , logging & Audit
Reporting and analytics. Real- time analytics on OLTP be done with CCI indexes very easy for developer and Power Bi reports. By default, Synapse Analytics creates a CCI.
I will Cover
• Batch & Row Execution and using query store to check performance
• Delete and Update Operations
• Bulk Loading Data
• Segment and Rowgroup Elimination
• Partitioning
• Nonclustered Columnstore Indexes on Rowstore Tables
• Nonclustered Rowstore Indexes on Columnstore Tables
• Maintenance & Performance
• Columnstore Indexes on Temporary Tables & Memory-Optimized tables
• Using analytic data in OLTP Database with CCI. Analytic data sources can DW, Hadoop, SQL Server Polybase and more . I will shpw you how Power BI developer and application developer can gain hundreds percent of performance improvement very easy !

This is a demo session only with minimum theory & lessons from the fields!
https://www.youtube.com/watch?v=BKsngBKCfNA

Analytics in Power BI with R and Python with SQL Server 2019 2022 ML Service & Polybase

If you are a BI developer, business analyst, data scientist who wants to push Power BI and transform it from being just a BI tool into an advanced data analytics tool, then this is session. R and Python languages are powerful complements to Power BI. They enable advanced data transformation techniques that are difficult to perform in Power BI in its default configuration, but become easier through the application of data wrangling features that languages such as R and Python support. I will cover:
• Create data visualizations through R using the ggplot2 package
• Ingest data using R and Python to overcome the limitations of Power Query
• Use String manipulations not otherwise possible in Power BI using R and Python
• Use SQL 2019 2022 Polybase with Power Bi, R and Python to explore Hadoop, Oracle, MongoDB and SQL server data sets with 1 T-SQL Query to build your organization data lake with min effort and without ETL\ELT in real time .
• If time Permit: Apply pre-trained models in SQL Server Machine Learning Services models
This is a maximum demo session with minimum theory!
https://www.youtube.com/watch?v=BKsngBKCfNA

Nosql SQL Databases for Developer Security officers

Learn basic term and how to Defense You Oracle , SQL Server , MongoDB, Redis , Docker DB , Hadoop, data lakes in 50 Minutes and SQL Injection .

This is the basic of basic for every security offices and summarize of years of experience with simple basic tools which give you the power to discover unauthorized access.

This is Only demo session and minimal , theory

SQL Server 2019/22 on Containers and Kubernetes(k8s) from Zero to a Hero!

If containers are the new virtual machines, then Kubernetes are the new servers. Kubernetes is an important technology to the future of containerized applications, especially running enterprise workloads like SQL Server .In this session :
Containers Explained
Docker architecture
Installation choices
Install Docker Desktop on Windows
State of Windows & Linux SQL Server Containers
Demo SQL Linux Containers
How to uninstall Docker Machine under Windows 10
docker run hello-world
Exploring Docker Hub
Docker image
Docker ps
Stop running containers, remove all containers and images
Docker Inspect
Distribution Hash
Image Manifest
Running SQL Server on Linux images Container
Union Filesystem
Running SQL Server on Linux images Container
docker exec command
Runtime options with Memory, CPUs, and GPUs
copy backup file to container
Copy a file out of the container
Exploring the Container Logs
Docker Networking for SQL Server DBAs
Smart SQL Server 2019 In-Place Upgrade
If time permits :
SQL Server and Kubernetes VS Windows Clustering
Getting Started with Kubernetes on Docker Desktop
kubectl command to ineteract with K8s Cluster
SQL Server Docker desktop and Kubernetes without persistency Demo
Helm Chart o SQL Server Availability Groups on k8s
SQL Server Docker desktop and Kubernetes with persistency Demo
only with minimum theory & lessons from the fields !

T-SQL Window Functions in SQL Server 2019/22

I am also Oracle DBA so when SQL Server 2012 supported window functions I publish before everyone first article about SQL Server and windows function in SQL Server magazine .
In this session you will become an expert who can use window functions to solve T-SQL query problems. Replace slow cursors and self-joins with queries that are easy to write and perform better. I will covers the latest performance enhancements through SQL Server 2019 & 2022.
Window functions are useful in analytics and business intelligence reporting. Once you begin using window functions, such as ROW_NUMBER and LAG, you will discover many ways to use them. You will approach SQL Server queries in a different way, thinking about sets of data instead of individual rows. Your queries will run faster and easier to maintain.
If time permits :Data with time : system-version tables , Optimization intervals queries . time series data with moving averages and windows functions

Query Store for SQL Server 2019/2022 from zero to an hero & lessons learned from the fields .

Query Store is an important and recent feature in SQL Server that provides insight into the details of query execution and how that execution has changed over time. Query Store helps to identify queries that aren’t performing well, or that have regressed in their performance. Query Store provides detailed information and wait stats that you need to resolve root causes, and it allows you to force the use of a known good execution plan. With SQL Server 2017 and later you can automate the correction of regressions in performance.

You'll Learn :
• Best practices in implementing Query Store on production servers
• Detect and correct regressions in query performance
• Lower the risk of performance degradation following an upgrade
• Use tools and techniques to get the most from Query Store
• Automate regression correction and other uses of Query Store.
• If time permits : SQL Server 2022 new feature !

Data virtualization with SQL Server 2019 PolyBase and integration with Power BI .

In this session we will learn about the improvements to PolyBase in SQL Server 2019, which allows you to extend the querying capability to data sources like SQL Server, Oracle, MongoDB, Redis, Hadoop CDH, and other data sources. You also get insights on the design, capabilities, and performance advantages of PolyBase, save ETL Processes as follows:
• Installing and Configuring PolyBase Windows & Linux
• Connecting to Hadoop
• Using Predicate Pushdown to Enhance Query Performance
• Packet Capture With\Without Predicate Pushdown
• When to use Predicate Pushdown
• Limitations on Pushdown with Complex Filters
• Built-In Integrations: Oracle, MongoDB , Radis and More Integrating via ODBC : Apache Spark , Apache Hive, Microsoft Excel Monitor PolyBase with Dynamic Management Views .
• PolyBase Query Tuning , Execution Plans and Statistics PolyBase Scenarios : ETL VS ELT jobs
This is a demo session only with minimum theory & lessons from the fields !

Analytics in Power BI with R and Python with SQL Server 2019 ML Service & Polybase : From zero to an

If you are a BI developer, business analyst, data scientist who wants to push Power BI and transform it from being just a BI tool into an advanced data analytics tool, then this is session . R and Python languages are powerful complements to Power BI. They enable advanced data transformation techniques that are difficult to perform in Power BI in its default configuration, but become easier through the application of data wrangling features that languages such as R and Python support.
• Create data visualizations through R using the ggplot2 package
• Ingest data using R and Python to overcome the limitations of Power Query
• Apply pre-trained models in SQL Server Machine Learning Services models
• Use String manipulations not otherwise possible in Power BI using R and Python
• Use SQL 2019 Polybase with Power Bi , R and Python to explore Hadoop , Oracle , MongoDB and SQL server data sets with 1 T-SQL Query .
My previous lectures : Practical SQL 2014 Data Mining and introduction to R ,Practical data science and Performance patterns for a DBA with SQL Server 2017

Data virtualization with SQL Server 2019 PolyBase and integration with Power BI

In this session we will learn about the improvements to PolyBase in SQL Server 2019, which allows you to extend the querying capability to data sources like SQL Server, Oracle, MongoDB, Redis, Hadoop CDH, and other data sources. You also get insights on the design, capabilities, and performance advantages of PolyBase, save ETL Processes as follows:
• Installing and Configuring PolyBase Windows & Linux
• Connecting to Hadoop
• Using Predicate Pushdown to Enhance Query Performance
• When to use Predicate Pushdown
• Limitations on Pushdown with Complex Filters
• Built-In Integrations: SQL Server , Oracle, MongoDB ,Cloudera Hadoop , Redis and More Integrating via ODBC : Apache Spark , Apache Hive, Microsoft Excel Monitor PolyBase with Dynamic Management Views .
• PolyBase Query Tuning , Execution Plans and Statistics PolyBase Scenarios : ETL VS ELT jobs .
This is a demo session only with minimum theory & lessons from the fields !
https://www.sqlsaturday.com/1003/Speakers/Submission.aspx

Analytics in Power BI with R and Python with SQL Server 2019 ML Service & Polybase

If you are a BI developer, business analyst, data scientist who wants to push Power BI and transform it from being just a BI tool into an advanced data analytics tool, then this is session . R and Python languages are powerful complements to Power BI. They enable advanced data transformation techniques that are difficult to perform in Power BI in its default configuration, but become easier through the application of data wrangling features that languages such as R and Python support.
• Create data visualizations through R using the ggplot2 package
• Ingest data using R and Python to overcome the limitations of Power Query
• Apply pre-trained models in SQL Server Machine Learning Services models
• Use String manipulations not otherwise possible in Power BI using R and Python
• Use SQL 2019 Polybase with Power Bi , R and Python to explore Hadoop , Oracle , MongoDB and SQL server data sets with 1 T-SQL Query .
My previous lectures : Practical SQL 2014 Data Mining and introduction to R ,Practical data science and Performance patterns for a DBA with SQL Server 2017

Self AI , NLP , R and Python , SQL Server 2019 ML Service & Polybase with Power BI Desktop

Learn how to use AI features are built into Power BI Desktop and help you to gain new insights from existing data. Automatically using button or through writing Data Analysis Expressions (DAX) or writing code in R, Python, or M languages. This session show how to use the entire suite of AI features to you with clear guided examples :
• Asking Questions in Natural Language.
• Insights Feature .
• Adding Smart Visualizations
• Create data visualizations through R using the ggplot2 package
• Ingest data using R and Python to overcome the limitations of Power Query
• Apply pre-trained models in SQL Server Machine Learning Services models
Use String manipulations not otherwise possible in Power BI using R and Python
• Using NLP with R & Python and Power BI
• Use SQL 2019 Polybase with Power Bi , R and Python to explore Hadoop , Oracle , MongoDB and SQL server data sets with 1 T-SQL Query .

SQL Server Advanced Data Types : JSON with SQL 2019/22 polybase and Power BI from zero to an hero

I this session I will demystify the complex data types that are available to developers in modern SQL Server 2019:
How to write T-SQL to better understand this complex data types available in SQL Server and how to use these complex structures appropriately.
Connect and import JSON data using SQL 2019 polybase and T SQL only from native document DBs: MongoDB and Cosmos DB .
Use SQL 2019 Polybase with Power Bi , Power query , R and Python to explore JSON , document DBs and SQL server data sets with 1 T-SQL Query .
If time permits : SQL 2022 T SQL JSON extensions
This is a demo session only with minimum theory & lessons from the fields !

Query Store hints in SQL Server 2022 and parameter sniffing Problem

Query Store hints leverage Query Store to provide a method to shape query plans without changing application code. Now are available in SQL Server 2022
You already know you have parameter sniffing issues, and now you need to figure out how to fix it. Learn how we resolve bad Parameter Sniffing with Query Store in SQL 2016/17/19 and how it can be resolved more efficiently and easy with Query Store hints in SQL 2022, to reduce the blast radius with index changes, query tuning, and database-level settings. I will discuss whether you should use Query Store hint or Parameter sensitive plan optimization, also new in SQL 2020 and it is also based on Query Store.

Update Conference Prague 2022 Upcoming

November 2022 Prague, Czechia

Azure Back to School 2022

September 2022

Code PaLOUsa 2022

August 2022 Louisville, Kentucky, United States

Power BI Portugal 2022 Sessions User group

June 2022

MVP Fusion & Friends

February 2021

Yitzhak David

DBA BDA POWER BI NOSQL K8s

Nahariyya, Israel