Yitzhak David
DBA BDA POWER BI NOSQL K8s
Nahariyya, Israel
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David Yitzhak, Team leader of Big Data and Nosql databases
David Yitzhak has over 24 years of experience with SQL Server, Oracle, Sybase and PostgreSQL . 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 , GroupBy Europe , Future Data Driven , Data Platforms GlobalHebrew , Code PaLOUsa 2021\2 , Pass summit 2021 and more …
Awards
Area of Expertise
Topics
Extend Power BI with R, Python and SQL Server 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:
• Configuring Python with Power BI
• Solving Common Issues When Using Python and R in Power BI
• Importing Unhandled Data Objects
• Using Regular Expressions in Power BI
• Logging Data from Power BI to External Sources
• Loading Large Datasets beyond the Available RAM in Power BI
• Boosting Data Loading Speed in Power BI with Parquet Format
• Create data visualizations through R using the ggplot2 package
• Using the Grammar of Graphics in Python
• 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
• Using Machine Learning Without Premium or Embedded Capacity
• Using the SQL Server Extensibility Framework’s R and Python engines with Power BI
• 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!
Self AI in Power BI Desktop Using R, Python and OpenAI
This session we will learn about Power BI ML and OpenAI as follows:
Preparing and Ingesting Data with Power Query consists of data transformation and modeling to prep data for both a Power BI dataset and queries that will be used to build ML models.
Exploring Data Using Power BI and Creating a Semantic Mode o discover features for ML models.
Model Data for Machine Learning in Power BI will explore the data using Power BI to discover potential features that can be used to build ML models.
Discovering Features Using Analytics and AI Visuals leverages Power BI as an analytics and data visualization tool to discover new features for the ML queries.
Discovering New Features Using R and Python Visuals, discovers additional features for the ML queries using the R and Python visuals in Power BI
Building Machine Learning Models with Power BI, builds ML models in Power BI. The ML queries designed in the previous chapters are used to build three ML models for binary classification, general classification, and regression predictions.
Evaluating Trained and Tested ML Models, reviews the three ML models that were built in Power BI. The testing results are reviewed and explained in the context of predictive capabilities.
Use Cases for OpenAI, plans for the use of OpenAI with the project and workshop.
This is a maximum demo session with minimum theory! My previous lecture is Self AI in Power BI Desktop Using R, Python and ChatGPT
Encryption in SQL Server 2022 from zero to a hero!
Encryption is a critical component in protecting your data from falling into the wrong hands.. Since 2016 Microsoft has been doing excellent work in adding to the encryption feature set within SQL Server, making encryption more secure, easier to use, and accessible to everyone who uses the product.
1. At-Rest Encryption Background about Transparent Data Encryption (TDE) , set up & mange TDE , Backup Encryption how to work with encrypted backups.
2. Introduction : Column Encryption Using Always Encrypted: background, set Up, Executing Queries , Encrypting Existing Data , Limitations and Key Rotation
This is a maximum demo session with minimum theory but it based on 25 years of experience and hundreds of lectures in tuning area including latest's version of SQL Server 2022 & Oracle 19/21/23C!
Data Governance using Azure Purview
Join us to learn how to easily and quickly produce a holistic and up-to-date map of an organization's data source map with automatic data discovery capabilities, data classification and content worlds, and an end-to-end data flow hierarchy.
In this session Itai Binyamin will demonstrate how to use Microsoft's new service - Azure Purview. This is a cloud service for managing the data sources and the various of content in our organization. The service provides an end-to-end solution to the world of Data Governance - Azure Purview.
From 0 to 100 in one session!
# Note! We use Meetup system for event registration only. Please make sure you signed up for a group to stay in touch and get more information including links to download presentations and watch recordings: https://bit.ly/GlobalHebrew
Power BI Machine Learning and OpenAI: The fast track & the complete guide
Explore data through business intelligence, predictive analytics, and text generation:
Data Modeling, and Planning
• Preparing and Ingesting Data with Power Query
• Exploring Data Using Power BI and Creating a Semantic Model
• Model Data for Machine Learning in Power BI
Artificial Intelligence and Machine Learning Visuals and Publishing to the Power BI Service:
• Discovering Features Using Analytics and AI Visuals & R and Python Visuals
• Deploying Data Ingestion and Transformation Components to the Power BI Cloud Service
Building Machine Learning Models with Power B:
• Iterating & Evaluating Trained and Tested ML Models
• Applying Power BI ML Model
Integrating OpenAI with Power BI
This is a demo session only with minimum theory!
OpenAI , ChatGPT and GPT4 for Power BI Desktop
• Introduction to ChatGPT and OpenAI
• Prompt Engineering for with ChatGPT and GPT4 : Quick Introduction
• Clear and effective prompts to guide ChatGPT, including techniques for setting context, using explicit instructions, and experimenting with different prompt styles to achieve desired outcomes.
• ChatGPT chatbot technology with Power BI Desktop integration allows users to interact with data and reports through NLP queries. A step-by-step guidance on setting up the integration and use of ChatGPT to enhance functionality.
This is a demo session only with minimum theory!
T-SQL Window Functions in PostgreSQL 15
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 PostgreSQL 15.
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. I will cover:
• Exploring Ranking Functions: ROW_NUMBER, RANK VS DENSE_RANK
• Window Aggregate Functions
• Running and Moving Aggregates
• Using Frames and Window
• LAG and LEAD windows functions
• FIRST_VALUE and LAST_VALUE windows functions
• Statistical Functions
• Tuning windows functions
• T-SQL Windows Function in SQL Server PostgreSQL 15
https://www.analytics.gt/t-sql-window-functions-in-sql-server-2019-itshak-david/
SQL Server on Containers and Kubernetes from Zero to a Hero in the year 2022
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
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 !
Adaptive query plans in SQL Server 2022 from zero to a hero!
Intelligent query processing—a family of features whose purpose is to improve the performance of existing workloads with no application changes or minimal implementation effort. I will cover the new features of adaptive query plans in SQL server 2022: Memory grant feedback and Adaptive join.
Memory grant feedback feature was introduced with SQL Server 2017 and has been improved and enhanced in the following two releases. Original release was memory grant feedback for batch mode. Row mode version was introduced in SQL Server 2019. This feature helped to adjust memory grant sizes for both batch and row mode operators. SQL Server 2022 improves on this feature by adding persistence and percentile capabilities.
New to SQL Server 2022 is that some of the features, such as memory grant feedback, require the query store to persist the information of queries and plans. Memory grant feedback had the limitation that the feedback was lost when plans were evicted or SQL Server was restarted.
Choosing an incorrect join algorithm during query optimization due to cardinality estimation errors could seriously impact the performance of your query. Main purpose of an adaptive join is to leave the decision of which physical join to utilize until the execution time. Although memory grant feedback started with batch mode and was later enhanced to include row mode, adaptive join remains a batch mode-only feature.
This is a maximum demo session with minimum theory!
T-SQL Window Functions in SQL Server 2022
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. I will cover :
• Exploring Ranking Functions: ROW_NUMBER, RANK VS DENSE_RANK
• Window Aggregate Functions
• Running and Moving Aggregates
• Using Frames and Window
• LAG and LEAD windows functions
• FIRST_VALUE and LAST_VALUE windows functions
• T-SQL Windows Function in SQL Server 2022
• Statistical Functions
• Tuning windows functions
https://www.analytics.gt/t-sql-window-functions-in-sql-server-2019-itshak-david/
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, Python and ChatGPT
If you are a BI developer, business analyst, or 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:
• 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
• Load &Transforming Data into the Power BI Data Model Using R and Python
• Reading SQL Server Data using R & Python
• ChatGPT chatbot technology with Power BI Desktop integration allows users to interact with data and reports through NLP queries. A step-by-step guidance on setting up the integration and use of ChatGPT to enhance functionality.
This is a demo session only with minimum theory!
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!
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
SQL Server 2022 & Azure SQL DB Wait Statistics from zero to a hero!
Learn how the database engine processes a query and how to query wait statistics information through various SQL Server dynamic management views (DMVs). I will show you how Query Store (QS) create and gather metrics to build your own baselines.
Next, I will talk about Wait Types, dives into specific waits, the causes, some examples, and resolutions. I will break down waits into categories by CPU, IO, backups, locks, latches, high-availability and disaster-recovery, preemptive, background and miscellaneous, and In-Memory OLTP. I will show you how QS can find it in minutes!
This is a maximum demo session with minimum theory but it based on 25 years of experience and hundreds of lectures in tuning area including latest's version SQL Server 2022!
Auditing & Ledger for Microsoft SQL Server and Azure SQL from zero to a hero!
I have 25 years of experience with SQL Server & Oracle hardening and security
I will cover all the types of auditing available in SQL Server, Azure SQL, and AWS RDS SQL Server. You will learn how to use SQL Server Audit and SQL 2022 Ledger to track changes to schema, security, and configurations. Not all changes can be captured with these features, so the I will cover other features like change data capture (CDC), temporal tables, and common criteria compliance. I will cover auditing methods in both Azure SQL Database and Azure SQL Managed Instance. you will learn how to use SQL Server Audit in AWS RDS SQL Serve.
This is a maximum demo session with minimum theory but it based on 25 years of experience and hundreds of lectures in tuning area including latest's version SQL Server 2022!
Oracle DB Programming: new Features in SQL, PL/SQL, and JSON from zero to a hero!
SQL is a powerful. Learn how to answer complex questions with a few lines. PL/SQL includes many extensions to make SQL even easier to work with Oracle Docs Database is huge. Session is about Modern Oracle Database Programming with focus on: Functionality and Enhancements: Collections , Analytic Functions ,Pagination and Set Operators, JSON in DB Path Expressions ,Manipulate JSON Temporary Table , SQL Macro, Calling PL/SQL from SQL and Upgrade Your Application with Zero Downtime .
This is a maximum demo session with minimum theory but it based on 25 years of experience and hundreds of lectures in tuning area including latest's version Oracle 19/21/23C and SQL Server 2022!
Encryption in SQL Server 2022 from zero to a hero!
Encryption is a critical component in protecting your data from falling into the wrong hands.. Since 2016 Microsoft has been doing excellent work in adding to the encryption feature set within SQL Server, making encryption more secure, easier to use, and accessible to everyone who uses the product.
1. At-Rest Encryption Background about Transparent Data Encryption (TDE) , set up & mange TDE , Backup Encryption how to work with encrypted backups.
2. Column Encryption Using Always Encrypted: background, set Up , Executing Queries , Encrypting Existing Data , Limitations and Key Rotation
This is a maximum demo session with minimum theory but it based on 25 years of experience and hundreds of lectures in tuning area including latest's version of SQL Server 2022 & Oracle 19/21/23C!
Running Oracle DB in Linux Containers from zero to a hero!
• Installing Docker Desktop and Docker Engine for Linux
• Image & Container & Volume Management & Networking & Union Filesystem
• Oracle Database Quick Start & introducing Docker and Oracle
• Working with oracle container: Hostname, Directories, Configuration Files , Binaries, Volumes
• Persistency
• Mount Types
• Customize Container Environments
• Container Networks
• Building and Customizing Images: Dockerfile
This is a maximum demo session with minimum theory but it based on 25 years of experience and hundreds of lectures in tuning area including latest's version of SQL Server 2022 & Oracle 19/21/23C and the lecture SQL Server 2022 on Linux Containers and Kubernetes from Zero to a Hero!
Intelligent Query Processing in SQL Server 2022 next Gen the fast track!
Intelligent query processing—a family of features whose purpose is to improve the performance of existing workloads with no application changes or minimal implementation effort. Originally, SQL Server 2017, up to SQL Server 2022. In will cover:
• Overview of intelligent query processing
• Query Store hints in SQL Server 2022 and parameter sniffing Problem
• Parameter Sensitivity Plan optimization (PSP). Does it really work in all scenarios?
• Memory grant feedback: Percentile and persistence mode
• Adaptive joins and thresholds.
If time permits:
• Cardinality estimation feedback
• Degree of parallelism feedback
• Interleaved execution
• Table variable deferred compilation
This is a maximum demo session with minimum theory and real experience over more than 24 year!
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 2022 and it is also based on Query Store.
This is a maximum demo session with minimum theory and real experience over more than 24 year!
Query Store for SQL Server 2022 from zero to a hero & lessons learned from the fields.
Query Store (QS) 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. QS helps to identify queries that aren’t performing well, or that have regressed in their performance. QS 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:
• Troubleshooting Without QS
• Architecture of the QS
• Standard QS Reports
• Demo: Resolving bad Parameter Sniffing with QS : SQL 2016 2017 2019
• Query Store Use Cases
• Query Store Catalog Views
• Configuring QS
• Forcing Plans
• QS Configuration Best Practices
• Auto Plan Correction and Wait Statistics
• What new in SQL Server 2022 QS?
o QS By default
o QS hints
o QS hints Demo: Resolving bad Parameter Sniffing with Query Store : SQL 2022
o Qs for Secondary replica
o Memory grant feedback : Percentile and Persistence mode memory grant feedback
o Degree of parallelism (DOP) feedback.
o Parameter sensitive plan optimization
This is a demo session only with minimum theory & lessons from the fields!
SQL Server 2022 on Linux Containers and Kubernetes from Zero to a Hero!
SQL Server 2022 on Linux Containers and Kubernetes 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
Docker Inspect
Distribution Hash
Image Manifest
Union Filesystem
Running SQL Server on Linux images Container
Runtime options with Memory, CPUs, and GPUs
Exploring the Container Logs
Docker Networking for SQL Server DBAs
Smart SQL Server 2022 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!
NoSQL Databases for Developer & Security officers: MongoDB & Redis. The fast track!
Learn basic term and how work easily with 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
• Connect to MongoDB Server with NoSqlBooster & Visual Studio Code & MongoDB Compass
• MongoDB Basic CRUD Operations
• MongoDB Security
• Azure Cosmos DB's API for MongoDB
Redis for Developer & Security Officers:
• Redis Enterprise
• Getting Started with Redis Enterprise using Docker
• Data structure storage
• Redis Security
If time permits:
• 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
• 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 office 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 2022 from zero to a hero!
A clustered columnstore index (CCI) is usually the best choice providing optimal query performance for almost large tables. I am using columnstore indexes 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, DW, logging & Audit, reporting and analytics. Real- time analytics on OLTP be done with CCI indexes. 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
SQL 2022 new features : Columnstore and Batch Mode Improvements:
• Ordered Clustered Columnstore Index
• Columnstore String Improvements
• Vector Extension to Improve Batch Mode
• Columnstore Segment Elimination Enhancements
This is a demo session only with minimum theory & lessons from the fields!
https://www.youtube.com/watch?v=BKsngBKCfNA
Auditing and Ledger together in SQL Server 2022 from zero to a hero!
Passive security refers to the practice of logging user activity in order to avoid the threat of nonrepudiation. SQL Server 2022 also introduces Ledger, which uses blockchain technology to make data tamper-evident, which allows for streamlined auditing processes. In this session, we will discuss the new ledger functionality, how to implement it and how to use it to discover who has changed data. I will demonstrate the concepts of auditing and demonstrating how to implement SQL Server Audit, including creation of custom audit event. I will Cover :
• Auditing and Ledger Ledger
• Append-Only Ledger Tables
• Ledger Database
• Database Ledger and Digest Management
• Creating a Server Audit Specification
• Enabling and Invoking Audits
• Updateable Ledger Tables
• Database Audit Specifications
• Auditing the Audit
This is a demo session only with minimum theory & lessons from the fields!
DAX and Data Modeling in Power BI: Creating the Perfect Semantic Layer
Explore data through business intelligence, predictive analytics, and text generation:
Data Modeling Components
Star Schema and Data Modeling Common Best Practices
Star Schema Preparation in Power Query Editor
Data Preparation Common Best Practice
Data Modeling Components
Preparing and Ingesting Data with Power Query
Preparing and Ingesting Data with OpenAI & ChatGPT
Exploring Data Using Power BI and Creating a Semantic Model
Exploring Data Using Power BI and Creating a Semantic Model with OpenAI & ChatGPT
Model Data for Machine Learning in Power BI
Star Schema and Data Modeling Common Best Practices
Advanced Data Modeling Techniques
More Advanced Data Warehousing: SCDs
Row-Level and Object-Level Security
Direct Query Connections to Power BI Datasets
New Options, Features, and DAX Functions
This is a demo session only with minimum theory!
SQL Server 2022 on containers, Docker, Podman, Kubernetes (k8s), and ChatGPT!
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: Podman & WSL
Demo SQL Linux Containers
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 2022 In-Place Upgrade
If time permits:
SQL Server and Kubernetes VS Windows Clustering
Kubernetes on Docker Desktop
kubectl command to interact with K8s Cluster
SQL Server Docker desktop and Kubernetes without persistency Demo
Working in Docker Using ChatGPT
Demo: Build Multi-Stage Docker Image
This is a demo session only with minimum theory & lessons from the fields!
https://www.youtube.com/watch?v=BKsngBKCfNA
PostgreSQL Query Optimization for SQL Server DBAs: The ultimate Guide.
The Ultimate Guide to Building Efficient Queries for SQL server DBA. PostgreSQL becomes more and mor popular (DB-Engines Ranking)
I will give quick overview about PostgreSQL editions and tuning tools : Open Source, EDB PostgreSQL, Percona PostgreSQL and Azure Database for PostgreSQL Flexible Server and tuning tools and features vs SQL Server from real world experience. Then I will teach you to optimize your queries based on your previous knowledge from SQL Serve as follows:
Optimizing OLTP and OLAP: PostgreSQL Specifics
Algorithm Cost Models
Data Access Algorithms: Full Scan, Index-Based Table Access, Index-Only Scan
B-Tree Indexes and Selection Criteria Other Kinds of Indexes
Combining Relations: Nested Loops, Hash-Based Algorithms, Sort-Merge Algorithm and compration
Understanding Execution Plans
Short Queries and Indexes
What are short queries?
Selection Criteria: Index Selectivity &Unique Indexes and Constraints
Indexes and Non-equal Conditions and Column Transformations
Indexes and the like Operator
Using Multiple Indexes
Compound Indexes
Partial Indexes
Indexes and Join Order
Why Does PostgreSQL Ignore Index?
Let PostgreSQL choose Right Indexes
Build the Right Index(es)
Long Queries and Full Scans
What are long queries?
Full Scans & Hash Joins
Long Queries and the Order of Joins: Semi-joins and Join Order, Anti-join. Semi- and Anti-joins Using the JOIN Operator, When to Specify Join Order
Grouping: Filter First, Group Last & Grouping: Group First, Select Last
Using SET Operations
Avoiding Multiple Scans
More Long Queries Techniques
Temporary Tables and CTEs
Views: Why Use Views?
Creating, using, Refreshing and Optimizing Materialized Views
Partitioning
Azure Data Factory for Data Engineers & SSIS developers
• Creating an Azure Data Factory Instance
• First Pipeline
• The Copy Activity
• Pipeline Expressions
• Parameters
• Controlling Flow
• Data Flows
• Integration Runtimes
• Power Query in ADF
• Publishing to ADF
• Triggers
• Monitoring
• Tools and Other Services
This is a demo session only with minimum theory & lessons from the fields!
Implementing Graphs SQL Server and Azure SQL
In this session we will build graph solutions using SQL Server and Azure SQL
• I will Demonstrates multiple approaches for implementing graph structures in SQL Server and Azure SQL. I will compare this solution and other Databases: PostgreSQL, MongoDB and Graph databases .
• Provides coded examples of every technique that can be adapted to readers’ needs.
• Background on Graphs, Data Structures and Algorithms
• SQL Graph Table Basics
• Tree Structures, Algorithms, and Performance
• Directed Acyclic Graphs
This is a demo session only with minimum theory & lessons from the fields!
AI database agents for SQL server, Oracle & PostgreSQL DBAs & Developers
Learning about AI database agents: how to develop A I agents that area able to interact with tabular data as well as SQL databases. So we'll learn about function calls as well as interacting or leveraging OpenAI system API with SQL databases and A I agents. I'm going to show users to type in natural language just like English. And then you'll be able to use an agent that will interact with data in this case SQL database and table or data in the form of CSV. Topics:
• Setup Development Environment
• AI Agents Deep Dive
• Building Database AI Agents - Deep Dive
• Building Database Agents - CSV Agents
• Building Database Agents - SQL Database Agents
• OpenAI Function Calling & SQL Database
• Function Calling - Using Function Calling with Database AI Agents
• OpenAI Assistants API - Leveraging the Assistants API for SQL Database AI Agents
Essential Concepts of Vector Databases for DBAs
Session especially for DBAs, developers, software engineers who want to learn about vector databases Fundamentals and their implementation in SQL Server and PostgreSQL, also you have Vector Databases Solutions that I will also introduce. Topic will be covered:
• Traditional vs Vector Databases - Differences
• Vector Databases Solutions - Top 5 Vector Databases
• Building Vector Databases - Hands-on - Chroma Vector Database
• Common Measures of Vector Similarity
• Vector Databases and LLM - the Full Workflow
• Vector Databases & the Langchain Framework
• Choosing the Right Vector Database
Data.TLV Summit 2024 Sessionize Event
Global Power Platform Bootcamp 2024 | Zürich Edition - #GPPBZH Sessionize Event
Global AI Summit 2024 Sessionize Event
90DaysOfDevOps - 2024 Community Edition Sessionize Event
Data Platform Diversity, Equity, and Inclusion Virtual Group User group Sessionize Event
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Future Data Driven Summit 2023 Sessionize Event
Power BI Portugal 2023 S1 Sessions User group Sessionize Event
SQLSaturday MN 2022 Sessionize Event
Malta Community: Query Optimization in SQL Server 2022: From Zero to Hero Sessionize Event
PASSMN Monthly Meeting 2022/2023 User group Sessionize Event
Update Conference Prague 2022 Sessionize Event
Virtual M365 Friday Cincinnati Sessionize Event
Future Data Driven Summit 2022 Sessionize Event
Triangle Area SQL Server User Group (TriPASS) User group Sessionize Event
Azure Back to School 2022 Sessionize Event
Code PaLOUsa 2022 Sessionize Event
Power BI Portugal 2022 Sessions User group Sessionize Event
philly.NET Code Camp 2022 Sessionize Event
Global Power Platform Bootcamp - Hyderabad Sessionize Event
Global Power Platform Bootcamp - PH & Delhi Community Sessionize Event
Surati Tech Talks 2022 Sessionize Event
PASS Data Community Summit 2021 Sessionize Event
DBCC International 2021 Sessionize Event
Data Saturday Sofia Sessionize Event
Scenic City Summit 2021 Sessionize Event
Data Saturday Plovdiv Sessionize Event
Code PaLOUsa 2021 Sessionize Event
Virtual 2021 Data.SQL.Saturday.LA Sessionize Event
Bizz Summit ES Sessionize Event
Malta Data Saturday 2021 Sessionize Event
Data Saturday #5 Redmond 2021 Sessionize Event
Virtual Power BI Days Germany 2021-03-23 Sessionize Event
datasaturdays.com Pordenone 2021 #0001 Sessionize Event
MVP Fusion & Friends Sessionize Event
Global Power Platform Bootcamp - Kuala Lumpur, Malaysia Sessionize Event
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Data Saturday Guatemala 2021 Sessionize Event
Yitzhak David
DBA BDA POWER BI NOSQL K8s
Nahariyya, Israel
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