An overview of blockchain fundamentals, including examples of Oracle 20c Blockchain Tables. Includes concepts of trust, immutability, hashes, distributed nodes, and cryptography.
Blockchain for the DBA and Data ProfessionalKaren Lopez
With all the hype around blockchain, why should a DBA or other data professional care? In this session, we will cover the basics of blockchain as it applies to data and database processes:
Immutability
Verification
Distribution
Cryptography
Transactions
Trust
We will look at current offerings for blockchain features in Azure and in database and data stores. Finally, we'll help you identify the types of business requirements that need blockchain technologies.
You will learn:
Understand the valid uses of blockchain approaches in databases
How current technologies support blockchain approaches
Understand the costs, benefits, and risks of blockchain
This one-hour presentation covers the tools and techniques for migrating SQL Server databases and data to Azure SQL DB or SQL Server on VM. Includes SSMA, DMA, DMS, and more.
PaaSport to Paradise: Lifting & Shifting with Azure SQL Database/Managed Inst...Sandy Winarko
This session focuses on the all PaaS solution of Azure SQL DB/Managed Instance (MI) + SSIS in Azure Data Factory (ADF) to lift & shift, modernize, and extend ETL workflows. We will first show you how to provision Azure-SSIS Integration Runtime (IR) – dedicated ADF servers for running SSIS – with SSIS catalog (SSISDB) hosted by Azure SQL DB/MI, configure it to access data on premises using Windows authentication and Virtual Network injection/Self-Hosted IR as a proxy, and extend it with custom/Open Source/3rd party components. We will next show you how to use the familiar SSDT/SSMS tools to design/test/deploy/execute your SSIS packages in the cloud just like you do on premises. We will finally show you how to modernize your ETL workflows by invoking/scheduling SSIS package executions as first-class activities in ADF pipelines and combining/chaining them with other activities, allowing you to trigger your pipeline runs by events, automatically (de)provision SSIS IR just in time, etc.
Azure Databricks is Easier Than You ThinkIke Ellis
Spark is a fast and general engine for large-scale data processing. It supports Scala, Python, Java, SQL, R and more. Spark applications can access data from many sources and perform tasks like ETL, machine learning, and SQL queries. Azure Databricks provides a managed Spark service on Azure that makes it easier to set up clusters and share notebooks across teams for data analysis. Databricks also integrates with many Azure services for storage and data integration.
This presentation is for those of you who are interested in moving your on-prem SQL Server databases and servers to Azure virtual machines (VM’s) in the cloud so you can take advantage of all the benefits of being in the cloud. This is commonly referred to as a “lift and shift” as part of an Infrastructure-as-a-service (IaaS) solution. I will discuss the various Azure VM sizes and options, migration strategies, storage options, high availability (HA) and disaster recovery (DR) solutions, and best practices.
Presentation on Large Scale Data ManagementChris Bunch
The document summarizes recent research on MapReduce and virtual machine migration. It discusses papers that compare MapReduce to parallel databases, describe techniques for live migration of virtual machines with low downtime, and propose using system call logging and replay to further reduce migration times and overhead. The document provides context on debates around MapReduce and outlines key approaches and findings from several papers on virtual machine migration.
Azure SQL Database is a relational database-as-a-service hosted in the Azure cloud that reduces costs by eliminating the need to manage virtual machines, operating systems, or database software. It provides automatic backups, high availability through geo-replication, and the ability to scale performance by changing service tiers. Azure Cosmos DB is a globally distributed, multi-model database that supports automatic indexing, multiple data models via different APIs, and configurable consistency levels with strong performance guarantees. Azure Redis Cache uses the open-source Redis data structure store with managed caching instances in Azure for improved application performance.
This document provides an overview and summary of the author's background and expertise. It states that the author has over 30 years of experience in IT working on many BI and data warehouse projects. It also lists that the author has experience as a developer, DBA, architect, and consultant. It provides certifications held and publications authored as well as noting previous recognition as an SQL Server MVP.
Migrating on premises workload to azure sql databasePARIKSHIT SAVJANI
This document provides an overview of migrating databases from on-premises SQL Server to Azure SQL Database Managed Instance. It discusses why companies are moving to the cloud, challenges with migration, and the tools and services available to help with assessment and migration including Data Migration Service. Key steps in the migration workflow include assessing the database and application, addressing compatibility issues, and deploying the converted schema to Managed Instance which provides high compatibility with on-premises SQL Server in a fully managed platform as a service model.
ITCamp 2019 - Andy Cross - Machine Learning with ML.NET and Azure Data LakeITCamp
ML.NET is an open source, machine learning framework built in .NET and runs on Windows, Linux and macOS. It allows developers to integrate custom machine learning into their applications without any prior expertise in developing or tuning machine learning models. Enhance your .NET apps with sentiment analysis, price prediction, fraud detection and more using custom models built with ML.NET
In this Session, Andy will show not only the core of ML.NET but best practices around Azure Data Lake and data in general when using .NET
Technical session on Databases as Service in Azure
Technical session - Azure SQL DB on Dec 20, 2020
https://youtu.be/Cl4IDpc_0yc
Technical session - 2 on Azure SQL DB - Dec 27, 2020
https://youtu.be/_4lZ54eI3F0
Technical session on Azure Cosmos DB -Dec 27, 2020
https://youtu.be/rtDwX1K_64k
Move a successful onpremise oltp application to the cloudIke Ellis
This document discusses preparing to move a legacy on-premises SQL Server application to Azure. It recommends:
1. Decoupling the database from the server name and database names to allow future changes.
2. Making the database smaller by deleting old data, unused indexes, and moving BLOBs to Azure storage.
3. Defragging and shrinking the database, implementing compression, and moving the backup process to Azure.
4. Migrating SQL Server to an Azure VM as the first step, choosing appropriate VM sizes and premium SSD disks for performance. Further steps will break the database into microservices and move components to Azure PaaS offerings.
With the recent release of SQL Server 2016 SP1 providing a consistent programming surface area has generated quite a buzz in the SQL Server community. SQL Server 2016 SP1 allows businesses of all sizes to leverage full feature set such as In-Memory technologies on all editions of SQL Server to get enterprise grade performance. This presentation focuses on the new improvements, new limits on the lower editions, differentiating factors and key scenarios enabled by SQL Server 2016 SP1 which makes SQL Server 2016 SP1 an obvious choice for the customers. This session was delivered to PASS VC DBA fundamentals chapter for everyone to learn about these exciting new improvements announced with SQL Server 2016 SP1 to ensure they are leveraging them to maximize performance and throughput of your SQL Server environment.
This document summarizes key components of Microsoft Azure's data platform, including SQL Database, NoSQL options like Azure Tables, Blob Storage, and Azure Files. It provides an overview of each service, how they work, common use cases, and demos of creating resources and accessing data. The document is aimed at helping readers understand Azure's database and data storage options for building cloud applications.
This document provides an overview of Azure SQL DB environments. It discusses the different types of cloud platforms including IaaS, PaaS and DBaaS. It summarizes the key features and benefits of Azure SQL DB including automatic backups, geo-replication for disaster recovery, and elastic pools for reducing costs. The document also covers pricing models, performance monitoring, automatic tuning capabilities, and security features of Azure SQL DB.
This document discusses using virtualization and containers to improve database deployments in development environments. It notes that traditional database deployments are slow, taking 85% of project time for creation and refreshes. Virtualization allows for more frequent releases by speeding up refresh times. The document discusses how virtualization engines can track database changes and provision new virtual databases in seconds from a source database. This allows developers and testers to self-service provision databases without involving DBAs. It also discusses how virtualization and containers can optimize database deployments in cloud environments by reducing storage usage and data transfers.
The document summarizes new features in SQL Server 2016 SP1, organized into three categories: performance enhancements, security improvements, and hybrid data capabilities. It highlights key features such as in-memory technologies for faster queries, always encrypted for data security, and PolyBase for querying relational and non-relational data. New editions like Express and Standard provide more built-in capabilities. The document also reviews SQL Server 2016 SP1 features by edition, showing advanced features are now more accessible across more editions.
Geek Sync | Planning a SQL Server to Azure Migration in 2021 - Brent OzarIDERA Software
The document discusses planning a SQL Server migration to Azure. It outlines four key steps: 1) Choosing an Azure target service; 2) Working around unavailable services; 3) Provisioning appropriate hardware resources; and 4) Tuning performance once in Azure. Common challenges include agent jobs, cross-database transactions, and adjusting to Azure's standardized hardware configurations and throughput limits. The document recommends starting with a "lift and shift" migration to VMs for initial simplicity.
This document provides an overview of Azure Databricks, including:
- Azure Databricks is an Apache Spark-based analytics platform optimized for Microsoft Azure cloud services. It includes Spark SQL, streaming, machine learning libraries, and integrates fully with Azure services.
- Clusters in Azure Databricks provide a unified platform for various analytics use cases. The workspace stores notebooks, libraries, dashboards, and folders. Notebooks provide a code environment with visualizations. Jobs and alerts can run and notify on notebooks.
- The Databricks File System (DBFS) stores files in Azure Blob storage in a distributed file system accessible from notebooks. Business intelligence tools can connect to Databricks clusters via JDBC
HA/DR options with SQL Server in Azure and hybridJames Serra
What are all the high availability (HA) and disaster recovery (DR) options for SQL Server in a Azure VM (IaaS)? Which of these options can be used in a hybrid combination (Azure VM and on-prem)? I will cover features such as AlwaysOn AG, Failover cluster, Azure SQL Data Sync, Log Shipping, SQL Server data files in Azure, Mirroring, Azure Site Recovery, and Azure Backup.
Azure SQL Database (SQL DB) is a database-as-a-service (DBaaS) that provides nearly full T-SQL compatibility so you can gain tons of benefits for new databases or by moving your existing databases to the cloud. Those benefits include provisioning in minutes, built-in high availability and disaster recovery, predictable performance levels, instant scaling, and reduced overhead. And gone will be the days of getting a call at 3am because of a hardware failure. If you want to make your life easier, this is the presentation for you.
Azure SQL Database Managed Instance is a new flavor of Azure SQL Database that is a game changer. It offers near-complete SQL Server compatibility and network isolation to easily lift and shift databases to Azure (you can literally backup an on-premise database and restore it into a Azure SQL Database Managed Instance). Think of it as an enhancement to Azure SQL Database that is built on the same PaaS infrastructure and maintains all it's features (i.e. active geo-replication, high availability, automatic backups, database advisor, threat detection, intelligent insights, vulnerability assessment, etc) but adds support for databases up to 35TB, VNET, SQL Agent, cross-database querying, replication, etc. So, you can migrate your databases from on-prem to Azure with very little migration effort which is a big improvement from the current Singleton or Elastic Pool flavors which can require substantial changes.
Microsoft SQL server 2017 Level 300 technical deckGeorge Walters
This deck covers new features in SQL Server 2017, as well as carryover features from 2012 onwards. This includes high availability, columnstore, alwayson, In-memory tables, and other enterprise features.
In this presentation, we will do assess the on-premises environment and determining what workloads and databases are ready to make the move and what can you do to improve their Azure readiness while reducing downtime during the migration. Planning and assessment plays a critical role in moving to the cloud. We would see wide range of resources and tools to get an assessment completed with ease while identifying workload dependencies with practical tips and tricks focusing on sizing and costs. And finally, we’ll assess the SQL instances and identify their readiness for Azure as well.
These slides are a copy of a last Azure Cosmos DB + Gremlin API in Action session which I had the pleasure to present on June 2nd, 2018 at PASS SQL Saturday event in Montreal. The original PowerPoint version contained much more elaborate series of animations. We understand that those had to be flatten for upload in this case. Though I guess you'll get the idea of the logic involved.
The document provides an overview of a blockchain conference agenda with the following key points:
- The schedule includes sessions on Bitcoin blockchain, use cases, smart contracts, blockchain fundamentals, and blockchain and databases.
- It defines participants, transactions, and contracts on blockchains. Participants are members with identities and roles. Transactions are asset transfers between participants. Contracts set conditions for transactions.
- It explains some core concepts of blockchains including that they are distributed secure logfiles, how they provide transparency and robustness without central control, and how mining and proof-of-work consensus keeps the network secure.
- It discusses the differences between permissioned and unpermissioned ledgers, and considerations for whether
The fast-emerging distributed-ledger technology known as blockchain holds great promise. Blockchain provides controlled, secure access to sensitive data enabling traditionally independent organizations to work together to streamline and integrate processes. Business leaders are still trying to figure out how to put the technology to work. Yet most agree: Blockchain can unlock the vast value trapped in their business operations.
Blockchain is a decentralized digital ledger that records transactions across many nodes in a network. Changes to transactions require consensus from other nodes. Blockchain technology is still developing and the costs and best applications are unknown. Blocks contain transaction data structured using techniques like hashing, Merkle trees, and asymmetric encryption to securely record transactions in the distributed ledger. The key components that enable blockchain are decentralized nodes, distributed ledger, transactions, blocks, hashing, public/private keys, and a consensus mechanism like proof-of-work mining.
Migrating on premises workload to azure sql databasePARIKSHIT SAVJANI
This document provides an overview of migrating databases from on-premises SQL Server to Azure SQL Database Managed Instance. It discusses why companies are moving to the cloud, challenges with migration, and the tools and services available to help with assessment and migration including Data Migration Service. Key steps in the migration workflow include assessing the database and application, addressing compatibility issues, and deploying the converted schema to Managed Instance which provides high compatibility with on-premises SQL Server in a fully managed platform as a service model.
ITCamp 2019 - Andy Cross - Machine Learning with ML.NET and Azure Data LakeITCamp
ML.NET is an open source, machine learning framework built in .NET and runs on Windows, Linux and macOS. It allows developers to integrate custom machine learning into their applications without any prior expertise in developing or tuning machine learning models. Enhance your .NET apps with sentiment analysis, price prediction, fraud detection and more using custom models built with ML.NET
In this Session, Andy will show not only the core of ML.NET but best practices around Azure Data Lake and data in general when using .NET
Technical session on Databases as Service in Azure
Technical session - Azure SQL DB on Dec 20, 2020
https://youtu.be/Cl4IDpc_0yc
Technical session - 2 on Azure SQL DB - Dec 27, 2020
https://youtu.be/_4lZ54eI3F0
Technical session on Azure Cosmos DB -Dec 27, 2020
https://youtu.be/rtDwX1K_64k
Move a successful onpremise oltp application to the cloudIke Ellis
This document discusses preparing to move a legacy on-premises SQL Server application to Azure. It recommends:
1. Decoupling the database from the server name and database names to allow future changes.
2. Making the database smaller by deleting old data, unused indexes, and moving BLOBs to Azure storage.
3. Defragging and shrinking the database, implementing compression, and moving the backup process to Azure.
4. Migrating SQL Server to an Azure VM as the first step, choosing appropriate VM sizes and premium SSD disks for performance. Further steps will break the database into microservices and move components to Azure PaaS offerings.
With the recent release of SQL Server 2016 SP1 providing a consistent programming surface area has generated quite a buzz in the SQL Server community. SQL Server 2016 SP1 allows businesses of all sizes to leverage full feature set such as In-Memory technologies on all editions of SQL Server to get enterprise grade performance. This presentation focuses on the new improvements, new limits on the lower editions, differentiating factors and key scenarios enabled by SQL Server 2016 SP1 which makes SQL Server 2016 SP1 an obvious choice for the customers. This session was delivered to PASS VC DBA fundamentals chapter for everyone to learn about these exciting new improvements announced with SQL Server 2016 SP1 to ensure they are leveraging them to maximize performance and throughput of your SQL Server environment.
This document summarizes key components of Microsoft Azure's data platform, including SQL Database, NoSQL options like Azure Tables, Blob Storage, and Azure Files. It provides an overview of each service, how they work, common use cases, and demos of creating resources and accessing data. The document is aimed at helping readers understand Azure's database and data storage options for building cloud applications.
This document provides an overview of Azure SQL DB environments. It discusses the different types of cloud platforms including IaaS, PaaS and DBaaS. It summarizes the key features and benefits of Azure SQL DB including automatic backups, geo-replication for disaster recovery, and elastic pools for reducing costs. The document also covers pricing models, performance monitoring, automatic tuning capabilities, and security features of Azure SQL DB.
This document discusses using virtualization and containers to improve database deployments in development environments. It notes that traditional database deployments are slow, taking 85% of project time for creation and refreshes. Virtualization allows for more frequent releases by speeding up refresh times. The document discusses how virtualization engines can track database changes and provision new virtual databases in seconds from a source database. This allows developers and testers to self-service provision databases without involving DBAs. It also discusses how virtualization and containers can optimize database deployments in cloud environments by reducing storage usage and data transfers.
The document summarizes new features in SQL Server 2016 SP1, organized into three categories: performance enhancements, security improvements, and hybrid data capabilities. It highlights key features such as in-memory technologies for faster queries, always encrypted for data security, and PolyBase for querying relational and non-relational data. New editions like Express and Standard provide more built-in capabilities. The document also reviews SQL Server 2016 SP1 features by edition, showing advanced features are now more accessible across more editions.
Geek Sync | Planning a SQL Server to Azure Migration in 2021 - Brent OzarIDERA Software
The document discusses planning a SQL Server migration to Azure. It outlines four key steps: 1) Choosing an Azure target service; 2) Working around unavailable services; 3) Provisioning appropriate hardware resources; and 4) Tuning performance once in Azure. Common challenges include agent jobs, cross-database transactions, and adjusting to Azure's standardized hardware configurations and throughput limits. The document recommends starting with a "lift and shift" migration to VMs for initial simplicity.
This document provides an overview of Azure Databricks, including:
- Azure Databricks is an Apache Spark-based analytics platform optimized for Microsoft Azure cloud services. It includes Spark SQL, streaming, machine learning libraries, and integrates fully with Azure services.
- Clusters in Azure Databricks provide a unified platform for various analytics use cases. The workspace stores notebooks, libraries, dashboards, and folders. Notebooks provide a code environment with visualizations. Jobs and alerts can run and notify on notebooks.
- The Databricks File System (DBFS) stores files in Azure Blob storage in a distributed file system accessible from notebooks. Business intelligence tools can connect to Databricks clusters via JDBC
HA/DR options with SQL Server in Azure and hybridJames Serra
What are all the high availability (HA) and disaster recovery (DR) options for SQL Server in a Azure VM (IaaS)? Which of these options can be used in a hybrid combination (Azure VM and on-prem)? I will cover features such as AlwaysOn AG, Failover cluster, Azure SQL Data Sync, Log Shipping, SQL Server data files in Azure, Mirroring, Azure Site Recovery, and Azure Backup.
Azure SQL Database (SQL DB) is a database-as-a-service (DBaaS) that provides nearly full T-SQL compatibility so you can gain tons of benefits for new databases or by moving your existing databases to the cloud. Those benefits include provisioning in minutes, built-in high availability and disaster recovery, predictable performance levels, instant scaling, and reduced overhead. And gone will be the days of getting a call at 3am because of a hardware failure. If you want to make your life easier, this is the presentation for you.
Azure SQL Database Managed Instance is a new flavor of Azure SQL Database that is a game changer. It offers near-complete SQL Server compatibility and network isolation to easily lift and shift databases to Azure (you can literally backup an on-premise database and restore it into a Azure SQL Database Managed Instance). Think of it as an enhancement to Azure SQL Database that is built on the same PaaS infrastructure and maintains all it's features (i.e. active geo-replication, high availability, automatic backups, database advisor, threat detection, intelligent insights, vulnerability assessment, etc) but adds support for databases up to 35TB, VNET, SQL Agent, cross-database querying, replication, etc. So, you can migrate your databases from on-prem to Azure with very little migration effort which is a big improvement from the current Singleton or Elastic Pool flavors which can require substantial changes.
Microsoft SQL server 2017 Level 300 technical deckGeorge Walters
This deck covers new features in SQL Server 2017, as well as carryover features from 2012 onwards. This includes high availability, columnstore, alwayson, In-memory tables, and other enterprise features.
In this presentation, we will do assess the on-premises environment and determining what workloads and databases are ready to make the move and what can you do to improve their Azure readiness while reducing downtime during the migration. Planning and assessment plays a critical role in moving to the cloud. We would see wide range of resources and tools to get an assessment completed with ease while identifying workload dependencies with practical tips and tricks focusing on sizing and costs. And finally, we’ll assess the SQL instances and identify their readiness for Azure as well.
These slides are a copy of a last Azure Cosmos DB + Gremlin API in Action session which I had the pleasure to present on June 2nd, 2018 at PASS SQL Saturday event in Montreal. The original PowerPoint version contained much more elaborate series of animations. We understand that those had to be flatten for upload in this case. Though I guess you'll get the idea of the logic involved.
The document provides an overview of a blockchain conference agenda with the following key points:
- The schedule includes sessions on Bitcoin blockchain, use cases, smart contracts, blockchain fundamentals, and blockchain and databases.
- It defines participants, transactions, and contracts on blockchains. Participants are members with identities and roles. Transactions are asset transfers between participants. Contracts set conditions for transactions.
- It explains some core concepts of blockchains including that they are distributed secure logfiles, how they provide transparency and robustness without central control, and how mining and proof-of-work consensus keeps the network secure.
- It discusses the differences between permissioned and unpermissioned ledgers, and considerations for whether
The fast-emerging distributed-ledger technology known as blockchain holds great promise. Blockchain provides controlled, secure access to sensitive data enabling traditionally independent organizations to work together to streamline and integrate processes. Business leaders are still trying to figure out how to put the technology to work. Yet most agree: Blockchain can unlock the vast value trapped in their business operations.
Blockchain is a decentralized digital ledger that records transactions across many nodes in a network. Changes to transactions require consensus from other nodes. Blockchain technology is still developing and the costs and best applications are unknown. Blocks contain transaction data structured using techniques like hashing, Merkle trees, and asymmetric encryption to securely record transactions in the distributed ledger. The key components that enable blockchain are decentralized nodes, distributed ledger, transactions, blocks, hashing, public/private keys, and a consensus mechanism like proof-of-work mining.
How Blockchain Technology Is Evolving In The CloudShikhaKonda
https://go-dgtl.com/whitepaper/how-blockchain-technology-is-evolving-in-the-cloud/?utm_source=offpage&utm_medium=thirdparty&utm_campaign=alo-seo - Cloud and blockchain are increasingly becoming the most valuable combinations to enhance the security of enterprise data living on the cloud. Learn more
How Blockchain Technology Is Evolving In The Cloud - GoDgtl.pdfPeeterParkar
Blockchain technology is evolving to provide security benefits when used with cloud computing. Major cloud platforms like Amazon, Google, and Microsoft now offer blockchain-as-a-service (BaaS) to securely store data in the cloud using blockchain's decentralized, immutable ledger. Blockchain addresses cloud computing's security risks like data loss and lack of transparency. Its use in the cloud is expected to grow significantly, expanding to applications in digital identity, payments, supply chain management, and more.
Is Azure Blockchain Cloud the Future of Cloud Computing | SysforeSysfore Technologies
Azure Blockchain as a Service (BaaS) is the new and experimental cloud technology service which Microsoft Azure is offering for its Platform as a Service (PaaS) customers. It is trying to create a marketplace for the blockchain, the distributed ledger technology on which bitcoin is built. IBM is the other adopter of this new cloud service, through its Bluemix Cloud service.
Sysfore can give you all the facts about Bitcoin cloud technology. Before going into how Bitcoin cloud works, you need to understand what the Bitcoin technology is.
This document provides an overview of blockchain technology from the perspectives of technology, business, and user experience. It explores key questions about distributed vs centralized ledgers, how blockchains work, how they are maintained, and how blockchain may impact businesses. The document discusses how blockchain hashes transactions into an immutable chain, preventing tampering. It provides examples of how blockchain could track the lifecycle of assets like cars and music to build trust and transparency across industries.
zenoh: zero overhead pub/sub store/query computeAngelo Corsaro
Unifies data in motion, data in-use, data at rest and computations.
It carefully blends traditional pub/sub with distributed queries, while retaining a level of time and space efficiency that is well beyond any of the mainstream stacks.
It provides built-in support for geo-distributed storages and distributed computations
An independent research project conducted by the talented Harvard grad student Andrew Serpa, under the guidance of Josh Gould and Andrew Reid (Con Edison). Examines utility use-cases for blockchain.
How Integrated Process Management Completes the Blockchain JigsawCognizant
Blockchains, or distributed ledger technology, makes digital transactions safer for all parties, assuming that organizations apply traditional business orchestration and integrated process management to tightly connect legacy systems of record with emerging blockchain networks, promoting trust and true collaboration across their value chains.
What is Blockchain Technology? A Beginner’s Guide.pdfimoliviabennett
According to a recent study published by CoinDesk, blockchain technology development will continue to expand rapidly in the years to come. Those who are interested in blockchain technology would also have a greater desire to learn about it
This document provides an overview of blockchain technology and its potential applications. It discusses how blockchain can be used in accounting to improve transparency and auditability of financial records. It also explores how blockchain could benefit the finance industry by allowing faster and cheaper transactions without intermediaries. Real estate is another sector that may see benefits from blockchain, such as reduced costs, increased efficiency and transparency, and lower fraud risks. The document provides learning objectives related to understanding blockchain's history, disruptive nature, future potential, and advantages/disadvantages.
How Blockchain Development Can Revolutionize Your Digital Strategy.pdfPixel Softwares
Reinvent Digital Dynamics: Embrace the power of blockchain technology to reimagine your digital strategy. With decentralized solutions and smart contracts, Pixel Softwares can revolutionize your business landscape.
CHAPTER 12 Integrating Non-Blockchain Apps with Ethereum EstelaJeffery653
CHAPTER 12 Integrating Non-Blockchain Apps with Ethereum 205
Chapter 12
Integrating Non-
Blockchain Apps
with Ethereum
Although you can build entirely blockchain-based applications, it is far more likely that your applications will be a combination of traditional and blockchain components. You learn in Chapter 3 that some use cases lend
themselves well to blockchain apps but others do not. In this book, we chose to
highlight one use case, supply chain, because blockchain offers clear advantages
over traditional methods. However, even a comprehensive supply chain applica-
tion will likely run partially as a traditional application and partially on the
blockchain.
Many emerging blockchain apps consist of core components that operate as smart
contracts and other components that operate as traditional applications that
interact with users and provide supporting functionality. This hybrid approach to
application development requires the capability to integrate the two different
development models. In other words, to develop hybrid applications that run par-
tially on the blockchain, you need to know how to design them to talk with each
other and operate seamlessly.
IN THIS CHAPTER
» Exploring differences between
blockchain and databases
» Identifying differences between
blockchain and traditional
applications
» Integrating traditional applications
with Ethereum
» Testing and deploying integrated
blockchain apps
206 PART 4 Testing and Deploying Ethereum Apps
Distributed application design and development isn’t new. In fact, some of the
difficulties with distributed applications led to the need for technologies like
blockchain. Remember that blockchain technology doesn’t solve all application
problems, but it does have its place. Now that you know how to develop dApps for
the Ethereum blockchain, in this chapter you learn how to integrate your smart
contracts with applications that do not include blockchain technology. The capa-
bility to integrate blockchain and non-blockchain applications makes it possible
to develop applications that use the right technology for a wide range of needs.
Comparing Blockchain and
Database Storage
In Chapter 2, you learn about some of the differences between storing data in a
blockchain and a database. Both technologies can store data, but clear differences
exist between the two. One of the first obstacles you might encounter when asked
to integrate blockchain with an existing application is determining what data you
should migrate to the blockchain.
Traditional applications store most of their data in a database. Databases provide
fast access to shared data. Blockchains can also provide access to shared data, but
they may not be as fast as a database. As you learn in Chapter 2, there are other
differences as well. It is important that you understand the relative strengths of
each data storage technique to make good design decisions for integrating block-
ch ...
This document discusses how Postgres fits into a DevOps world. It notes that as companies become more software-focused, DevOps practices like continuous integration/delivery, microservices, and containers are on the rise. This means databases need to be developer-friendly, support versatile data models like JSON, integrate with other technologies, and allow for rapid deployment including on databases-as-a-service platforms. Postgres is well-suited to this new environment as an open-source, multi-platform database that can scale easily and works well with other data systems through foreign data wrappers. The role of the database administrator is also changing to focus more on strategic tasks like performance, security, and data management rather than system administration.
Build Blockchain Prototype using Azure Workbench and Manage data on ledgerMohammad Asif
In this session we show how to create blockchain prototype using Azure Blockchain Workbench and integrate with existing applications & Scale your blockchain apps with azure blockchain as service.
This document summarizes a presentation about blockchain on Azure. It discusses:
1. The four pillars of blockchain - secure, shared, distributed, and ledger.
2. Different types of blockchain networks including public, private, and consortium.
3. Why Microsoft is well-positioned for blockchain with its open ecosystem on Azure.
4. How blockchain is evolving from simple ledgers to incorporating smart contracts and external data access through cryptlets.
5. Examples of blockchain applications including supply chain management and social good projects.
SWIFT Embraces Crypto Chainlink Integration and How It Helps with Tokenized A...Codezeros
The world's leading financial messaging network, SWIFT, has partnered with Chainlink, a leading blockchain oracle network, to revolutionize the way tokenized real world assets (RWAs) are traded and managed. Tokenized RWAs are digital representations of physical assets, such as real estate, commodities, and securities. They can be traded on blockchain-based platforms, and they offer a number of advantages over traditional assets, such as increased liquidity and transparency. The integration of SWIFT and Chainlink will enable the secure and reliable transfer of data between the real world and the blockchain. This will make it possible to trade tokenized RWAs on a global scale, and it will also help to improve the efficiency and transparency of the RWA market. The implications of the SWIFT-Chainlink partnership are far-reaching. It could lead to the wider adoption of blockchain technology by the financial industry, and it could also help to make the global financial system more efficient and secure. Read more about the SWIFT-Chainlink partnership and how it could revolutionize the trading and management of tokenized RWAs.
Read More: https://www.codezeros.com/swift-embraces-crypto-chainlink-integration-and-how-it-helps-with-tokenized-assets-rwa
LESSON 2 BLOCKCHAIN DECENTRALIZATION _ DATAFICATION IN BLOCKCHAIN TECHNOLOGY ...Leapwaters
Blockchain is a system of recording information in a way that makes it difficult or impossible to change, hack, or cheat the system. A blockchain is essentially a digital ledger of transactions that is duplicated and distributed across the entire network of computer systems on the blockchain.
Data Modelling for security and privacy PRAGUE.pptxKaren Lopez
Fast presentation on data design for security and privacy within databases.
Data Masking
Subsetting
Row Level Security
Always Encrypted
Monitoring and Alerting
Slide deck for the DGIQ SIG on AI Ethics.
Are you concerned about data and AI ethics? Do you worry about how to make sure the algorithms and systems that affect our lives are fair, honest, responsible, and respectful of our rights and values? Do you have opinions about how to build an organizational culture that cares about these topics
Join us for what will surely be a lively and interesting session where you are the speakers.
Special interest group (SIG) discussions are group conversations on topics that are new, or specific to an audience segment. The format is casual and without any formal presentation. The objective is to engage all participants in an exchange of ideas, questions, and advice, so please come with a willingness to participate in the conversation.
A Designer's Favourite Security and Privacy Features in SQL Server and Azure ...Karen Lopez
SQL Server includes multiple features that focus on data security, privacy, and developer productivity. In this session, we will review the best features from a database designer’s and developer’s point of view.
– Always Encrypted
– Dynamic Data Masking
– Row Level Security
– Data Classification
– Assessments
– Defender for SQL Server
– Ledger Tables
…and more
We’ll look at new and older features, why you should consider them, where they work, where they don’t, who needs to be involved in using them, and what changes, if any, need to be made to applications or tools that you use with SQL Server.
You will learn:
– The pros and cons of implementing each feature
– How implementing these new features may impact existing applications
– 10 tips for enhancing SQL Server security and privacy protections
Designer's Favorite New Features in SQLServerKaren Lopez
A database designer's favourte features in SQL Server...with a bit of Azure SQL DB, too.
Always Encrypted
Row Level Security
Microsoft Purview
Azure Enabled SQL Server
Azure Defender for SQL
Azure Defender for Cloud
Dynamic Data Masking
Ledger Database and Tables
Data Privacy
Data Governance
The document discusses challenges with managing data and keeping data clean. It notes that ensuring clean, consistent data is provided to customers is important. It also notes that despite best efforts, some invalid or unexpected data will inevitably exist in systems, similar to how some contamination exists in water systems, and outlines some strategies for addressing data quality issues.
Expert Cloud Data Backup and Recovery Best Practice.pptxKaren Lopez
We’ve been deploying backup solutions since the beginning of computing and the foundations of backup and recovery have stayed the same: make sure backups run consistently and set recovery objectives. Yet systems in 2022 don’t work or act the same way they did decades ago. Cloud data backups have helped us meet the need for offsite backups, as well as impacted how we budget for them. Ransomware has impacted how we store them. The laws of physics might be more of an issue than when we had tapes stored in a safe down the hall. Cost models have changed, too.
In this session, Karen Lopez covers best practices for modern data recovery…and she will share stories of worst practices just to keep it real.
Manage Your Time So It Doesn't Manage YouKaren Lopez
NASA Space Apps NYC Pre-Hackathon Symposium presentation by Karen Lopez, InfoAdvisors and NASA Datanaut. Karen presents on how to successfully manage your time and deliverables in the NASA Space Apps Challenge no matter where you are participating.
Data Security and Protection in DevOps Karen Lopez
The document discusses securing and protecting data in DevOps environments. It covers topics such as data discovery, classification, curation, cataloging data assets, assessing risks, auditing, dynamic data masking, row-level security, always encrypted columns, and building a culture of data security. The presentation encourages cataloging all data, classifying its sensitivity, designing test data separately from production data, and continually monitoring and testing security practices.
Data Modeling for Security, Privacy and Data ProtectionKaren Lopez
Karen Lopez (@datchick/InfoAdvisors) 90-minute presentation on Data Security, Data Privacy, Compliance and how data modelers should discover, assess, and monitor these important data management responsibilities.
Designing for Data Security by Karen LopezKaren Lopez
As security and complaince becomes more important for organizations, especially in the age of GDPR, data breach and other legislation, Karen covers the types of features data architects and designers should be considering when building modern, protected and defensive systems.
There are many data modeling and database design terms and jargon that uses the word "key." Do you know the difference between a surrogate key and a primary key? A super key and a candidate key? Could you explain them to a technical audience? A business user or an auditor?
In this presentation, Karen Lopez covers the concepts of primary keys, foreign keys, candidate key, surrogate keys, and more.
How to Survive as a Data Architect in a Polyglot Database WorldKaren Lopez
Karen Lopez talks to data architects and data moders how they can best deliver value on modern data drive projects beyond relational database technologies. She covers NoSQL Databases and Datastores, which data stories they best fit and which ones they don't. She ends with 10 tips for adding more value to ployschematic database solutions.
Karen's Favourite Features of SQL Server 2016Karen Lopez
Slides from a one hour webinar on Karen Lopez's favorite features from database designer's point of view. Topics include Always Encrypted, Data Masking, Row Level Security, Foreign Keys, JSON and more.
Notice an error? Let me know. I welcome this sort of feedback.
This document provides an overview of NoSQL databases in Azure. It discusses 7 different database types - key-value, column family, document, graph and Hadoop. For each database type it provides information on what it is, examples of use cases, and how to query or model data. It encourages attendees to explore these databases and stresses that choosing the right database for the job is important.
Karen Lopez 10 Physical Data Modeling BlundersKaren Lopez
Karen Lopez's presentation about 10 Physical Data Modeling/Database Design blunders, based on her work in helping organizations get the most value out of their models and data.
Notice an error? Let me know. I welcome this sort of feedback.
NoSQL and Data Modeling for Data ModelersKaren Lopez
Karen Lopez's presentation for data modelers and data architects. Why data modeling is still relevant for big data and NoSQL projects.
Plus 10 tips for data modelers for working on NoSQL projects.
This comprehensive Data Science course is designed to equip learners with the essential skills and knowledge required to analyze, interpret, and visualize complex data. Covering both theoretical concepts and practical applications, the course introduces tools and techniques used in the data science field, such as Python programming, data wrangling, statistical analysis, machine learning, and data visualization.
Telangana State, India’s newest state that was carved from the erstwhile state of Andhra
Pradesh in 2014 has launched the Water Grid Scheme named as ‘Mission Bhagiratha (MB)’
to seek a permanent and sustainable solution to the drinking water problem in the state. MB is
designed to provide potable drinking water to every household in their premises through
piped water supply (PWS) by 2018. The vision of the project is to ensure safe and sustainable
piped drinking water supply from surface water sources
Thingyan is now a global treasure! See how people around the world are search...Pixellion
We explored how the world searches for 'Thingyan' and 'သင်္ကြန်' and this year, it’s extra special. Thingyan is now officially recognized as a World Intangible Cultural Heritage by UNESCO! Dive into the trends and celebrate with us!
2. Karen Lopez
• Karen has 20+ years of
data and information
architecture experience
on large, multi-project
programs.
• She is a frequent speaker
on data modeling, data-
driven methodologies and
pattern data models.
• She wants you to love
your data.
3. ABSTRACT
With all the hype around blockchain, why should a data architect or
other data professional care? In this session, we will cover the basics
of blockchain as it applies to data and database processes:
Immutability
Verification
Distribution
Cryptography
Transactions
Trust
We will look at current offerings for blockchain features in Azure
and in database and data stores. Finally, we'll help you identify the
types of business requirements that need blockchain technologies.
You will learn:
Understand the valid uses of blockchain approaches in
databases
How current technologies support blockchain approaches
Understand the costs, benefits, and risks of blockchain
Blockchain for the DBA and
Data professional: Basics of
Blockchain
4. WHY THIS TOPIC?
I was asked to give a primer on
Blockchain
Buzz
More focus on data uses
Better understanding of uses
I own a blockchain skirt
5. WHY DBAS AND DATA PROFESSIONALS
Concepts
Business implementations
Database technologies
10. TRANSACTIONS
“It’s basically the
same thing as a
database
transaction”
Not changeable
Must be offset with another transaction
Consensus is reached when 51% of the nodes agree
transaction is valid
Recorded in all nodes
11. NODES
Distributed Ledgers
Transactions are recorded in all
nodes. Instead of one ledger, there
are many ledgers to maintain trust
Nodes are:
Distributed, multiply-owned nodes
Based on P2P architectures
No central owner or manager:
Consensus-based
12. BLOCK
One transaction of data
Data about transaction
#1 {data} #2 {data} #1 #3 {data} #2
Hash of data Hash from previous block
13. ADD BLOCK PROCESS
Here’s a
Transaction1
Send
Transaction
to all nodes2 Validate
Transaction3 Add to
blockchain4
…
Nodes
14. TRUST
To manipulate the data,
one would need to
change all (or 51%) the
copies of the data, which
are managed by different
people.
…and do so at exactly the
same time
15. HISTORY – THE CHAIN
Everyone sees
Where the asset was previously
in the chain
When some transaction about
the asset was done
Every previous state of an asset
in the chain
16. TRUST EVERYONE, BUT ALWAYS CUT THE DECK
Blockchain does not
validate the truthfulness of
the transaction that is put
into the chain
17. TRIGGERS
An action that happens after a
transaction
Delivery
Penalty
Payment
…anything
18. LEDGERS
Traditional
Each org has own ledger
Managed by one entity
Audited
Requires constant reconciliation
Sometimes not secure
May be encrypted
Blockchain
Multiple copies
Managed by multiple entities
Transparent
Trustable
Encrypted
20. NATIVE BLOCKCHAIN TABLES
Oracle Blockchain Tables
Focuses on Tamper Resistance
Insert only
Not distributed
Not visible to others
Still centralized management
Features
PKI signatures: impersonation resistance
Encryption
Trust but Verify: copies hashes and data
to an external data store
Performance: no consensus required, no
extra infrastructure
CREATE Blockchain Table Trade_Ledger;
21. ORACLE BLOCKCHAIN TABLE
Transaction of data in a Blockchain Table as a row
Data about transaction in Blockchain Table as
columns
#1 {data} #0 #2 {data} #1 #3 {data} #2
Hash of data Hash from previous block
Audit Log of hashes and PKI Signatures
23. ORACLE BLOCKCHAIN TABLE
NO DROP
NO DROP UNTIL n DAYS IDLE
NO DELETE
NO DELETE UNTIL n DAYS AFTER INSERT [LOCKED]
DBMS_BLOCKCHAIN_TABLE.VERIFY_ROWS
24. ORACLE BLOCKCHAIN TABLE CREATE
CREATE BLOCKCHAIN TABLE bctab_part
(trans_id number primary key, sender varchar2(50), recipient varchar2(50),
trans_date DATE, amount number)
NO DROP UNTIL 16 DAYS IDLE
NO DELETE UNTIL 25 DAYS AFTER INSERT
HASHING USING "SHA2_512" VERSION "v1"
PARTITION BY RANGE(trans_date)
(PARTITION p1 VALUES LESS THAN (TO_DATE('30-09-2019','dd-mm-yyyy')),
PARTITION p2 VALUES LESS THAN (TO_DATE('31-12-2019','dd-mm-yyyy')),
PARTITION p3 VALUES LESS THAN (TO_DATE('31-03-2020','dd-mm-yyyy')),
PARTITION p4 VALUES LESS THAN (TO_DATE('30-06-2020','dd-mm-yyyy'))
);
25. RESTRICTIONS ORACLE BLOCKCHAIN TABLE
Updating and merging rows
Adding, dropping, and renaming columns
Truncating the blockchain table
Dropping partitions
Defining BEFORE ROW triggers that fire for update operations (other triggers are allowed)
Direct-path loading
Inserting data using parallel DML
Converting a regular table to a blockchain table or vice versa
XA transactions
https://docs.oracle.com/en/database/oracle/oracle-database/20/admin/managing-tables.html
26. WHY WOULD ONE
USE A BLOCKCHAIN
TABLE?
More trustworthy
More protection from
DBA/SysAdmin tampering
Don’t need or want full blockchain
functionality
30. BLOCKCHAIN & COIN FLUFF
“Blockchain is free, so it will put every business that
charges a small fee out of business”
Credit card merchants
Banks
Music labels
Amazon
Travel agencies
Travel providers
Stock exchanges
….
32. BLOCKCHAIN IN REAL LIFE
Supply Chain
Inventory
Transportation
Healthcare
Utilities
Financial
33. BLOCKCHAIN IN
REAL LIFE
Large Global Retailer’s
Canadian operations
Track deliveries
Verify transactions
Automate payments
500,000 loads of inventory
853 million cases of merchandise
Significant cost savings
Faster payments
34. 2019 STATS
From IDC
Total spending 2.9 billion on
blockchain
That’s an increase of 89% from
2018
Predicted to reach 12.4 billion by
2022
35. OTHER INTERESTING
STATS
Bitcoin miners are paid to provide
consensus on transactions
In 2017, miners used more energy that
all of New Zealand
In 2010 an early Bitcoin user bought
two pizzas for 10,000 Bitcoin
These are about Bitcoin, but
they are interesting factiods
36. WHAT DOES THIS MEAN
TO A DATA
MODELER/ARCHITECT?
Support for RDBMS new features are required in our
data modeling tools
Understanding when to use Blockchain and when to
use traditional logging/accounting tables mandatory
Understanding the difference between
Ledger/Blockchain tables and traditional Blockchain
services required