The document discusses Oracle Optimized Solutions, which are predefined solutions that integrate Oracle's servers, storage, networking and software components. This provides benefits such as lower costs, reduced risk, and improved business agility compared to custom configured systems. Specific optimized solutions are described for applications like Siebel CRM, PeopleSoft HCM and E-Business Suite that deliver high performance, availability and reduced costs.
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.
QuerySurge - the automated Data Testing solutionRTTS
The document discusses QuerySurge, an automated data testing solution that helps verify data quality and find errors. It notes that traditional data quality tools focus on profiling, cleansing and monitoring data, while QuerySurge also enables data testing through easy-to-use query wizards and comparison of source and target data without SQL coding. QuerySurge allows collaborative testing across teams and platforms, integrates with development tools, and can significantly reduce testing time and improve data quality.
The document describes managing the Oracle Automatic Storage Management (ASM) instance. It discusses initializing and starting the ASM instance, creating and dropping ASM disk groups, adding and removing disks from disk groups, and retrieving ASM metadata. The key benefits of ASM include eliminating tasks such as file system management and performance tuning of storage.
This document provides guidance on using Oracle's Exadata Cloud Service (ExaCS) or Exadata Cloud at Customer (ExaCC) to set up disaster recovery for an on-premises database using Oracle Data Guard or Active Data Guard. It outlines the key benefits of a hybrid cloud/on-premises configuration and provides a 10-step process for implementing this along with considerations for security, networking, and ongoing management after deployment. The document is intended to help technical audiences set up a cloud-based standby database for disaster recovery that follows Oracle Maximum Availability Architecture best practices.
Active Directory is a centralized hierarchical directory database that contains information about all user accounts and shared network resources. It provides user logon authentication services and organizes and manages user accounts, computers, groups and network resources. Active Directory enables authorized users to easily locate network resources. It features include fully integrated security, easy administration using group policy, scalability to large networks, and flexibility through features like cross-forest trusts and site-to-site replication.
Azure Data Factory (ADF) is a cloud-based data integration service that allows users to easily construct ETL and ELT processes through a code-free visual interface or custom code. ADF can connect to both cloud and on-premises data sources, support data transformation, and also run existing SSIS packages that have been migrated to the cloud. Key components of ADF include storage accounts, containers, linked services, datasets, data pipelines, triggers, and data flows which allow users to move, transform and process data.
Delta Lake, an open-source innovations which brings new capabilities for transactions, version control and indexing your data lakes. We uncover how Delta Lake benefits and why it matters to you. Through this session, we showcase some of its benefits and how they can improve your modern data engineering pipelines. Delta lake provides snapshot isolation which helps concurrent read/write operations and enables efficient insert, update, deletes, and rollback capabilities. It allows background file optimization through compaction and z-order partitioning achieving better performance improvements. In this presentation, we will learn the Delta Lake benefits and how it solves common data lake challenges, and most importantly new Delta Time Travel capability.
This document provides an overview and introduction to Splunk, including:
1. It discusses the challenges of machine data including volume, velocity, variety and variability.
2. Splunk's mission is to make machine data accessible, usable and valuable to everyone.
3. It demonstrates how Splunk can unlock critical insights from machine data sources like order processing, social media, customer service systems and more.
Oracle RAC 19c: Best Practices and Secret InternalsAnil Nair
Oracle Real Application Clusters 19c provides best practices and new features for upgrading to Oracle 19c. It discusses upgrading Oracle RAC to Linux 7 with minimal downtime using node draining and relocation techniques. Oracle 19c allows for upgrading the Grid Infrastructure management repository and patching faster using a new Oracle home. The presentation also covers new resource modeling for PDBs in Oracle 19c and improved Clusterware diagnostics.
Big data architectures and the data lakeJames Serra
The document provides an overview of big data architectures and the data lake concept. It discusses why organizations are adopting data lakes to handle increasing data volumes and varieties. The key aspects covered include:
- Defining top-down and bottom-up approaches to data management
- Explaining what a data lake is and how Hadoop can function as the data lake
- Describing how a modern data warehouse combines features of a traditional data warehouse and data lake
- Discussing how federated querying allows data to be accessed across multiple sources
- Highlighting benefits of implementing big data solutions in the cloud
- Comparing shared-nothing, massively parallel processing (MPP) architectures to symmetric multi-processing (
This presentation is based on Lawrence To's Maximum Availability Architecture (MAA) Oracle Open World Presentation talking about the latest updates on high availability (HA) best practices across multiple architectures, features and products in Oracle Database 19c. It considers all workloads, OLTP, DWH and analytics, mixed workload as well as on-premises and cloud-based deployments.
Performance Optimizations in Apache ImpalaCloudera, Inc.
Apache Impala is a modern, open-source MPP SQL engine architected from the ground up for the Hadoop data processing environment. Impala provides low latency and high concurrency for BI/analytic read-mostly queries on Hadoop, not delivered by batch frameworks such as Hive or SPARK. Impala is written from the ground up in C++ and Java. It maintains Hadoop’s flexibility by utilizing standard components (HDFS, HBase, Metastore, Sentry) and is able to read the majority of the widely-used file formats (e.g. Parquet, Avro, RCFile).
To reduce latency, such as that incurred from utilizing MapReduce or by reading data remotely, Impala implements a distributed architecture based on daemon processes that are responsible for all aspects of query execution and that run on the same machines as the rest of the Hadoop infrastructure. Impala employs runtime code generation using LLVM in order to improve execution times and uses static and dynamic partition pruning to significantly reduce the amount of data accessed. The result is performance that is on par or exceeds that of commercial MPP analytic DBMSs, depending on the particular workload. Although initially designed for running on-premises against HDFS-stored data, Impala can also run on public clouds and access data stored in various storage engines such as object stores (e.g. AWS S3), Apache Kudu and HBase. In this talk, we present Impala's architecture in detail and discuss the integration with different storage engines and the cloud.
ClickHouse Materialized Views: The Magic ContinuesAltinity Ltd
Slides for the webinar, presented on February 26, 2020
By Robert Hodges, Altinity CEO
Materialized views are the killer feature of ClickHouse, and the Altinity 2019 webinar on how they work was very popular. Join this updated webinar to learn how to use materialized views to speed up queries hundreds of times. We'll cover basic design, last point queries, using TTLs to drop source data, counting unique values, and other useful tricks. Finally, we'll cover recent improvements that make materialized views more useful than ever.
This document provides an overview of Active Directory (AD) in Windows Server 2019. It describes what AD is, when and why it is used, and how to configure and manage it. Key components of AD are discussed such as domains, organizational units, group policy, backups. AD services like certificate services, domain services, and federation services are also summarized. The document provides best practices for using group policy and designing the AD structure.
Microsoft Fabric is the next version of Azure Data Factory, Azure Data Explorer, Azure Synapse Analytics, and Power BI. It brings all of these capabilities together into a single unified analytics platform that goes from the data lake to the business user in a SaaS-like environment. Therefore, the vision of Fabric is to be a one-stop shop for all the analytical needs for every enterprise and one platform for everyone from a citizen developer to a data engineer. Fabric will cover the complete spectrum of services including data movement, data lake, data engineering, data integration and data science, observational analytics, and business intelligence. With Fabric, there is no need to stitch together different services from multiple vendors. Instead, the customer enjoys end-to-end, highly integrated, single offering that is easy to understand, onboard, create and operate.
This is a hugely important new product from Microsoft and I will simplify your understanding of it via a presentation and demo.
Agenda:
What is Microsoft Fabric?
Workspaces and capacities
OneLake
Lakehouse
Data Warehouse
ADF
Power BI / DirectLake
Resources
This document provides an overview and strategy for Oracle systems. It outlines challenges customers face with increasing costs, resource constraints, time to value, and outdated infrastructure. It then summarizes Oracle's engineered systems approach which provides extreme performance, low risk deployment, and breakthrough efficiency through fully integrated hardware and software solutions. The document reviews several Oracle engineered systems like Exadata, Exalogic, Exalytics, and Oracle servers that are designed to work together.
This document provides an overview of key concepts and services in Microsoft Azure. It discusses economies of scale, public cloud models, private and hybrid cloud models, and compares cloud service models. It also covers core Azure architectural components, services, solutions, and management tools. Key areas discussed include compute, networking, data services, big data and analytics, artificial intelligence, internet of things, and security. Monitoring and governance methodologies in Azure are also summarized.
Databricks is a Software-as-a-Service-like experience (or Spark-as-a-service) that is a tool for curating and processing massive amounts of data and developing, training and deploying models on that data, and managing the whole workflow process throughout the project. It is for those who are comfortable with Apache Spark as it is 100% based on Spark and is extensible with support for Scala, Java, R, and Python alongside Spark SQL, GraphX, Streaming and Machine Learning Library (Mllib). It has built-in integration with many data sources, has a workflow scheduler, allows for real-time workspace collaboration, and has performance improvements over traditional Apache Spark.
Azure Cost Management is a native Azure service that helps you analyze costs, create and manage budgets, export data, and review and act on optimization recommendations to save money.
Windows Intune is a cloud-based security and management service that allows users to protect PCs from malware, manage updates, monitor PCs proactively, provide remote assistance, inventory hardware and software, and set security policies from anywhere without complex infrastructure. While it delivers some rich functionality of on-premises solutions, its monitoring events are limited compared to the comprehensive set available in on-premises solutions. It is an easy-to-deploy, subscription-based solution hosted on a highly available, secure, private, and scalable multi-tenant service.
This is part 1 of the Azure storage series, where we will build our understanding of Azure Storage, and will also learn about the storage data services, and the types of Azure Storage. Last but not least, we will also touch base on securing storage accounts
In the second part, we will continue with our demo on creating and utilizing the Azure Storage.
1. Azure Governance provides native platform capabilities to ensure compliant use of cloud resources through environment factory, policy-based control, and resource visibility features.
2. Environment factory allows users to deploy and update cloud environments in a repeatable manner using composable artifacts like ARM templates.
3. Policy-based control enables real-time policy evaluation and enforcement as well as periodic and on-demand compliance assessment at scale across management groups.
Oracle Cloud Infrastructure is a cloud platform designed to help customers modernize, adapt, and innovate. It provides over 100 platform services to support workloads, runs in 46 global cloud regions, and offers flexibility through public cloud, hybrid cloud, and multicloud options. OCI aims to help customers modernize their entire application portfolio and infrastructure more efficiently and with more agility.
This overview provides insight into the ODA Engineered System. It outlines how the ODA is: Simple, Optimsed and Affordable to implement for all organisations.
Contact me to find out more:
E-mail:[email protected]
Phone: +441189244490
Twitter: @daryllwhyte
LinkedIn: https://ie.linkedin.com/in/daryllwhyte
Website- Oracle ODA: https://www.oracle.com/oda
This document discusses designing a modern data warehouse in Azure. It provides an overview of traditional vs. self-service data warehouses and their limitations. It also outlines challenges with current data warehouses around timeliness, flexibility, quality and findability. The document then discusses why organizations need a modern data warehouse based on criteria like customer experience, quality assurance and operational efficiency. It covers various approaches to ingesting, storing, preparing, modeling and serving data on Azure. Finally, it discusses architectures like the lambda architecture and common data models.
Upgrade to Oracle Database 19c using AutoUpgrade. AutoUpgrade provides one-command orchestration to upgrade Oracle databases from earlier versions to 19c. It automates many of the pre-upgrade, upgrade, and post-upgrade tasks to simplify the upgrade process. After completing the upgrade, there are some additional post-upgrade tasks recommended such as configuring database statistics retention periods and checking free space usage.
This document provides an overview and introduction to Splunk, including:
1. It discusses the challenges of machine data including volume, velocity, variety and variability.
2. Splunk's mission is to make machine data accessible, usable and valuable to everyone.
3. It demonstrates how Splunk can unlock critical insights from machine data sources like order processing, social media, customer service systems and more.
Oracle RAC 19c: Best Practices and Secret InternalsAnil Nair
Oracle Real Application Clusters 19c provides best practices and new features for upgrading to Oracle 19c. It discusses upgrading Oracle RAC to Linux 7 with minimal downtime using node draining and relocation techniques. Oracle 19c allows for upgrading the Grid Infrastructure management repository and patching faster using a new Oracle home. The presentation also covers new resource modeling for PDBs in Oracle 19c and improved Clusterware diagnostics.
Big data architectures and the data lakeJames Serra
The document provides an overview of big data architectures and the data lake concept. It discusses why organizations are adopting data lakes to handle increasing data volumes and varieties. The key aspects covered include:
- Defining top-down and bottom-up approaches to data management
- Explaining what a data lake is and how Hadoop can function as the data lake
- Describing how a modern data warehouse combines features of a traditional data warehouse and data lake
- Discussing how federated querying allows data to be accessed across multiple sources
- Highlighting benefits of implementing big data solutions in the cloud
- Comparing shared-nothing, massively parallel processing (MPP) architectures to symmetric multi-processing (
This presentation is based on Lawrence To's Maximum Availability Architecture (MAA) Oracle Open World Presentation talking about the latest updates on high availability (HA) best practices across multiple architectures, features and products in Oracle Database 19c. It considers all workloads, OLTP, DWH and analytics, mixed workload as well as on-premises and cloud-based deployments.
Performance Optimizations in Apache ImpalaCloudera, Inc.
Apache Impala is a modern, open-source MPP SQL engine architected from the ground up for the Hadoop data processing environment. Impala provides low latency and high concurrency for BI/analytic read-mostly queries on Hadoop, not delivered by batch frameworks such as Hive or SPARK. Impala is written from the ground up in C++ and Java. It maintains Hadoop’s flexibility by utilizing standard components (HDFS, HBase, Metastore, Sentry) and is able to read the majority of the widely-used file formats (e.g. Parquet, Avro, RCFile).
To reduce latency, such as that incurred from utilizing MapReduce or by reading data remotely, Impala implements a distributed architecture based on daemon processes that are responsible for all aspects of query execution and that run on the same machines as the rest of the Hadoop infrastructure. Impala employs runtime code generation using LLVM in order to improve execution times and uses static and dynamic partition pruning to significantly reduce the amount of data accessed. The result is performance that is on par or exceeds that of commercial MPP analytic DBMSs, depending on the particular workload. Although initially designed for running on-premises against HDFS-stored data, Impala can also run on public clouds and access data stored in various storage engines such as object stores (e.g. AWS S3), Apache Kudu and HBase. In this talk, we present Impala's architecture in detail and discuss the integration with different storage engines and the cloud.
ClickHouse Materialized Views: The Magic ContinuesAltinity Ltd
Slides for the webinar, presented on February 26, 2020
By Robert Hodges, Altinity CEO
Materialized views are the killer feature of ClickHouse, and the Altinity 2019 webinar on how they work was very popular. Join this updated webinar to learn how to use materialized views to speed up queries hundreds of times. We'll cover basic design, last point queries, using TTLs to drop source data, counting unique values, and other useful tricks. Finally, we'll cover recent improvements that make materialized views more useful than ever.
This document provides an overview of Active Directory (AD) in Windows Server 2019. It describes what AD is, when and why it is used, and how to configure and manage it. Key components of AD are discussed such as domains, organizational units, group policy, backups. AD services like certificate services, domain services, and federation services are also summarized. The document provides best practices for using group policy and designing the AD structure.
Microsoft Fabric is the next version of Azure Data Factory, Azure Data Explorer, Azure Synapse Analytics, and Power BI. It brings all of these capabilities together into a single unified analytics platform that goes from the data lake to the business user in a SaaS-like environment. Therefore, the vision of Fabric is to be a one-stop shop for all the analytical needs for every enterprise and one platform for everyone from a citizen developer to a data engineer. Fabric will cover the complete spectrum of services including data movement, data lake, data engineering, data integration and data science, observational analytics, and business intelligence. With Fabric, there is no need to stitch together different services from multiple vendors. Instead, the customer enjoys end-to-end, highly integrated, single offering that is easy to understand, onboard, create and operate.
This is a hugely important new product from Microsoft and I will simplify your understanding of it via a presentation and demo.
Agenda:
What is Microsoft Fabric?
Workspaces and capacities
OneLake
Lakehouse
Data Warehouse
ADF
Power BI / DirectLake
Resources
This document provides an overview and strategy for Oracle systems. It outlines challenges customers face with increasing costs, resource constraints, time to value, and outdated infrastructure. It then summarizes Oracle's engineered systems approach which provides extreme performance, low risk deployment, and breakthrough efficiency through fully integrated hardware and software solutions. The document reviews several Oracle engineered systems like Exadata, Exalogic, Exalytics, and Oracle servers that are designed to work together.
This document provides an overview of key concepts and services in Microsoft Azure. It discusses economies of scale, public cloud models, private and hybrid cloud models, and compares cloud service models. It also covers core Azure architectural components, services, solutions, and management tools. Key areas discussed include compute, networking, data services, big data and analytics, artificial intelligence, internet of things, and security. Monitoring and governance methodologies in Azure are also summarized.
Databricks is a Software-as-a-Service-like experience (or Spark-as-a-service) that is a tool for curating and processing massive amounts of data and developing, training and deploying models on that data, and managing the whole workflow process throughout the project. It is for those who are comfortable with Apache Spark as it is 100% based on Spark and is extensible with support for Scala, Java, R, and Python alongside Spark SQL, GraphX, Streaming and Machine Learning Library (Mllib). It has built-in integration with many data sources, has a workflow scheduler, allows for real-time workspace collaboration, and has performance improvements over traditional Apache Spark.
Azure Cost Management is a native Azure service that helps you analyze costs, create and manage budgets, export data, and review and act on optimization recommendations to save money.
Windows Intune is a cloud-based security and management service that allows users to protect PCs from malware, manage updates, monitor PCs proactively, provide remote assistance, inventory hardware and software, and set security policies from anywhere without complex infrastructure. While it delivers some rich functionality of on-premises solutions, its monitoring events are limited compared to the comprehensive set available in on-premises solutions. It is an easy-to-deploy, subscription-based solution hosted on a highly available, secure, private, and scalable multi-tenant service.
This is part 1 of the Azure storage series, where we will build our understanding of Azure Storage, and will also learn about the storage data services, and the types of Azure Storage. Last but not least, we will also touch base on securing storage accounts
In the second part, we will continue with our demo on creating and utilizing the Azure Storage.
1. Azure Governance provides native platform capabilities to ensure compliant use of cloud resources through environment factory, policy-based control, and resource visibility features.
2. Environment factory allows users to deploy and update cloud environments in a repeatable manner using composable artifacts like ARM templates.
3. Policy-based control enables real-time policy evaluation and enforcement as well as periodic and on-demand compliance assessment at scale across management groups.
Oracle Cloud Infrastructure is a cloud platform designed to help customers modernize, adapt, and innovate. It provides over 100 platform services to support workloads, runs in 46 global cloud regions, and offers flexibility through public cloud, hybrid cloud, and multicloud options. OCI aims to help customers modernize their entire application portfolio and infrastructure more efficiently and with more agility.
This overview provides insight into the ODA Engineered System. It outlines how the ODA is: Simple, Optimsed and Affordable to implement for all organisations.
Contact me to find out more:
E-mail:[email protected]
Phone: +441189244490
Twitter: @daryllwhyte
LinkedIn: https://ie.linkedin.com/in/daryllwhyte
Website- Oracle ODA: https://www.oracle.com/oda
This document discusses designing a modern data warehouse in Azure. It provides an overview of traditional vs. self-service data warehouses and their limitations. It also outlines challenges with current data warehouses around timeliness, flexibility, quality and findability. The document then discusses why organizations need a modern data warehouse based on criteria like customer experience, quality assurance and operational efficiency. It covers various approaches to ingesting, storing, preparing, modeling and serving data on Azure. Finally, it discusses architectures like the lambda architecture and common data models.
Upgrade to Oracle Database 19c using AutoUpgrade. AutoUpgrade provides one-command orchestration to upgrade Oracle databases from earlier versions to 19c. It automates many of the pre-upgrade, upgrade, and post-upgrade tasks to simplify the upgrade process. After completing the upgrade, there are some additional post-upgrade tasks recommended such as configuring database statistics retention periods and checking free space usage.
The document discusses Oracle VM virtualization software. It provides an overview of Oracle's virtualization strategy and portfolio, including Oracle VM VirtualBox for development, Oracle VM Server for production environments, and Oracle VM templates to accelerate application deployment. It highlights features such as centralized management, high performance, integration with Oracle technologies like Enterprise Manager, and lower TCO compared to VMware.
Oracle Solaris Application-Centric Lifecycle and DevOpsOTN Systems Hub
This document discusses application-centric lifecycles and DevOps. It describes how traditional waterfall development models with infrastructure silos have given way to agile development models and self-service infrastructure with DevOps. It then outlines Oracle's approach to providing a complete deployment pipeline for applications with tools for packaging, testing, deploying and updating applications and infrastructure in an automated and secure manner.
Oracle super cluster for oracle e business suiteOTN Systems Hub
The document discusses Oracle SuperCluster, an engineered system optimized for Oracle E-Business Suite and Oracle Database. It provides examples of customers who implemented Oracle E-Business Suite on SuperCluster and saw significant performance improvements such as 5x faster transaction times, 2x faster patching, and a database migration completed in 12 weeks. The SuperCluster is described as Oracle's most powerful engineered system, with servers, storage, networking and software optimized to run Oracle software and applications extremely efficiently.
Oracle Solaris Simple, Flexible, Fast: Virtualization in 11.3OTN Systems Hub
Oracle Solaris
Simple, Flexible, Fast:
Virtualization in 11.3
Duncan Hardie – Principal Product Manager
Edward Pilatowicz – Senior Principal Software Engineer
Oracle Solaris
June 14, 2016
This document provides an overview of Oracle Solaris. It discusses security features like Silicon Secured Memory that protects against memory attacks. It describes how Oracle Solaris leverages across Oracle products and accelerates analytics and encryption workloads. Oracle Solaris also provides simple, secure deployment of applications in private or public clouds.
This document provides an overview of Oracle's Exalogic Elastic Cloud product. It describes Exalogic as an engineered system that provides extreme performance for Java workloads through its use of InfiniBand networking and optimized software stack. It can serve as a foundation for building private or public clouds and consolidating enterprise applications. The performance, scalability, and manageability of Exalogic are positioned as providing significant cost reductions over traditional infrastructure.
Exalogic is an engineered system optimized for running Oracle middleware and applications. The document discusses Exalogic's hardware and software components, including the Exalogic Elastic Cloud Software (EECS) which provides virtualization, management, and cloud capabilities. Key features of the latest EECS 2.0.6 release include improved performance, stability, deployment tools, and the ability to run virtual and physical environments on the same Exalogic rack.
The document summarizes Oracle's SuperCluster engineered system. It provides consolidated application and database deployment with in-memory performance. Key features include Exadata intelligent storage, Oracle M6 and T5 servers, a high-speed InfiniBand network, and Oracle VM virtualization. The SuperCluster enables database as a service with automated provisioning and security for multi-tenant deployment across industries.
Making DevOps Secure with Docker on Solaris (Oracle Open World, with Jesse Bu...Jérôme Petazzoni
Docker, the container Engine and Platform, is coming to Oracle Solaris! This is the talk that Jérôme Petazzoni (Docker) and Jesse Butler (Oracle) gave at Oracle Open World in November 2015.
Oracle Solaris Build and Run Applications Better on 11.3OTN Systems Hub
Build and Run Applications Better on Oracle Solaris 11.3
Tech Day, NYC
Liane Praza, Senior Principal Software Engineer
Ikroop Dhillon, Principal Product Manager
June, 2016
- Oracle Database Cloud Service provides Oracle Database software in a cloud environment, including features like Real Application Clusters (RAC) and Data Guard.
- It offers different service levels from a free developer tier to a managed Exadata service. The Exadata service provides extreme database performance on cloud infrastructure.
- New offerings include the Oracle Database Exadata Cloud Service, which provides the full Exadata platform as a cloud service for large, mission-critical workloads.
The document discusses MySQL Cluster and how it provides in-memory real-time performance, web scalability, and 99.999% availability. It then summarizes how PayPal, Big Fish, Alcatel-Lucent, and Playful Play use MySQL Cluster for mission critical applications that require high performance, scalability, and availability.
The document discusses MySQL Cluster, an in-memory database that provides real-time performance, scalability, and high availability. It describes how MySQL Cluster is used by major companies like PayPal, Big Fish, Alcatel-Lucent, and Playful Play to power applications that require fast data access, high scalability, and near 100% uptime. These companies chose MySQL Cluster because it can meet the demanding requirements for their mission-critical systems.
AMIS Oracle OpenWorld & CodeOne Review - Pillar 2 - SaaS and Standard Applica...Lucas Jellema
SaaS is a crucial part of Oracle's portfolio. In SaaS - Oracle claims leadership in all horizontal business applications markets except in Sales / CRM where it acknowledges Salesforce as the leader. It has the broadest portfolio of any vendor and the largest marketshares. It is now seriously modernizing the applications - around themes such as machine learning & digital assistant, smart UI, blockchain and Internet of Things. For the first time, Oracle starts to wean customers away from Applications Unlimited (EBS, Peoplesoft, Siebel, JDEdwards) and towards Fusion Applications in the cloud. This presentation introduces the Soar offer to move and improve from on premises Apps to SaaS. It also discusses the innovations announced by Oracle in its major suites. As presented on November 5th 2018 at AMIS HQ, Nieuwegein, The Netherlands.
The annual review session by the AMIS team on their findings, interpretations and opinions regarding news, trends, announcements and roadmaps around Oracle's product portfolio.
Oracle Data Integration overview, vision and roadmap. Covers GoldenGate, Data Integrator (ODI), Data Quality (EDQ), Metadata Management (MM) and Big Data Preparation (BDP)
The document outlines 5 strategic reasons for using MySQL:
1. MySQL is widely used and the #1 open source database.
2. MySQL has a low total cost of ownership.
3. MySQL is continuously innovating to meet the needs of the web.
4. MySQL is a mature solution with a long development history.
5. MySQL offers strong security features through tools like Enterprise Security, Firewall, and Audit.
The document discusses Oracle's new approach to business analytics and visualization. It notes that traditional corporate BI systems are viewed as inflexible and analytics are only for a privileged few. However, it argues there is still hope as analytics can provide a 10x ROI. The new approach involves visual analytics embedded in every Oracle solution across mobile, cloud, on-premises and big data to provide a single, integrated platform that allows business users to easily access, blend and scale insights from various data sources.
The document discusses how MySQL can be used to unlock insights from big data. It describes how MySQL provides both SQL and NoSQL access to data stored in Hadoop, allowing organizations to analyze large, diverse datasets. Tools like Apache Sqoop and the MySQL Applier for Hadoop are used to import data from MySQL to Hadoop for advanced analytics, while solutions like MySQL Fabric allow databases to scale out through data sharding.
- CIOs need to improve data center operations and support new workloads while reducing costs. They must embrace both evolutionary and transformative approaches like virtualization, private cloud, and public cloud.
- Cloud adoption is increasing, both in external public clouds and internal private clouds. Hybrid cloud approaches that leverage both internal and external options are becoming standard.
- Oracle provides integrated private and public cloud solutions from chips to cloud, allowing workloads to move seamlessly between on-premise and public cloud deployments.
Databases are fundamentally changing due to new technologies and new requirements. This has never been more evident than with Oracle Database 12c, which has been the most rapidly adopted release in over a decade. This session provides a technical introduction to what's new in Oracle Database 12c and Oracle’s Engineered systems. We will describe which industry transformation inspired each enhancement and explain when and how you can embrace each enhancement while preserving your existing performance.
MySQL London Tech Tour March 2015 - Big DataMark Swarbrick
This document discusses unlocking insights from big data using MySQL. It describes how MySQL powers major web applications and handles large volumes of data. Big data is creating new opportunities for value creation across industries like healthcare, manufacturing, and retail by enabling insights from diverse and high-volume data sources. Hadoop has become popular for scaling to store and process big data across clusters. Successful big data initiatives follow a lifecycle of acquiring, organizing, analyzing and applying data to make better decisions.
Oracle Openworld Presentation with Paul Kent (SAS) on Big Data Appliance and ...jdijcks
Learn about the benefits of Oracle Big Data Appliance and how it can drive business value underneath applications and tools. This includes a section by Paul Kent, VP Big Data SAS describing how SAS runs well on Oracle Engineered Systems and on Oracle Big Data Appliance specifically.
DBCS Office Hours - Modernization through MigrationTammy Bednar
Speakers:
Kiran Tailor - Cloud Migration Director, Oracle
Kevin Lief – Partnership and Alliances Manager - (EMEA), Advanced
Modernisation of mainframe and other legacy systems allows organizations to capitalise on existing assets as they move toward more agile, cost-effective and open technology environments. Do you have legacy applications and databases that you could modernise with Oracle, allowing you to apply cutting edge technologies, like machine learning, or BI for deeper insights about customers or products? Come to this webcast to learn about all this and how Advanced can help to get you on the path to modernisation.
AskTOM Office Hours offers free, open Q&A sessions with Oracle Database experts. Join us to get answers to all your questions about Oracle Database Cloud Service.
A spectrophotometer is an essential analytical instrument widely used in various scientific disciplines, including chemistry, biology, physics, environmental science, clinical diagnostics, and materials science, for the quantitative analysis of substances based on their interaction with light. At its core, a spectrophotometer measures the amount of light that a chemical substance absorbs by determining the intensity of light as a beam of light passes through the sample solution. The fundamental principle behind the spectrophotometer is the Beer-Lambert law, which relates the absorption of light to the properties of the material through which the light is traveling. According to this law, the absorbance is directly proportional to the concentration of the absorbing species in the material and the path length that the light travels through the sample. By exploiting this principle, a spectrophotometer provides a powerful, non-destructive means of identifying and quantifying substances in both qualitative and quantitative studies.
The construction of a spectrophotometer involves several key components, each playing a vital role in the overall functioning of the instrument. The first critical component is the light source. The choice of the light source depends on the range of wavelengths needed for analysis. For ultraviolet (UV) light, typically a deuterium lamp is used, while tungsten filament lamps are commonly used for the visible light range. In some advanced spectrophotometers, xenon lamps or other broad-spectrum sources may be used to cover a wider range of wavelengths. The light emitted from the source is then directed toward a monochromator, which isolates the desired wavelength of light from the full spectrum emitted by the lamp. Monochromators generally consist of a prism or a diffraction grating, which disperses the light into its component wavelengths. By rotating the monochromator, the instrument can select and pass a narrow band of wavelengths to the sample, ensuring that only light of the desired wavelength reaches the sample compartment.
The sample is typically held in a cuvette, a small transparent container made of quartz, glass, or plastic, depending on the wavelength range of interest. Quartz cuvettes are used for UV measurements since they do not absorb UV light, while plastic or glass cuvettes are sufficient for visible light applications. The path length of the cuvette, usually 1 cm, is a critical parameter because it influences the absorbance readings according to the Beer-Lambert law. Once the monochromatic light passes through the sample, it emerges with reduced intensity due to absorption by the sample. The transmitted light is then collected by a photodetector, which converts the light signal into an electrical signal. This electrical signal is proportional to the intensity of the transmitted light and is processed by the instrument’s electronics to calculate absorbance or transmittance values. These values are then give
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Pulmonary delivery of biologics (insulin, vaccines, mRNA)
Definition and Purpose
Pulmonary Delivery: Involves administering biologics directly to the lungs via inhalation.
Goal: To achieve rapid absorption into the bloodstream, enhance bioavailability, and improve therapeutic outcomes.
Types of Biologics
• Insulin: Used for diabetes management; inhaled insulin can provide a non-invasive alternative to injections.
• Vaccines: Pulmonary delivery of vaccines (e.g., mRNA vaccines) can stimulate local and systemic immune responses.
• mRNA Therapeutics: Inhalable mRNA formulations can be used for gene therapy and vaccination, allowing for direct delivery to lung cells.
Advantages
• Non-Invasive: Reduces the need for needles, improving patient comfort and compliance.
• Rapid Onset: Direct absorption through the alveolar membrane can lead to quicker therapeutic effects.
• Targeted Delivery: Focuses treatment on the lungs, which is beneficial for respiratory diseases.
Future Directions
• Personalized Medicine: Potential for tailored therapies based on individual patient needs and responses.
• Combination Therapies: Exploring the use of pulmonary delivery for combination therapies targeting multiple diseases.
Gene therapy via inhalation
Definition and Purpose
• Gene Therapy: A technique that involves introducing, removing, or altering genetic material within a patient’s cells to treat or prevent disease.
• Inhalation Delivery: Administering gene therapies directly to the lungs through inhalation, targeting respiratory diseases and conditions.
Mechanism of Action
• Aerosolized Vectors: Utilizes viral or non-viral vectors (e.g., liposomes, nanoparticles) to deliver therapeutic genes to lung cells.
• Cell Uptake: Once inhaled, the vectors penetrate the alveolar epithelium and deliver genetic material to target cells.
Advantages
• Localized Treatment: Direct delivery to the lungs can enhance therapeutic effects while minimizing systemic side effects.
• Non-Invasive: Inhalation is less invasive than traditional injection methods, improving patient compliance.
• Rapid Onset: Potential for quicker therapeutic effects due to direct absorption in the pulmonary system.
Personalized inhaler systems with sensors
• Smart Inhalers: Devices with sensors that track usage and technique.
• Real-Time Monitoring: Connect to apps for data on adherence and inhalation patterns.
• Tailored Treatment: Adjusts medication based on individual usage data.
• Patient Engagement: Provides feedback and reminders to empower self-management.
• Improved Outcomes: Enhances adherence and reduces exacerbations in respiratory conditions.
• Future Potential: May integrate with other health data and use AI for predictive insights.
Sustained-Release Nano Formulations
Definition: Nanoscale drug delivery systems that release therapeutic agents over an extended period.
Components: Made from polymers, lipids, or inorganic materials that encapsulate drugs.
Mechanism:
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