High Availability and Oracle SQL Developer Project Readiness Kit (Publication Date: 2024/02)


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Discover Insights, Make Informed Decisions, and Stay Ahead of the Curve:

  • Can the data platform provide the high availability required for your business critical applications?
  • What should you do to improve high availability of the real time data processing solution?
  • How do you create a data center that offers high availability, can scale to meet increasing customer demand, and yet is cost effective?
  • Key Features:

    • Comprehensive set of 1526 prioritized High Availability requirements.
    • Extensive coverage of 59 High Availability topic scopes.
    • In-depth analysis of 59 High Availability step-by-step solutions, benefits, BHAGs.
    • Detailed examination of 59 High Availability case studies and use cases.

    • Digital download upon purchase.
    • Enjoy lifetime document updates included with your purchase.
    • Benefit from a fully editable and customizable Excel format.
    • Trusted and utilized by over 10,000 organizations.

    • Covering: Numeric Functions, Aggregate Functions, Set Operators, Real Application Clusters, Database Security, Data Export, Flashback Database, High Availability, Undo Management, Object Types, Error Handling, Database Cloning, Window Functions, Database Roles, Autonomous Transactions, Extent Management, SQL Plus, Nested Tables, Grouping Data, Redo Log Management, Database Administration, Client Tools, String Functions, Date Functions, Data Manipulation, Pivoting Data, Database Objects, Bulk Processing, SQL Statements, Regular Expressions, Data Import, Data Guard, NULL Values, Explain Plan, Performance Tuning, CASE Expressions, Data Replication, Database Clustering, Automatic Storage Management, Data Types, Database Connectivity, Data Dictionary, Data Recovery, Stored Procedures, User Management, PL SQL Records, Analytic Functions, Restore Points, SQL Developer, Backup And Recovery, Complex Joins, Materialized Views, Query Optimization, Oracle SQL Developer, Views And Materialized Views, Data Pump, Object Relational Features, XML And JSON, Performance Monitoring

    High Availability Assessment Project Readiness Kit – Utilization, Solutions, Advantages, BHAG (Big Hairy Audacious Goal):

    High Availability

    High availability refers to the ability of a data platform to consistently and reliably provide access to business critical applications, without any significant disruptions or downtime.

    1. Oracle Real Application Clusters (RAC) – provides scalability and fault tolerance, ensuring high availability for business critical applications.

    2. Data Guard – offers standby databases for disaster recovery, minimizing downtime and maintaining high availability for business critical applications.

    3. Automatic Failover – in case of node failure, RAC automatically fails over to another node, ensuring continuous availability for business critical applications.

    4. Active Data Guard – allows read-only access to standby databases, enabling real-time reporting while maintaining high availability for business critical applications.

    5. Oracle Clusterware – provides cluster management and monitoring, ensuring high availability for business critical applications.

    1. Scalability and fault tolerance for seamless availability.
    2. Disaster recovery for minimal downtime.
    3. Automatic failover for uninterrupted operations.
    4. Real-time reporting while maintaining availability.
    5. Efficient management and monitoring of clusters for continuous availability.

    CONTROL QUESTION: Can the data platform provide the high availability required for the business critical applications?

    Big Hairy Audacious Goal (BHAG) for 10 years from now:

    By 2030, the data platform should be able to guarantee 99. 999% uptime for all business-critical applications. This means that any maintenance or unexpected downtime should not exceed 5 minutes per year. The platform should also have built-in failover mechanisms and automatic disaster recovery procedures to ensure seamless operations in case of a hardware or software failure. Additionally, it should have the capability to scale dynamically with increased demand and handle large volumes of data without compromising on availability. The platform should also have advanced monitoring and alerting systems in place to proactively detect and resolve any potential issues before they impact business operations. Ultimately, the goal is to have a data platform that is always available, reliable, and resilient, enabling seamless business operations and growth.

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    High Availability Case Study/Use Case example – How to use:

    Client Situation:

    The client, a leading financial services company, was facing significant challenges with their data platform′s high availability. They had multiple business critical applications that required a highly available and reliable data platform to support their daily operations. However, their existing data platform was unable to meet the uptime and availability requirements, resulting in frequent downtimes and disruptions in their business operations. This not only impacted their productivity but also resulted in financial losses and damaged their reputation among clients.

    Consulting Methodology:

    To address the client′s high availability concerns, our consulting team followed a comprehensive methodology that involved an in-depth assessment of their existing data platform, identifying the gaps and vulnerabilities, and proposing suitable solutions to improve its high availability.

    1. Assessment: The first step in the consulting process involved conducting an assessment of the client′s existing data platform. This included analyzing the architecture, hardware, software, network infrastructure, and disaster recovery plans.

    2. Gap Analysis: After the assessment, our team identified the areas of improvement and potential gaps in the client′s data platform that were causing downtime and disruptions.

    3. Solution Design: Based on the analysis and identified gaps, our team proposed a solution design that addressed the high availability concerns of the client. The proposed solution included implementing redundant systems, load balancing, failover mechanisms, and disaster recovery plans to ensure uninterrupted data availability.

    4. Implementation: The solution design was implemented using industry-leading technologies and best practices, ensuring minimal disruption to the client′s ongoing operations.

    5. Testing and Validation: Once the implementation was completed, our team conducted rigorous testing to validate the high availability and reliability of the data platform. This involved simulating failure scenarios and measuring the time to recovery.


    Based on our consulting methodology, the following deliverables were provided to the client:

    1. Detailed assessment report highlighting the gaps and vulnerabilities in their existing data platform.

    2. Solution design document outlining the proposed changes to improve high availability.

    3. Implementation plan and timeline.

    4. Testing and validation report showcasing the effectiveness of the implemented solution.

    Implementation Challenges:

    During the implementation process, our team faced several challenges that needed to be addressed, including:

    1. Limited Downtime Window: The client′s business operations were critical, and they could only afford minimal downtime for implementing changes to their data platform. Our team had to work within a tight timeframe to minimize the impact on their ongoing operations.

    2. Integration with Legacy Systems: The client′s data platform had to be integrated with their legacy systems, which had complex requirements and protocols. Our team had to work closely with the client′s IT team to ensure seamless integration.

    3. Data Migration: As part of the solution design, our team proposed migrating their data to a new platform, which required careful planning and execution to avoid any data loss or disruption in the business operations.


    The success of our consulting engagement was measured using the following KPIs:

    1. Uptime: The uptime of the data platform increased from 97% to 99.9%, meeting the high availability requirements of the client.

    2. Recovery Time Objective (RTO): The RTO reduced from two hours to fifteen minutes, ensuring minimal disruption to business operations in the event of a failure.

    3. Recovery Point Objective (RPO): The RPO was reduced from eight hours to one hour, minimizing data loss in case of a disaster.

    4. Customer Satisfaction: The client′s satisfaction with the improved high availability of their data platform was measured through regular feedback surveys, and it showed a significant increase from their previous satisfaction levels.

    Management Considerations:

    1. Budget Constraints: The client had budget constraints, and our team worked within those constraints to provide an effective solution that met their high availability requirements.

    2. Ongoing Maintenance: To ensure the continuous availability of their data platform, our team recommended regular maintenance and monitoring. We also provided the client with a detailed maintenance plan and a training session to equip their IT team with the necessary skills.


    1. According to IDC′s report, The Business Value of High Availability Storage Environments, organizations with high availability storage environments experience 97% less downtime and 90% shorter outages compared to those with non-HA environments.

    2. A research paper by McKinsey & Company titled Unlocking the potential of blockchain for financial services states that high availability is a critical requirement for blockchain-based technology in financial services companies due to the industry′s high volume and real-time nature of transactions.

    3. Cognizant′s whitepaper on High Availability: The Cornerstone of Your Finance Applications′ Resilience highlights the importance of high availability for finance applications and the impact of downtime on financial institutions, including reputational damage, revenue loss, and regulatory compliance risks.

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