Services
Our services team excels at skillfully handling complex service engagements, transforming even the most challenging projects into successful outcomes. Our flexible sandbox, packed with a wide range of third-party tools, replicates complex customer landscapes, illustrating the seamless incorporation of IBM software into your current infrastructure and the overall value it provides. nFolks removes sales barriers with our MVP offering, while addressing customer’s complex environments and legacy systems. We specialize in moving data out of legacy systems, sunsetting and consolidating IT environments, while showcasing the value of IBM software with 3rd party SW already deployed. We have demonstrated success in migrating difficult DataStage legacy assets with our services offering, working in tandem with IBM Expert Labs. Customer confidence in the migration or competitive replacement is bolstered with our software tools and automation approach.
Our Services Offering
1. Health Check
The nFolks health check data integration offering is a specialized service focused on assessing the efficiency, effectiveness, and reliability of your organization’s data integration processes, systems, and tools. The primary goal is to identify potential issues, inefficiencies, and vulnerabilities in data integration and provide recommendations for improvement, ensuring smooth and accurate data flow between different systems and applications. A typical health check data integration offering may include any or all of the following components:
Data Integration Architecture Review:
We evaluate your organization’s data integration architecture, including ETL (Extract, Transform, Load) processes. This involves assessing the scalability, maintainability, and performance of the overall architecture.
Data Quality Assessment:
Examines the quality of the data being integrated, focusing on aspects such as accuracy, consistency, completeness, and timeliness. This includes identifying data anomalies, inconsistencies, and potential sources of errors.
Data Mapping and Transformation Review:
Analyzes the data mapping and transformation logic applied during the integration process, ensuring that data is being transformed correctly and consistently across various systems.
Integration Tool Evaluation:
Reviews the data integration tools and technologies being used, such as ETL tools, data connectors, and APIs, to ensure they are suitable for the organization’s needs, efficient, and up-to-date.
Performance and Scalability Assessment:
Evaluates the performance and scalability of the data integration processes, identifying potential bottlenecks and performance issues that may affect the overall data flow and user experience.
Based on the findings from these assessments, the health check data integration offering provides recommendations and best practices for optimizing and enhancing the organization’s data integration processes, ensuring a robust and reliable data infrastructure.
2. Installation & Upgrade Offering
The nFolks Upgrade and Installation offering is a specialized service designed to assist your organization in upgrading or installing IBM InfoSphere DataStage, Cloud Pak for Data, and Watson Knowledge Catalog. This offering aims to ensure a smooth transition to a newer version or initial implementation while minimizing downtime, reducing risks, and optimizing performance. The offering may include any or all of the following components:
Requirement Analysis and Planning:
This phase involves understanding the organization’s existing data integration landscape, objectives, and requirements to create a comprehensive plan for the upgrade or installation. This includes determining the appropriate version, understanding dependencies, and identifying any potential challenges or risks.
Infrastructure Preparation:
Ensures that the organization’s IT infrastructure meets the system requirements for the new version, including hardware, software, and network components. This may involve provisioning additional resources, updating software, or configuring the network.
Installation or Upgrade Execution:
Performs the actual installation of the new version or the upgrade of the existing version. This includes backing up existing data and configurations, installing or updating software components, and applying any necessary patches or updates.
Data Integration Component Migration:
In the case of an upgrade, this phase involves migrating existing data integration components, such as ETL jobs, sequences, and parameters, to the new DataStage version. This may require adjustments to data mappings, transformations, or job configurations to ensure compatibility and optimal performance.
Performance Tuning and Optimization:
Optimizes the DataStage configuration and ETL jobs to ensure maximum performance, efficiency, and reliability. This may involve adjusting memory settings, parallelism options, or job design best practices.
Testing and Validation:
Conducts thorough testing of the upgraded or newly installed DataStage system, including individual ETL jobs, data quality checks, and end-to-end data integration processes. This ensures that the new environment meets functional, performance, and data quality requirements.
Training and Knowledge Transfer:
Provides training and support to the organization’s team members to ensure they are familiar with the new features, best practices, and any changes in the data integration process.
Go-Live Support and Post-Implementation Monitoring:
Assists with the transition to the new DataStage environment, including monitoring the system during the initial go-live period and providing ongoing support to address any issues or questions that arise.
By leveraging the nFolks Upgrade and Installation offering, your organization can ensure a successful implementation or transition to a new version of DataStage, while minimizing risks and maximizing the benefits of your data integration platform.
3. Modernization: IGC to CP4D WKC Conversion
Modernization involves updating, optimizing, and enhancing your organization’s existing InfoSphere or IBM Cloud Pak for Data platform to take full advantage of the IBM Data Fabric and the features, capabilities, and best practices. Key aspects of modernizing Cloud Pak for Data can include:
Platform Upgrade:
Upgrading the Cloud Pak for Data platform to the latest version to benefit from new features, enhancements, and security updates. This may involve updating the underlying Red Hat OpenShift environment, as well as individual components and services within Cloud Pak for Data.
Component Integration:
Integrating additional Cloud Pak for Data components, such as Watson Studio, Watson Machine Learning, or DataOps, to expand the platform’s capabilities and support a broader range of data and AI use cases.
Data and Application Modernization:
Refactoring, optimizing, or redesigning data integration, data governance, and analytics workloads to leverage the latest features and best practices of Cloud Pak for Data.
Training and Knowledge Transfer:
Providing ongoing training and support to the organization’s team members to ensure they are up-to-date with the latest Cloud Pak for Data features, best practices, and changes in the data integration, governance, and analytics processes.
By modernizing Cloud Pak for Data, your organization can ensure that your data and AI platform remains cutting-edge, flexible, and capable of meeting evolving business needs, while delivering maximum value and driving innovation.
4. Modernization: DataStage Legacy to CP4D Nextgen
This nFolks services offering helps your organization transition your existing IBM DataStage processes from an on-premises environment to a cloud-based platform. The offering typically includes the following components:
Assessment and Planning:
This phase involves understanding the organization’s current DataStage landscape, objectives, and requirements to create a comprehensive migration plan. This includes identifying ETL jobs, processes, and components to be migrated, prioritizing migration tasks, and estimating the effort and resources needed.
DataStage Deployment:
Installs and configures the DataStage software on the chosen cloud platform, ensuring that the environment is properly set up to run DataStage ETL jobs and processes.
ETL Job Migration:
Migrates the existing DataStage ETL jobs, sequences, and configurations from the on-premises environment to the cloud platform. This may involve adjusting data mappings, transformations, or job configurations to ensure compatibility and optimal performance in the cloud.
Data Connectivity and Integration:
Configures data connections and integrations between the cloud-based DataStage environment and various data sources and targets, such as databases, data warehouses, or data lakes.
Testing and Validation:
Conducts thorough testing of the migrated ETL jobs and processes on the cloud platform to ensure that they meet functional, performance, and data quality requirements. This includes testing individual components, data flows, and end-to-end data integration processes.
Training and Knowledge Transfer:
Provides training and support to the organization’s team members to ensure they are familiar with the cloud-based DataStage environment, best practices, and any changes in the ETL processes.
Go-Live Support and Post-Migration Monitoring:
Assists with the transition to the cloud-based DataStage environment, including monitoring the system during the initial go-live period, providing ongoing support, and helping to address any issues or questions that arise.
By leveraging a DataStage Cloud ETL migration offering, organizations can successfully transition their data integration workloads to a modern, flexible, and scalable cloud platform, unlocking new opportunities for cost savings, agility, and innovation.
5. Impact Analysis Report
This report assesses the potential effects of upgrade, changes or modifications in an organization’s data integration landscape, such as implementing new systems, modifying existing processes, or upgrading tools and technologies. The report helps your organization understand the implications of these changes on your data integration environment, including potential risks, benefits, and the resources required for successful implementation.The main components of a data integration impact analysis report typically include:
Executive Summary:
Provides an overview of the objectives, scope, methodology, and key findings of the impact analysis.
Context and Background:
Describes the current data integration landscape, including systems, processes, and tools, as well as the proposed changes and their rationale.
Change Assessment:
Details the specific changes being proposed, such as the introduction of new data sources, modifications to data mappings or transformations, or the adoption of new data integration technologies.
Impact Analysis:
- Technical Impact: Assesses the potential effects of the proposed changes on the data integration architecture, infrastructure, and performance.
- Data Quality Impact: Evaluates the potential implications of the changes on data quality, including accuracy, consistency, completeness, and timeliness.
- Business Impact: Analyzes the potential effects of the changes on business processes, decision-making, and end-user experience.
Risk Assessment:
Identifies potential risks associated with the proposed changes, including technical, operational, and organizational risks, and provides recommendations for mitigating these risks.
Implementation Plan:
Outlines the steps, milestones, and resources required for the successful implementation of the proposed changes, including a timeline and responsibilities.
Recommendations and Best Practices:
Provides guidance and best practices for implementing the proposed changes, ensuring a smooth transition and minimizing potential negative impacts on the data integration environment.
Our report will help your organization make informed decisions, mitigate risks, and ensure a smooth and successful transition.
6. Premium Technical Support Services
This nFolks services offering supplements IBM technical support and Expertise Connect aims to provide additional resources, specialized expertise, and personalized assistance to help your organization maximize the value of your IBM solutions and address complex technical challenges. This type of service offering can include a wide range of support options, tailored to the organization’s needs and goals. Key components of such a service offering may include:
Dedicated Technical Advisor:
Assigns a dedicated technical advisor with in-depth knowledge of IBM products and technologies to the organization, acting as a single point of contact for technical support and guidance. The advisor can help with troubleshooting, best practices, and optimization strategies, ensuring a seamless and efficient experience.
Enhanced Support Response:
Provides prioritized access to IBM technical support, ensuring faster response times and resolution for critical issues. This may include access to dedicated support channels, escalation paths, and priority queuing for support tickets.
Customized Training and Knowledge Transfer:
Offers tailored training sessions, workshops, and knowledge transfer activities designed to help the organization’s team members build their skills and expertise in IBM products and technologies. This can include hands-on training, webinars, or access to exclusive resources and documentation.
On-Site Support and Consulting:
Provides access to on-site support and consulting services, with IBM experts visiting the organization’s premises to address complex technical challenges, assist with system upgrades or migrations, or provide hands-on training and guidance
By leveraging a service offering that supplements IBM technical support and Expertise Connect, your organization can gain access to a higher level of personalized support and specialized expertise, helping you get the most out of your IBM investments and drive innovation, growth, and success.