DataSelf Analytics - Deployment Steps

DataSelf Analytics can be deployed using two main methods:

1. Self-service Deployment: It’s designed for clients who are knowledgeable about their IT environment, BI infrastructure, source systems, and the DataSelf toolset. In these cases, the out-of-the-box deployment can often be completed in minutes to hours, depending on access, configuration, data volume, and the client’s technical readiness.

2. DataSelf-assisted Deployment: It’s recommended for clients who prefer or require assistance from the DataSelf team. In this approach, DataSelf consultants help guide the client through the deployment process, including kickoff, source system connection, data extraction, scheduling, QA guidance, security setup, and training. In these cases, thedeployment can often be completed in days to weeks, depending on the client’s technical readiness.

The following is a summary of the main steps involved in deploying DataSelf Analytics via the DataSelf-assisted deployment approach:

• Order: The client places the order and pays for the software subscription (SaaS) and consulting services fees to their DataSelf seller.

• Kickoff and Alignment Meeting: The meetings take place soon after paperwork and payments are processed by the parties. It covers an overview of the order (SOW), schedule, roles, and next steps. Recommended stakeholders from the client (and VAR if applicable): business sponsor, project manager, IT lead, main source system (ERP/CRM) tech lead.

• Deployment of the out-of-the-box DataSelf Analytics solution: This usually happens within one to five business days from the kickoff meeting. A DataSelf BI Consultant works with the client’s IT to connect DataSelf ETL+ to the source system(s), executes a data load test, schedules the ETL+ automatic data extraction, and sets up security access to a few users. This step typically includes:

  • The provision of the client’s ETL+ and the data warehouse.

  • Connection/integration with the client’s analytics layer (such as Claude, ChatGPT, Domo, Excel, MS Fabric, Power BI, Tableau, and others).

  • The connection and provision of the client’s DFT+ templates across the client’s ETL+, data warehouse, and analytics layer(s).

  • Test and scheduled data refreshes to be sure the client’s data flows from their source system(s) all the way to the anaytics layer error free.

• Monitor the Go Live: At this point, the out-of-the-box system should be fully live and automatically extracting new data into the reporting system. Status logs are emailed to the selected recipients whenever data extractions execute (though they can later be set to only send on errors). Occasionally, error logs may uncover firewall or other security issues, scheduling conflicts, etc., that need additional resolution.

• Customizations: If customizations are required before QA, please check the tasks and schedule.

• Quality Assurance (QA): A DataSelf BI Certified Consultant trains the client’s business analyst(s) on how to run DataSelf QA reports. The business analyst(s) compares DataSelf QA reports against reports from the source system(s). DataSelf reports should match to the penny with your source system’s reports. For every reporting area (for instance, AR Aging Today), it should take a couple of hours of work for the business analyst to match the numbers (or report the discrepancies). If this process takes longer, we recommend contacting your DataSelf Consultant to discuss why it’s taking so long.

• Customizations: If customizations are required after QA, please check the tasks and schedule.

• User security: A DataSelf BI Certified Consultant will discuss your user security needs and implement/assist in setting up the system as described in your order (SOW).

• User Training and Onboarding: Please check the training included in your order (SOW).