Data Warehouse Automation

The greatest success with data infrastructure automation technology occurs when you're well prepared to reap the benefits. The ideal way to be ready is to evaluate your readiness. The checklist below describes twelve criteria to consider when evaluating your organization's readiness for automation.

Requirements Gathering

Do you define requirements through user stories and discovery processes instead of using a waterfall approach of gathering business requirements, functional requirements, and technical requirements for stakeholder signoff?

Data Management Architecture 

Does your architecture use a combination of best practices and specialized elements unique to your organization's needs?

Requirements Volatility 

Do you experience frequent changes to requirements including regular change throughout the development process?

Project Risk

Do your data infrastructure projects experience a high level of risk from poor data quality, lack of source data knowledge, insufficient budget, understaffing, scope creep, and other factors?

Time to Delivery 

Do your business stakeholders expect fast and frequent delivery of data access, analysis, and business capabilities?

Operations 

Are the processes and procedures for operation of your data infrastructure complex, detailed, time consuming, labor intensive, or fragile when something doesn't work right the first time?

Documentation 

Is the documentation for your data management processes and databases sparse, dated, and frequently out-of-sync with the implementation?

Data Infrastructure Maintenance 

Is your data infrastructure maintenance difficult. challenging, and dependent upon the knowledge of a few key individuals?

Project Backlog

Do you have an outstanding list of projects in waiting with a pattern of new projects being added to the backlog faster than older projects can be completed? Do you experience competing and conflicting priorities for project funding and staffing?

Data Management Future

Are big data, cloud hosted data, cloud analytics, data science and artificial intelligence among current expectations of your business leaders and data consumers? Are they on the horizon in the foreseeable future?

Testing 

Do you lack consistent, reliable, and repeatable process for data warehouse testing including unit, stream, and integration testing during development and validation testing during operation?

Organization and Culture 

Is your data warehousing team oriented to teamwork and collaboration? Is the IT relationship with business stakeholders collaborative? Use this checklist as an aid to think through your organization's readiness for data infrastructure automation. If you answered "yes" to many of these questions then you have the need, motivation, and culture to successfully adopt and benefit from automation in your organization.