Are you planning a data-intensive initiative? Targeted Marketing, Predictive Maintenance, Internet-of-Things, Customer Retention or most any other modern initiative are data-intensive. Their success is largely dependent on access to high-performing, high-quality, supported and understandable data. You may be planning to build or improve a leverageable platform such as a data lake or a data warehouse to support the initiative.
There are many questions to be answered that you need to get great answers to up front because the questions will keep coming during the initiative and you need to build on a solid project foundation.
While we have done an Information Management Action Plan (IMAP) service for over 40 clients over the years, your data strategy needs may vary which is why we have customized the IMAP service for the needs of a business initiative.
We will remotely interview your key project stakeholders, business and technical. We will understand and address your questions and the questions you should be asking at the current point of the initiative and create the next steps to conquer the important data aspect of the initiative.
Get help from the experts who have worked on the data challenges of 15 of the Fortune 1000 and numerous others; the highly published in-demand keynote speakers and analysts in the space who run the benchmarks and author the industry analysis.
MCG, led by William McKnight, will bring the necessary JUDGMENT to the process. If you entertain these important data questions in ways other than with an experienced understanding of the nuances, you will be disappointed in the project and the environment created.
We have a methodological approach to jumpstart your initiative which tremendously speeds up the value provided.
The 2-Week Data Initiative Jumpstart pairs nicely with our Proof-of-Concept service.
• What existing data artifacts can I use and how?
• What aspects of the data environment need remediation for this project?
• If I need to build a data lake or warehouse, what cloud and technology is best?
• What data goes where?
• How should data be acquired?
• How do we guide the analytics and data access?
• Do I need to stage data and where?
• What’s the data stack for the initiative (dedicated compute, storage, data integration, streaming, analytics, exploration, data lake, business intelligence, machine learning, data catalog)?
Project and Staffing
• Based on scope and timelines, how do we need to staff the project and what are the roles?
• How should we organize for agile delivery?
• What project milestones should be set in place?
• What is a realistic budget for the project or, conversely, what can I expect to do for the business with the budget I have?
• Is our path-to-production streamlined?
• How much data governance is necessary?
• What are the set of tasks for our project backlog?
• Based on the environment, what are the high-risk items and how do we mitigate?