Preparing your business for data science
What do you need to be ready for data science?
So you’re thinking about doing implementing data science project in your business?
You might be considering one or all of these options:
- Hiring a data scientist
- Using existing staff
- Engaging a consultant
Like with most things in business, if you fail to plan, you plan to fail.
Starting out on a project without adequate planning, risks wasted time and money when you hit unexpected roadblocks. Additionally, putting a data science project into production without sufficient testing, monitoring, and due diligence around legal obligations, can expose you to substantial problems.
I want to help you avoid as much as risk as possible by taking you through my data science readiness checklist, including topics like:
- Application development processes and capabilities
- Data platform maturity
- Use of data products within the business
- Skillsets of existing business intelligence and other analytical teams
- Analytical teams processes and capabilities
- IT and analytical teams alignment to business goals
- Recruitment, induction, and professional development processes
- Legal, ethical, and regulatory considerations
Armed with the checklist, there’ll be fewer “unknown unknowns” that could derail your project or cause extra cost. Let’s get planning!
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- February 23rd, 2018 - SQLBits