Data lab

The 5 essential ingredients of good data strategy

A good data strategy should be tailored to your organisation and robust against disruption. A data strategy should take into account the current business needs and potential for growth, and the possibilities that AI can bring in the future.

Five facets of data strategy

At Fast Data Science, we approach data strategy from these angles:

• Planning and discovery: we need to identify the data used in your organisation and understand its purpose and potential

• Data storage: we need to establish a plan for managing the storage of data and how it will move between systems.
• Data exploration and analytics: this is where the exciting AI happens.
• Risk and compliance management: we need to ensure that our data is safe, that GDPR, HIPAA etc are followed, and that our AI is accountable.
• Change management: this encompasses communication within the organisation, that we have a good executive sponsor, do we have change champions within the organisation, etc.

The five facets of data strategy consulting.

Starting out on a venture

If you are starting on a new venture and know that data science and AI will form part of your business model in the future, it’s worth getting some data strategy consulting at the outset to ensure that your data processes and data collection is on the right track.

AI strategy and machine learning strategy

Deep learning may appear as the best tool to be used in all projects, however big or small, when in reality most problems in data science are best solved with other simpler tools. We will discuss the pros and cons of the various options with you.

Data gathering

Normally before starting a data science project you must also have enough data gathering procedures in place. Is your website logging customer events? Does your app log users’ activity? Are you saving recorded images or overwriting them? With the advent of GDPR you will also need to make sure your agreement with your users or customers permits you to log the data we need.

Cloud or on premise?

Then there is the question of where and how you should build, host and deploy your solutions. We can work with on site or cloud providers according to your organisation’s preferences.

If you bring me on board your project at the beginning of a data science project, we will help you to make informed decisions and avoid sinking cash into approaches that later prove to be dead ends. We will help to set up a long lasting data science strategy which will be robust even in the face of future changes in your technology stack or business direction.