Architecting A Scalable Data Stack

Sponsored by: RUDDERSTACK

Our world is defined by information overload. From your watch tracking your health to your washing machine notifying you when your clothes are done and your phone tracking everything, our personal lives are constantly emitting streams of data.

It’s no different for businesses. Many businesses collect the types of product data mentioned above, of course, but that’s only one kind of data. Tracking sales leads, marketing journeys and customer experiences is now standard, to name just a few forms of business data. The amount of data produced by your business is immense — if harnessed properly, it can also be immensely valuable.

Companies that can leverage this data at scale are able to better understand their businesses and iterate more quickly. This unique competitive advantage helps them ultimately win in the marketplace.

Importantly, your efforts at implementing the tools and processes required to create value from data aren’t static. As your business grows in size and complexity, you iterate to adapt to demands from customers and the market. This changes how you create value from data.

We call this process The Data Stack Journey. This paper is meant to guide you in making good foundational decisions that will give you short-term benefit, and reduce or eliminate the all-too-common growing pains that happen as your business and data grow. We will cover:

	Company stages
	The core components of the customer data stack
	Recommendations on which components to use at each stage