Chapter 4. Building Your Analytics Platform
Whether you aim to build a simple dashboard highlighting basic company KPIs or a real-time predictive model to recommend products to customers, you will want to work backwards from the output to define the data architecture, design, tools, and people you will need to leverage to achieve this. This chapter will start with an overview of the current landscape of tools, data needs, and associated costs. It will end with some best practices, including Agile project management and building with quality and stakeholder trust in mind.
Technological Options
The AI hype has gone through several cycles of boom and bust. However, since 2010, we have seen an aggressive and steady push to inject more analytics and data savviness into nearly all industries and companies. To remain relevant and competitive, leaders have been pressured to learn and incorporate data and data systems into business decisions and product development pipelines. While some companies have lagged behind due to a lack of infrastructure or data expertise, or resistance to change, most companies have begun to leverage data to inform business decisions, and others have fully leaned in to create data-driven products. The industry, company, product, and leadership all impact the stage of data adoption and maturity they are and in what ways data is being leveraged.
In Chapter 1, we introduced the concept of data-informed decision-making. Applying this concept to companies, this ...
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