The Data Strategy Course: Building a Data-driven Business

Define the five strategic data use case areas—decision making, customer and market insight, smarter products, improved operations, and data monetization—to guide a data-driven business strategy.

Enable more people to access data and use it through curated dashboards to drive data-driven decision making that turns questions into actions and improves performance.

Compare curated dashboards with self-service data exploration to balance strategic insights and user-driven analysis. Identify key questions from goals and define metrics to answer them, noting both approaches can coexist.

Organizations must build end-to-end data infrastructure and elevate data literacy to empower employees to analyze and act on insights; self-service data exploration requires leadership support and high data quality.

define key business questions first (kbqs) to guide data collection, put data in context, and drive informed, data-driven decision-making.

Identify clear key business questions (KBQs) to unite siloed data, measure life-time value and loyalty with Net Promoter Score, and drive data-driven decisions through analytics.

Derive kbqs from strategy, 1–3 per objective to focus data needs, engage stakeholders, frame open questions, keep them clear, refine kbqs as information informs present-future decisions for a data-driven business.

Enable self-service data access with curated dashboards driven by key business questions, using starting screens and default visuals to democratize data-driven decision-making.

Move beyond self-service to curated dashboards that answer strategic questions with time-based visuals, benchmarks or targets, and annotations, complemented by clear text narratives to ensure insights are understood.

Discover how data strategy enables a data-driven business to understand customers and markets, predict buying or churn, and use tools like satellite tracking, weather updates, and sonar to time engagement.

A small butcher shop demonstrates how data helps understand customers and beat competition by measuring footfall with mobile signals, testing messages, and using open data like weather forecasts.

Netflix puts data and AI at the core of its strategy, using granular consumer insights to guide content, recommendations, thumbnails, streaming quality, and pre-production and post-production decisions.

Explore how Amazon uses customer data and collaborative filtering to power recommendation engines and build a 360-degree view that personalizes product suggestions.

Real-time and historical health data power predictive analytics to forecast ICU bed demand and patient flow. Learn how structured and unstructured data feed machine learning models for capacity planning.

Leverage data and AI to deliver personalized services, add value for customers, and predict needs, as shown by anticipatory shipping and predictive maintenance examples.

Explore seven data- and ai-driven ways to transform business processes, from automating meetings and boosting sales to improving product development and recruitment.

Leverage data from IoT and AI-enabled products to boost customer satisfaction, enhance product design with usage insights, and respond faster to micro moments, while creating new data-driven revenue streams.

Learn how data becomes a strategic asset by monetizing it, either by creating value from data in your products or by selling insights to customers and third parties.

ShotSpotter uses city sensors and geolocation to detect gunshots and deliver real-time, data-as-a-service insights to police, monetizing sound data at scale.

Identify and prioritize data use cases that link your data strategy to business goals, exploring data, AI, and analytics to drive smarter decisions, customer insights, smarter services and automated processes.

Align each data use case with a strategic goal, define data objectives and KPIs, and assign ownership. Move beyond annual surveys to near real-time employee engagement insights.

Prioritize your data use cases by strategic importance to identify one to three priorities and one or two quick wins. Review data requirements, governance, technology, capacity, and change management annually.

Identify data use cases aligned with strategic goals and automate collection of structured, external, and unstructured data for insights.

Understand structured versus unstructured data, and how semi-structured data blends both to unlock insights using modern analytics and deep learning tools such as Deep Face and Deep Text.

Explore internal versus external data, noting ownership, cost, and control; internal data is a low-cost asset, while external data offers richer insights with access and risk considerations, best when mixed.

Learn about activity, conversation, sensor, and photo/video data and how structured, semi-structured, and unstructured formats from internal and external sources generate digital traces used for market insights.

Understand metadata as data that describes other data, defining asset type, author, date created, usage, file size, so it links videos, photographs, webpages, or spreadsheets and enables discovery and governance.

Discover how real-time streaming data and streaming analytics enable proactive decisions, real-time insights, and ML-driven use cases across industries, with end-to-end platforms and data governance.

Identify existing internal data by talking to stakeholders, then collect insights from customer conversations, surveys and focus groups, ab tests, and sensor-enabled product data to inform a data-driven strategy.

Combine internal data with external data to reveal a fuller view of customers, suppliers, and competitors using free sources like government datasets, social media, and Google Trends.

Explore external data sources for a data-driven business, using freely available datasets from World Bank Open Data, IMF, NASA, and more to fuel insights.

When the data you need doesn't exist, generate and collect it to gain competitive advantage. Innovate with IoT mobile soil testing, central data repositories, and first-to-market data insights.