Four Strategies to Capture and Create Value from Big Data

Big data is a capability that allows firms to extract value from large volumes of data. When combining two dimensions — business objective and data type — the use of big data can be organized into four main strategies. 1) Performance management involves understanding the meaning of big data in company databases using pre-determined queries and multidimensional analysis. The data used for this analysis are transactional. 2) Data exploration makes heavy use of statistics to experiment and get answers to questions that managers might not have considered. It leverages predictive modeling techniques to predict user behaviour based on past business transactions and preferences. 3) Social analytics examines the vast amount of non-transactional data, often on social media platforms. 4) Decision science involves experiments and analysis of non-transactional data, such as consumer-generated product ideas and product reviews. In addition to explaining these strategies, this article provides a list of popular big data techniques and vendors and identifies three emergent big data practices: a) integrating multiple big data streams; b) building a big data capability; and c) being proactive and creating a big data policy.

• Transactional Data
• Predictive Modeling
• Social Media
• Product Reviews
• Analytics
• Big Data