Level: Intermediate to Advanced
Traditionally, business enterprises have used data internally for three main purposes: operations, compliance, and decision making. In the last few years, data-driven companies have developed data products to generate additional revenue. A data product is an outcome of data analytics activity that generates new revenue sources, enhances customer service, or offers new solutions to problems that span the industry. Data products don’t always have to focus on creating new revenue streams; they can also be used for enhancing the success rate of delivering data-centric solutions for internal stakeholders.
Data products are valuable when they solve a specific problem within a business or the industry. According to the McKinsey Global Institute, data is a $300 billion-a-year industry today. The data sector will continue to grow due to fast-growing mobile data traffic, cloud computing traffic, and the rapid development of artificial intelligence (AI) and Internet of Things (IoT) technologies. This course will equip participants with key concepts, design patterns, and development techniques required to build successful data products.
You Will Learn
- How to understand data products, types, and key characteristics
- How to identify business opportunities with data
- How to develop the business cases for data products
- How to design data products
- How to build and deploy data products
- About the commercialization of data products
- Business/data analysts
- Data scientists
- Data engineers
- IT developers
- Product managers