By 2025, the amount of newly created data worldwide will exceed 160ZB which is ten times that of 2016!
With the rapid development of the Internet, Big Data has become the buzzword. It is often mentioned in IT, finance, retail, and government services, putting a spotlight on digital marketing and e-commerce. The rise of search engines and social media has also led to an increase of data available, making it easier to collect consumer information. Many large companies will consolidate the data as a database to make it more efficient to understand consumer preferences and adjust market strategies.
Regardless of company size, as long as an enterprise can extract appropriate data and analyze them, they can transform the data into information with commercial value, reduce costs and investment risks, improve the efficiency of decision-making, and even understand competitors’ strategies. Making data-driven business decisions is the key to success.
Pain Points We Solved
Even when it is easier to collect data, how can businesses sieve through the large amount of data and select the most critical data for analysis and prediction? Some SMEs can only rely on the traditional marketing model and make speculations based on experience and market sense. However, the lack of systematic data analysis makes it easy to ignore market changes and increase investment risks.
As a solution, business intelligence emerged. Through the integration of business information through data analysis tools, data is transformed into easy-to-understand visual reports. With the addition of data mining and data forecasting technologies, companies can come up with faster and more cost-effective solutions and make profitable business decisions based on the content.
A real-life case of an online pet shop: Data-oriented reform in marketing for enhanced insights!
This online pet shop has been in business for two years. In the past, it has been advertising on social media to attract new customers. However, the results have been mediocre, and the business revenue was not stable. For long-term business development, the shop owner decided to enrol in this course, hoping to learn the application of data, and seek a change in the business model.
After completing this course, the store owner learned about consumption patterns and habits through