Data driven solutions is a method of marketing that is focused by using data to reach out to consumers who are more likely to react to your offerings or services. This strategy is becoming more popular in the e-commerce market and has been proved to be more effective than traditional methods of marketing.
Machine learning, data analytics and other computational techniques are employed to make sense of big data from various sources to meet specific business needs. Engineers can, for instance develop more efficient transport systems by analyzing data on traffic patterns and air pollution. Data collection and analysis in real-time can also help improve urban planning and the city’s infrastructure. This is because it permits governments to identify areas in need of improvement, like traffic congestion or public transport routes.
The first step to develop the data-driven solution is to clearly articulate the business issue that needs to be resolved. This ensures that the data is pertinent and that the insights generated are based upon empirical evidence. It is crucial to involve stakeholders at the beginning of this process, since it helps align initiatives in data with business goals and goals.
The next step is collecting the data required to support the solution. This could involve collecting data from external and internal sources, including customer databases web analytics tools and software applications. Once the data is collected it is important to standardize and organize it for easy analysis. This is where data management solutions, such as Hadoop, Apache Spark and AWS Glue, come into the picture. They provide a highly scalable platform to manage, store and process huge amounts of data. They also help businesses create a unified data catalog for easy access and management of data sets.
https://existentialbiz.com/2019/11/10/existential-business-in-our-time
