Data driven solutions are an extremely targeted method of marketing by using data to reach out to consumers who are more likely to respond to your services or products. This method is becoming more popular in the e-commerce market and has been proven to be more successful than traditional marketing techniques.
Data analytics, machine-learning and other computational techniques can be utilized to make sense of the massive amounts of data from multiple sources. For instance, by monitoring data on traffic patterns and air quality, engineers can devise more efficient transportation systems to reduce pollution and congestion. Real-time data collection and analysis is also aiding in the improvement of urban planning and city infrastructure by enabling governments to pinpoint areas of improvement, for instance in the case of congestion in traffic and public transport routes.
To create an enterprise solution that is based on data, it is important to clearly define the problem to be solved. This ensures that the data is pertinent and that the insights provided are based on actual evidence. Involving stakeholders at the outset of this process is vital as it helps to align data initiatives with their overall business goals and objectives.
The next step is to collect the data required to support the solution. This could involve gathering information from both internal and external sources such as customer databases and web analytics tools. After data is collected it is crucial to standardize and organize it to make it easy to analyze. Data management solutions like Hadoop Apache Spark and AWS Glue are helpful in this scenario. They provide a flexible architecture to manage, store and process large quantities of data. They allow companies to create a unified data catalog which permits easy access and management.