Grow and Improve Your Business by Predicting Future Patterns Properly
Data Collection is the First but Most Important Step

Data has become one of the world’s most precious resources so that the right and correct use of this data determines the direction of successes of many businesses. Furthermore, in the first step of any analytics, it is very important that the data is collected in the right and appropriate way and with high quality. Today, with the dramatic growth of technology, data is being generated at a very high rate and on a large scale. What seems necessary in this process is that this growing amount of data is carefully collected and selected In order to turn data into knowledge. Thus, we need accurate data collection for maintaining the integrity of research in business.

Data Collection is the process of gathering and measuring information on some targeted variables in a standardized and structured framework that enables enterprises and organizations answers their questions and the arisen issues and problems. In fact, the most important aspect of any decisions that we make in business is based on the data that is collected around it.

At first, define your project objectives and questions. Afterwards, in the process of collecting data we need to build and organize a data collection plan in order to ensure consistency and reliability of the collected data for which it leads to accurate results. And also, it is essential to have a data collection system for integrating the data. Protect your data integrity to support the observation of errors in the data collection process by taking and adopting two approaches: quality assurance and quality control.

Evaluate and improve your collected data for integrity of the research, reducing the probability of errors, efficient decision making, decreasing cost and time.

There are lots of ways and tools for collecting qualitative and quantitative data that it includes surveys, online tracking and marketing analytics, social media monitoring, questionnaire-based systems, computer-assisted interviewing systems.