The Importance of Data Scientists and Relevant Data

According to Analytics Insight, the Data Science field will involve as many as three million jobs by 2021. This includes positions including data analyst, statistician, data engineer/architect, machine learning engineer, big data engineer, business analyst, information security analyst, and management information system. The reason why data scientists are in such high demand now is because companies especially tech are starting to become data driven.

Data is required in all business decisions. However, companies on average use only 50% of all data available for decision making. The main reasons for this involve the quality of the data, the data not being available, or lack of data scientists within the company. The data not being available is not a good excuse for this. Within data science, there is a concept called missing data which provides several methods for interpreting data that is missing from the dataset. This can involve imputing missing data based on the type of missing data or amount of missing data there is. There are several ways that data can be missing from the set including missing completely at random, missing at random, etc. Generally, ignoring missing data is okay if less than 5% of the data is missing. But in our case, much more is missing which drives the analysis in a completely direction. The aspect involving quality of the data can be improved. A common reason to low data quality involves imbalanced data, where the distribution of data is not equal, leading to bias and lowering of predictive performance. Data scientists can handle this problem as well.

Another importance of a company is the consumers itself. Data science is a big contributor to how customers view and trust the company. A lot of it comes from Artificial Intelligence and speed. AI is important to attributing to value by processing data. For example, voice assistants such as google assistant and SIRI use AL and Natural Language Processing to respond to a consumer while improve speed and efficiency. Another bonus from this includes a natural response from these voice assistants. None of this would not exist without the works of data scientists within Google and Apple.

Data science is still a new, important developing field. Without data efficiency, company performance would drastically go down due to lack of value from consumers. The best part of working as a data scientist is that since most industries are becoming data-driven, there is nearly always a data scientist in need in any field of interest.