Closing Data Literacy Divide Revised

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Instructor
Course
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Closing Data Literacy Divide
Data literacy is crucial to any business entity. Education is one area that needs to close the data literacy divide. Teaching K-12 has been viewed to rely more on analog teaching methods than adopting digital data literacy programs. For the case of the companies, they have had to hire more data specialist to develop comprehensive data points. Apart from hiring more data specialist, most of the companies have also considered self-service analytics This even provides an opportunity for an efficient and fast way of accomplishing its activities. Moreover, the firms need more direction toward achieving agility and accessibility.
Why the Companies must Close literacy divide
Most of the business leaders lack literacy skills for prompt data interpretation. Technology plays an essential role for analysis of the data. As a result, the learning institutions should reconsider the step of closing data literacy divide by focusing on the existing literacy skills in an organization (Dykes, paragraph 4). K-12 training on data literacy would play a key role in addressing the challenge that exists in the current system. Teaching mathematics requires diverse interpretation skills. Digital method of reaching probability and calculus could boost learning at the K-12 level (Dykes, paragraph 4).Therefore, developing a self-service program on literacy to analytic methods could better serve the organization. The process enhances the effectiveness and availability of data across the organization.

Availability of data by convenient means shows that self-service data is transformational and increases data access to the employees.
Metrics important to my Field
Important data metrics include data collected especially to do with performance, quality of education and other activities such as the rate at which goals achievement occurs within a given timeframe. Understanding of the metrics requires access to various technology-based methods that will enhance my knowledge of data analysis and mastering different data interpretation techniques.
How Companies can develop the Skill
Similarly, companies should have access to multiple ways of data analysis and interpretation from a broader perspective. It is important to note that technology does not solve everything without the aid of data interpretation methods. Training should be regularly conducted to ensure that the employers are accustomed to the skills and competency required for analyzing a different set of metrics.

Work Cited
Dykes, B. Why Companies must Close the Data Literacy divide. 2017. https://www.domo.com/blog/companies-must-close-the-data-literacy-divide-part-1/