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According to Forbes Magazine, companies need to understand the critical importance of data quality.

Negative outcomes of poor and/or inaccurate data include: 

  • Poor decision making, based upon flawed analytics
  • Greater loss of productivity in order to fix data inaccuracies further down the pipeline from where it was gathered
  • Huge fines from regulatory compliance issues
  • Poorly targeted marketing communications
  • Damage to your company's reputation: An example would be Apple's 2012 Maps roll-out that was plagued by inaccurate and missing data

What is Data Quality? –

According to Profisee.com, there are really two issues involved in having quality data: 

  • The data helps you do what you intend with it: Such as data you have collected to determine how well customers can navigate around your website. Does the data actually help you understand that metric and make decisions on how to improve your online offering?
  • The data is an accurate representation of what is going on in the real world

What Professional Skills Aid in Data Quality Management (DQM)?

According to the Data Governance Institute, for a smaller organization, there are really three levels of employees who will deal with the management of your data:

Your Chief Data Officer or DQ Manager: This employee or consultant could actually have a number of different titles, but their role is to be the highest manager of your data. They will need to assemble a team from each department that will oversee the data. Information Week explains that this person will need to have multiple key skills, such as be highly experienced in your business field of endeavor, have a strong set of data management skills, be fluent with statistics and be very well-versed in managing the collection and usage of data. They need to have the focus of ROI.

The Data Quality Management Team: This team will be comprised of employees from each department that can fluently communicate with the other members of the team about the data that their department collects and uses. They will need to be great team players who can bridge differences and find ways to break down silos in order to create a system of DQM that works for all departments and contributes to the company's bottom line. They will need to take those communication skills and return to their own departments to help promote changes that may be made in data collection, analytics and standardization rules.

A Possible 4th Group of Data Stewards: If your organization is a bit larger, there will be data stewards who will be performing direct work on the data in order to carry out the decisions of the DQM team. This group will need the skill set to actually make changes to the data for the purposes of improving accuracy, standardizing, cleansing and creating new categories of data, as needed.

The Rest of Your Employees: Forbes is advocating for all employees to have a good set of data skills. The reason is that they have found the data skill set of many employees outside of IT usually is not adequate for them to utilize data to run analytics and make decisions on their own. For example, the marketing department can take data and analyze it to see how to better target prospects that are more likely to become customers in order to focus marketing efforts.

Forbes advocates all employees take courses in statistics and data visualization. The latter is the skill set to lay out the data in a manner that others can understand its significance. Today, such courses can be taken online through Coursera, Udemy and other providers for reasonable prices. In the case of Coursera, the courses are often taught by college professors at major universities around the country.

Now that many more companies are beginning to realize how much money they can save by having a culture of DQM and high quality data, the next step is that they ensure all employees have the necessary skill sets in order to maintain and utilize that data in order to improve ROI. 


INFOtainment News

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