Essay About Different Steps And Data Quality

Assess Whether You Have a Data Quality Problem
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Anood Albaram April 4th 2017Assess whether you have a data quality problemWe all know data quality problems when we see them. These data quality problems can undermine any organization’s ability to work efficiently. Most experts find the best strategy to fight any data quality issue is to understand the root causes and to put new process in place to prevent these problems from happening. The Friday afternoon measurement aims to help answer the question “ do I need to worry about data quality?” quick and powerfully. This method helps any company to easily measure the current level of data quality and to develop a high-level estimate of its impact. It also it adopts itself well to different set of data’s, and companies. As mentioned in the article, there are four different steps.  The first step is to assemble the last 100 things that happened -data records-, for example customer accounts, or delivering a product. Then focus on 10-15 critical data element. Lay these out on a spreadsheet. Step 2 is to ask 2-4 people join for a two hour meeting( the Family Afternoon Measurement takes its name because people set up these meetings on Friday afternoon). Step 3 working record by record, marking all obvious error in a noticeable color or highlighter. This step should not take more than 30 seconds on a record. Sometimes its possible to engage in detailed discussion about whether an item is truly incorrect.  Lastly, step 4, which summarizes the results. It Marks “Yes” if there are not errors and “ No” if there’s an error. It was a simple, fast, reasonably defensible method for figuring out weather you have a problem or not. Today, most companies and many businesses realize that the quality of their information is tied to their success. Businesses rely a lot on data to make important business decisions that can affect customer service, supply chain, and many other areas. So it is very important to know what should be done if any issues slip through.