The Importance of Data Quality During An Age of Analytics

If there is one thing that is imperative for any organization to be successful, it is high data quality. This is especially the case in today’s age of analytics. Businesses can be affected in many areas if data of low quality is able to be spread across departments. Performance can dip, customer or prospect data can be incomplete and communication efforts can be wasted. Therefore, improving the quality of data that is utilized should be one of the top priorities of any business.


One of the first things any business should do with the quality of the data is to perform assessment checks to ensure that the quality is high. There are some key steps to follow when undergoing this process.

First, gathering a list of recent data records that are used or created should be put together. Usually, these are compressed into the last 100 records. Next, around 10 or so data elements that are key to business operations should be focused on. The management teams should be able to go through each record and identify any potential errors and examine these results.

Once the results are thoroughly examined, a proper determination about the quality of data should be reached. If there are errors in more than two-thirds of the data, the quality of data can be hurting overall performance.

The Right Tools

In the analytics age, ensuring that the right tools are on standby is important for effective data management as well. Data is arguably a company’s biggest asset, and can directly influence performance for years to come.

There are specific tools that are needed for accurate analysis of data. Tools that are used should have third-party integration, shareable dashboards, data normalization and must be fully mobile.

Requesting a demo of any platform that is being considered is wide just to make sure that there is a feel of how it will work. You will also want to know how intuitive it is and how the dashboard is like. From there, you can make evaluations such as if the experience is satisfactory. If first impressions tell you that something is wrong, it is best to disregard it altogether.

Web Data Integration

Web data integration is another important process that can make checking data quality much less stressful. It entails normalizing data and presenting visuals to make analysis easier. WDI is very similar to web scraping, but it is far more comprehensive. This process can also help capitalize on massive influxes of data that are transferred. In order to analyze data accurately during the age of analytics, WDI is something that many businesses may want to consider.

Data Management Tips

Since the quality of data affects a number of important functions, there should be effective methods that businesses use to manage this data. One of the best ways to ensure proper management is to ensure that employees are updated with some of the best practices available. This includes methods involving safety, compliance, management and data entry.

In addition, certain team members should be designated to handle roper data management so as to not cause confusion. This can also work if there are data management hierarchies created to have multiple teams organize all of the proceedings. This could greatly decrease the chance that a breach occurs.

Finally, all of the data should be moved to a centralized database where a data architecture can be standardized and easier to track.

It is important for businesses to understand how to manage data during an age where many are embracing analytics.