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The best tips to help clean your dirty data better


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Dirty data is currently costing organizations up to $600 billion each year. The origins & causes of this data phenomenon are many but organizations should ensure that the trouble doesn’t add up & it should be eliminated from the system. Read on & know more on The Best Tips To Help Clean Your Dirty Data Better for the smooth functioning of your processes.

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The best tips to help clean your dirty data better

  1. 1. The Best Tips To Help Clean Your Dirty Data Better
  2. 2. In today’s business world, quality data means gold. No matter what kind of business you do, having quality data in hand goes a long way in performing to the best of your organization’s capability. But sometimes maintaining data sets becomes a hassle. As per various marketing researches, contact data of corporates decays on a rate of 25% annually. This means that about a quarter of the current databases will be invalid & won’t be useful in just a year. Sad…but true. Dirty data originates due to multiple factors & reasons
  3. 3. *Incomplete data *Inaccurate data *Duplicate data *Business rule violations *Incorrect data *Inconsistent data Unfortunately our technology is not advanced enough to identify the errors from the start & to nip them out from the bud. But there are certain tips that you can follow to clean up your dirty data. Dirty data originates due to multiple factors & reasons. Sometimes, the error can be caused by something as simple as a data mistake. Let’s see the six most common types of dirty data.
  4. 4.  Dedicate resources for maintaining data integrity  Implant analytics  Standardize and automate data entry  Impart visibility into the history & origin of the data  Attain help of experts
  5. 5.  Dedicate resources for maintaining data integrity It’s not possible for just one person to address all the quality issues with data. Yea, it’s necessary to have employees with statistical skills but more important to have a data champion with the knowledge for driving successful projects. Still, good decisions require inputs from across the industries than just one person. Having a shared understanding among employees regarding the uses & value of data, itself can be a remedy to data errors. Analytics tools, can play a major role in this part, as it’s driving the growth of collaborative analysis between the IT staff and business users.
  6. 6.  Implant analytics Organizations should move beyond creating analytical models to implanting analytics into their business operations for improving performance & ensuring data accuracy. Implanting analytic solutions is one of the best ways for identifying errors & warning conditions, enabling businesses in eliminating dirty data at the source and reacting faster to situation changes & process anomalies.
  7. 7.  Standardize and automate data entry Standardizing formats for data entry & requirements will ensure that critical fields are complete & the formats are consistent. Empower your data champions to apply these requirements without fail & automate data entry points where ever possible while introducing data into CRM & marketing automation platforms.
  8. 8. Sometimes it’s a hard task to convince your colleagues that dirty data exists & is badly impacting the quality of your decisions. With the aid of a visual data analytics tool, you can achieve this by showing the origin of the data along with it’s track record & the steps that are taken for arriving at any given result.  Impart visibility into the history & origin of the data
  9. 9.  Attain help of experts In general there are four main aspects of data management which are: Data Appending, Data Verification, Data Validation & Data Cleansing. There are vendors in the market who have more experience than you in these aspects of data management. Attaining the help of these data providers like DataCaptive can aid in curating the database as per your business needs in the best way possible.
  10. 10. Currently it’s impossible to stop the data rot. It’s a problem that all corporates will have to face. What marketers should focus is on having a proactive approach to replace the “afterthought” crisis management approach to dirty data. With genuine business collaborations & flexible analytics solutions, organizations will be able to successfully clean dirty data & maintain a vigilant approach to ensure data integrity.
  11. 11. Thanks! Any questions? Call us for a quote at 1-800-523-1387 Or contact us at