Datatron Blog

Stay Current with AI/ML

data trust

Don’t Let Your Dirty Data Get You Down

Dirty data” is a slang term for raw data, such as data that differ in format, resulting in duplicates, includes special characters or HTML tags, or has empty fields or errors, before undergoing an enrichment process. Consider a common example: The good old U.S. of A:

The foundation of any successful predictive analytics program is built on consistent and correct data.

United States of America, United States, U.S.A., USA, U.S., US, 100-United States of America.

There are 196 countries in the world, and we refer to a number of them in multiple ways. If your predictive analytics program integrates feeds from multiple data sources, you may find the globe suddenly expanding by a hundred extra countries.

Date formats are not universal. One thousand can be entered like this: 1,000 or like this: 1000. And then there’s human error. Adding an extra “0” once in sales data can throw the whole curve.

On average, 24% of enterprise data is dirty and unusable. Gaining the true insight to make quality decisions relies high quality data. Manually reviewing data tables is extremely time consuming, can cost you up to $83 for every 100 records in a database.

Meanwhile, the relevancy of your data is steadily slipping away. Never mind being agile, you’ve got another 100,000 tables to go.

Datatron provides a better way. Our AI data cleansing processes engage the five deep learning models represented in the following graphic to address duplication, outlier removal (for more representative metrics), identity resolution, enrichment (rectify incomplete entries), and subsidiaries (recategorize with mother company).

dirty data

Access to big data does not automatically increase your marketing prowess. Analytics based on accurate, timely and complete data support the optimization of your marketing plans and the identification of the next best action. Effective and automatic data cleansing technology is the first step in making your data work for you.

Take the example of Talkdesk, a cloud-based software provider for call centers, headquartered in San Francisco. Talkdesk has over 300,000 records in its database and adds 3,000 records every month.

Upon the discovery that up to 40% of its marketing and sales data was dirty and unusable, Talkdesk engaged Datatron. The company had used an array of different providers over the years, but still had not gained the insight to truly maximize marketing decisions.

Through Datatron’s automated AI data cleansing process and improved analytics, Talkdesk was able to immediately secure new marketing gains:

  • 11.5% increase in sales and marketing leads
  • 15% increase in the size of sales based on improved forecasting
  • 11% increase in deal velocity leading to shorter sales cycles
  • 25% increase in efficiency in the selling time of sales team
  • 27% improvement in overall data quality

According to Mike Leeds, Talkdesk Senior Director of Sales Operations, “The power of using Datatron AI surprised us with how much they made an impact on areas we were not expecting — like cost savings within our SDR team. And the confidence and trust our sales team has in the data going forward is a huge upside — for both our sales and marketing efforts as well as improved morale. Ongoing cleansing of our data 24/7 is how we do business.”

Don’t let your dirty data get you down — harness the true potential of your sales and marketing staff through improving the quality of your data through Datatron’s automated AI data cleansing capabilities.

Thanks for the read!

For more articles, go here!

Here at Datatron, we offer a platform to govern and manage all of your Machine Learning, Artificial Intelligence, and Data Science Models in Production. Additionally, we help you automate, optimize, and accelerate your ML models to ensure they are running smoothly and efficiently in production — To learn more about our services be sure to Request a Demo.


Datatron 3.0 Product Release – Enterprise Feature Enhancements

Streamlined features that improve operational workflows, enforce enterprise-grade security, and simplify troubleshooting.

Get Whitepaper


Datatron 3.0 Product Release – Simplified Kubernetes Management

Eliminate the complexities of Kubernetes management and deploy new virtual private cloud environments in just a few clicks.

Get Whitepaper


Datatron 3.0 Product Release – JupyterHub Integration

Datatron continues to lead the way with simplifying data scientist workflows and delivering value from AI/ML with the new JupyterHub integration as part of the “Datatron 3.0” product release.

Get Whitepaper


Success Story: Global Bank Monitors 1,000’s of Models On Datatron

A top global bank was looking for an AI Governance platform and discovered so much more. With Datatron, executives can now easily monitor the “Health” of thousands of models, data scientists decreased the time required to identify issues with models and uncover the root cause by 65%, and each BU decreased their audit reporting time by 65%.

Get Whitepaper


Success Story: Domino’s 10x Model Deployment Velocity

Domino’s was looking for an AI Governance platform and discovered so much more. With Datatron, Domino’s accelerated model deployment 10x, and achieved 80% more risk-free model deployments, all while giving executives a global view of models and helping them to understand the KPI metrics achieved to increase ROI.

Get Whitepaper


5 Reasons Your AI/ML Models are Stuck in the Lab

AI/ML Executive need more ROI from AI/ML? Data Scientist want to get more models into production? ML DevOps Engineer/IT want an easier way to manage multiple models. Learn how enterprises with mature AI/ML programs overcome obstacles to operationalize more models with greater ease and less manpower.

Get Whitepaper