Having clean, accurate data is essential for smooth business operations – especially when managing shipping orders and deliveries. Companies that rely on inaccurate data can quickly cause issues for themselves and their customers.
Cognistx Co-founder and CEO Sanjay Chopra points out that when you put garbage in, you get garbage out.
"If you have bad data, and you're relying on that data to make business decisions, more than likely, your business decisions won't be great."
If you're working on deliveries, imagine having to serve clients without a correct location or address and doing route planning based on those addresses. And then, if you add other unknown or inaccurate pieces on top of it – such as, in the propane industry, you don't know the tank size, the tank capacity, or the number of gallons that were delivered accurately last time – trying to predict how much and when they will need it becomes tough.
"One of the biggest reasons why there are data quality issues is inaccurate or incomplete data entries by human beings," says Chopra. "The majority of the data quality issues occur because data is not entered correctly. This can lead to inaccurate or incomplete data, which affects the quality of subsequent analyses as well."
Data Validation & Lack of Standardization
Another primary reason for poor data quality is a lack of data validation; if data isn't validated regularly, it can lead to inconsistencies and errors. A third big reason for data quality issues is a lack of standardization.
Database fields, says Chopra, have headers identifying one column for inputting a first name and another column's header indicating adding a last name. Without those headings/identifiers in those columns, any info could be entered, which would lead to issues with the data. This basic example clearly shows the importance of standardization. Other problematic practices include poor data storage, poor data management, lack of data cleansing and inconsistent data definitions.
Eliminating Hurdles to Data Quality
Cognistx's goal is to eliminate these hurdles to obtaining clean data through the use of artificial intelligence or AI.
"One of the capabilities of the Cognistx data quality engine is data anomaly detection," says Chopra. "We quickly integrate with a new customer's data, and the data quality engine has pre-built business intelligence models that help to identify inaccuracy, incompleteness, inconsistency; this reduces the unreliability of data."
Working with Clients
The first step Cognistx takes with a new customer is to identify the inconsistencies in their data. The second step is automated data cleaning, which helps normalize and complete the data while improving the consistency and reliability of the data.
"So, as soon as we integrate with a new customer's data, by understanding the structure and form of the rest of the data present in the database, data quality engine models recommend and clean the erroneous data," explains Chopra. "Of course, initially, when we start recommending a better data field or data value, we will need some kind of data validation for some initial weeks, but after that, the models that we have created will keep cleaning data at a constant, frequent level."
Out of the $110 billion data quality engine industry, Cognistx sets itself apart with the business-specific or the domain-specific solutions it has created. Cognistx developed the Data Quality Engine (DQE) to help businesses clean and manage their data. The DQE was first deployed to help oil and gas distributors.
"Two of the industries we were focusing on were propane distribution and paint manufacturing," says Chopra. "So, our solutions are laser focused on these two particular industries, and that is where our USP [unique selling point] lies."
As part of that focus, Cognistx built AI to optimize delivery routes for propane distribution companies.
"A lot of the district managers are planning it in a manual way," says Chopra, "so they spend a lot of time in that. What we have done is to solve the specific problem for this domain."
Cognistx's optimized routing solution creates a precise plan for district managers, saving vast amounts of time and effort and allowing them to work on other duties.