Data Quality Engine
Enhancing Performance, Operations and Profits with Data Quality
Fannie Mae logo

Cognistx and their DQE solution has greatly helped us to identify and address our data quality issues. Their team has become an extension of the AmeriGas team and that has helped us to move in the direction of continuous data monitoring, remediation of issues, and automation through machine-learning.

Executive | Amerigas Group Director, Logistics

The Data Quality Engine (DQE) is an AI-powered tool that not only identifies errors but corrects them. This intelligent solution employs self-learning capabilities to detect data anomalies, inconsistencies and inaccuracies and offers a seamless workflow for correction.

Key Benefits:

Identifies data issues that lead to significant operational challenges and hurdles.

Automatically cleans data using machine learning and AI technology.

Builds efficient delivery routes and provides optimal route plans.

Anticipates and proactively mitigates orders with a high probability of encountering issues.

Saves valuable time for analysts, delivery coordinators, order fulfillment and operational teams.

Significantly reduces operational costs.

features

AI-Powered Information Retrieval

SQUARE effortlessly retrieves the answers you need, saving you from the hassle of prolonged searches.

Context-Rich Answers

Unlike basic search engines, SQUARE doesn't stop at providing answers. It offers context from the source material, ensuring you understand the information in-depth and reducing the risk of misinterpretation.

Multi-Format Support

SQUARE effortlessly extracts information from various formats, including PDFs, videos, audio files, web URLs, and more. No matter where your data resides, SQUARE can access it and provide you with instant answers.

Real-time Web Intelligence

SQUARE is equipped with web crawling capabilities, allowing you to search and extract information from online sources, blogs, articles, and websites. Stay up-to-date with the latest information on the web.

Document Upload Capability

SQUARE allows you to upload your own documents directly within the application. Easily add new data sources to expand your search capabilities and find answers more effectively.

Seamless Integration

SQUARE seamlessly fits into your workflow, making it an essential tool for researchers, students, and professionals. It's user-friendly and can be customized to your specific needs.

DQE By the Numbers: Measuring Success

30M+
cost savings among clients using DQE
3M+
records cleaned
14M+
data issues identified
1M+
person hours saved
400K+
customer accounts cleaned
300K+
bad orders predicted

features

AI-Powered Information Retrieval

SQUARE effortlessly retrieves the answers you need, saving you from the hassle of prolonged searches.

Context-Rich Answers

Unlike basic search engines, SQUARE doesn't stop at providing answers. It offers context from the source material, ensuring you understand the information in-depth and reducing the risk of misinterpretation.

Multi-Format Support

SQUARE effortlessly extracts information from various formats, including PDFs, videos, audio files, web URLs, and more. No matter where your data resides, SQUARE can access it and provide you with instant answers.

Real-time Web Intelligence

SQUARE is equipped with web crawling capabilities, allowing you to search and extract information from online sources, blogs, articles, and websites. Stay up-to-date with the latest information on the web.

Document Upload Capability

SQUARE allows you to upload your own documents directly within the application. Easily add new data sources to expand your search capabilities and find answers more effectively.

Seamless Integration

SQUARE seamlessly fits into your workflow, making it an essential tool for researchers, students, and professionals. It's user-friendly and can be customized to your specific needs.

The Data Error Problem

Lost Revenue

US Companies lose over $3T in revenue and direct expenses annually as a result of poor or erroneous data.

Wasted Time

25% of senior managers report spending up to a quarter of their day searching for data.

Garbage In / Garbage Out

85% of senior managers believe their existing systems do not produce trustworthy data.

DQE Features and Add-ons

BUILT-IN FEATUREs:

Automates Data Issue Identification and Reporting

Supports Data Cleaning Efforts

Ongoing Data Quality Monitoring

Provides Tools for Granular Data Analysis

Integrates With 3rd Party Systems

Customizable to Your Data and Needs

ADD-ONs:

Route Optimization and Scheduling

Forecasting

Risk Prediction

Dynamic Pricing

Predict and Optimize Quality Outcomes and More

DQE in action

Data quality case studY

amerigas

Data Cleansing and Route Optimization

AmeriGas leverages DQE to enhance and streamline delivery routes, optimizing truck loads and elevating the efficiency of its supply chain through unparalleled accuracy. By optimizing delivery routes, the company significantly reduces costs, while enhancing relationships with customers and business partners.

AmeriGas implemented our AI-powered DQE to enhance operational efficiency, boost revenue and cut costs. The DQE identifies incorrect manual entries based on predefined business rules, while route optimization calculates the most optimal paths for product transportation.

So far, the DQE has successfully reduced costs by minimizing sub-optimal and zero-fills, while also boosting revenue by dramatically reducing no-fills.

DQE Business Benefits

• Route Optimization
• Cost Reduction
• Operational Efficiency

Results:
250+
districts covered by
route optimization
4.9M
customer accounts analyzed/year

Data quality case studY

armada

Anomaly and Error Detection

Our Data Quality Enhancement (DQE) Solution for Armada incorporates a precise set of business rules to accurately identify anomalous data and effectively mitigate misalignment of resources.

Armada encountered several supply chain challenges due to the retrieval of more than a million records every day and the absence of data quality tracking. DQE's anomaly detection examines vast and swiftly evolving datasets, enabling Armada to make well-informed decisions while conserving valuable time, money, and effort.

Analyzing process data and identifying anomalies enables Armada to minimize data errors, enhance operational efficiency, make informed decisions based on data, and save valuable time and resources.

Primary Analytical Objectives:

• Cost Reduction
• Operational Efficiency

Results:
50M+
records processed/year
1M+
anomalies detected/year
$10M+
dollars saved/year
40GB+
data processed/year

Data quality case studY

suburban

Anomaly and Error Detection

DQE has been instrumental in assisting Suburban in identifying millions of equipment-related issues that generate inefficiencies at the time of forecasting, planning, and billing. By leveraging historical patterns and the power of AI, DQE automates the resolution of these data issues, streamlining the process and ensuring greater accuracy.

DQE Business Benefits

• Reduction in forecasting an planning errors
• Avoid incorrect billing and related inefficiencies
• Cost reduction

Results:
1.3M
identified anomalies
90%
anomalies automatically fixed

recent DQE Posts

Beyond the Buzz: How AI Transforms Data Analysis
November 12, 2024

Traditional data analysis methods are grappling with the massive influx, speed, and diversity of information produced every second.Enter AI, a groundbreaking force that's transforming how we uncover insights,make informed decisions, and fuel business growth.

Why Data Quality Matters for Your Business
August 11, 2024

We've witnessed the significant impact that poor data can have on businesses across industries. Here's a look at how inaccurate or outdated data affects operations and how AI can provide solutions to enhance performance.

Get Started with DQE

request a meeting or demo

Interested in learning more about how our Data Quality Engine might benefit your company? Please use the form to request a demo or a meeting with our team.

Or if you'd like to schedule an appointment with Founder/CEO Sanjay Chopra, click here.

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