DATA QuALITY METHoD (DQM)

$3.1 Trillion Annually

Inadequate data quality costs U.S. businesses an estimated

The DQM aims to reduce this impact, combating financial losses caused by poor data quality.

175 zettabytes of data

will be created worldwide by 2025 (IDC) and

~30% of the data

will require real-time processing.

The DQM is crucial in maintaining high-quality data, and helping organizations efficiently meet growing demands.

Data Quality Method

As a data professional, you are well aware that ensuring the accuracy and trustworthiness of your data is crucial for making informed decisions. But with the ever-increasing amount of data being collected, data quality can be a challenging and time-consuming task. That's where Pandata Tech's Data Quality Method (DQM) solution comes in. Our software is designed to optimize your organization's data quality initiatives and increase algorithm reliability by over 50%. With the DQM, you can focus on innovation and success rather than spending countless hours collecting, validating, and labeling your data.

Our AI/physics-based approach provides a more efficient, accurate, and less computationally expensive solution than traditional methods like DVR. This unique approach allows us to validate both numerical and Boolean time-series data, making the DQM a valuable solution for various industries, including Defense, SCADA/ICS, Energy, Fintech, and Manufacturing. Don't just take our word for it. In a comparison race with a major O&G contractor using the same 90-day time-series data with 4.5MM+ data points, the DQM validated the data in just six minutes, while it took their team of SMEs and data professionals about a week. That's a significant reduction in the time and effort required for data validation.

By choosing Pandata Tech's DQM solution, you'll be revolutionizing your data quality initiatives and maximizing your team's productivity. Gain a competitive edge by ensuring your data is accurate and trustworthy.

What the DQM Helps Prevent

Ineffective Data Quality and Governance

  • By leveraging the DQM, organizations can enhance their data governance processes, ensuring data quality across the board, regardless of the current state of their governance efforts.

  • The DQM helps address the challenge faced by 40% of organizations where poor data quality is cited as the primary reason for failure in data analytics initiatives, enabling more successful outcomes. (Gartner)

  • The DQM helps organizations improve data quality, which is crucial for delivering better user experiences, ultimately leading to increased user satisfaction and loyalty.

Financial Loss and Inefficiency

  • With the help of the DQM, organizations can significantly reduce the occurrence of critical errors in newly created data records, ensuring higher data quality and reliability.

  • The DQM helps organizations avoid the financial impact of poor data quality, which currently costs businesses an average of $9.7 million per year. (Gartner)

  • Utilizing the DQM can prevent 80% of an analyst's time currently spent on data quality-related tasks, freeing up 60% more time for valuable activities.

Inaccurate Decision-Making

  • The DQM helps organizations maintain the accuracy and reliability of their data, avoiding pitfalls in decision-making and fostering stronger user relationships.

  • The DQM enables organizations to confidently harness data-driven insights, empowering more executives to make well-informed decisions based on substantial data analysis.

  • The DQM enables organizations to harness tangible business value through data-driven decision-making, increasing the number of organizations that benefit from high-quality data and informed decision-making processes.

Risks and Missed Opportunities

  • The DQM helps organizations identify data breaches, ensuring a more secure and reliable data environment.

  • The DQM addresses data quality issues that contribute to project challenges or cost overruns, leading to a reduced likelihood of digital transformation project failures and improved project outcomes.

  • By using the DQM, organizations can improve data quality, safeguarding against lost revenue, increased costs, and reputational damage that can occur as a result of poor data quality.

Interested in learning how Pandata Tech’s DQM can help your organization?

Real World Impact

AI EFFECTIVENESS & DATA QUALITY

85% of CEOs

(PWC survey)

believe that AI will significantly change the way they do business within the next five years.

56% Express Concern

about data quality and its impact on AI effectiveness.

The DQM addresses this concern by ensuring high data quality, which is crucial for the successful implementation of AI and machine learning technologies.

Real World Impact

RISK MITIGATION & COST REDUCTION

Organizations that improve data quality can experience reduced adverse effects from bad data and better allocate resources towards growth and innovation. Poor data quality costs organizations an average of

$14.2 Million Annually

The DQM effectively addresses risks by improving data quality, ultimately reducing the adverse effects of bad data on organizations.

Real World Impact

CONFIDENCE IN DECISION-MAKING

97% of Business Executives

report using data to make strategic decisions,

Yet Only 34% are Confident

in the accuracy of their data. (Accenture)

The DQM underscores the need for higher data quality, ensuring effective decision-making in business.

Benefits of the DQM

Improved Data Quality and Accuracy

  • Increased algorithm reliability by over 50%, providing organizations with more accurate and trustworthy data for critical decision-making.

  • Optimized data quality initiatives save time and effort on data validation, allowing data professionals to focus on innovation and success.

  • The AI/physics-based approach provides a more accurate solution, improving efficiency and providing a competitive advantage.

  • Enhanced data validation capabilities by being able to validate both numerical and Boolean time-series data to improve data accuracy and trustworthiness for better decision-making.

Increased Efficiency and Productivity:

  • Scalability to meet the needs of various industries enables organizations to easily adjust to changing business needs and requirements.

  • Ability to reduce errors and mitigate risks improves data quality and accuracy while reducing the risk of costly errors and operational damage.

  • Increased agility and responsiveness by improving data availability and accessibility enable faster decision-making and action.

  • Reduced costs by minimizing the need for manual data cleaning and validation processes improve efficiency and reduce operational costs.

Competitive Advantage

  • Quick and easy implementation and integration with existing systems enable organizations to quickly realize the benefits of improved data quality and accuracy.

  • Future-proofing your organization's data quality initiatives by leveraging cutting-edge technology and advanced algorithms that continuously learn and improve.

  • Competitive edge through faster and more accurate decision-making provides organizations with a significant advantage in a rapidly changing marketplace.

  • Enhanced risk management and mitigation strategies reduce the potential for costly operational and reputational damage.

Enhanced Analytics and Insights

  • Uncovering valuable insights and trends in data to drive business growth and innovation.

  • Enabling organizations to confidently leverage data for better decision-making.

  • Providing organizations with a more comprehensive and accurate view of their data.

  • Prioritizing data quality, which is associated with a 26% higher revenue growth rate, for improved business outcomes.

Experience the benefits of the DQM firsthand.