Successful Digital Transformation Needs a Data Quality First Approach. Here’s How to Get Started.

Today, just about every business is undergoing some form of digital transformation. Successful digital transformation improves how enterprises efficiently utilize technology, people, and processes to create new business models and revenue streams while meeting evolving customer, stakeholder, and regulator expectations. The need to stay ahead of nimble competitors, recalibrate quickly, and identify transformative opportunities early makes accelerated digital innovation a top priority.

The majority of transformative initiatives revolve around a firm’s most critical asset—their data—and how it is managed. To identify potential digital transformation opportunities, improve customer expectations, and act quickly on business trends, firms must be able to ensure the quality of the data providing insights and analytics. If not, they may experience billion-dollar losses, customer dissatisfaction, and other disastrous consequences.

An Experian survey found that 68 percent of businesses suffer from bottlenecks as a result of poor data quality. These errors are often ignored or overlooked until it’s too late, resulting in the failure or delay of a company’s digital transformation initiatives.

Often, achieving continuous data quality requires firms to update infrastructure, adopt new tools, or undergo a significant overhaul of business processes.

Common Data Quality Issues Hindering Digital Transformation

As firms scale their business, data can easily get overlooked. In fact, low data quality can result from a variety of factors, including:

• A siloed business landscape: Data is acquired from and stored in disparate systems, applications, and workflows. Each of these data sources consists of scattered, outdated, and duplicate records, leading to inaccurate data and extensive disarray in business processes.
• Manual and human error: Human error is expected, especially when manually entering data. Spelling mistakes, typos, and a lack of consistency in naming conventions are just a few examples.
• Data decay: Data decays as people leave their current roles in the organization, companies go out of business, and mergers occur. Data becomes stale and outdated.
• Lack of golden source or single source of truth: Without establishing and verifying a golden source or single source of truth, firms cannot confidently identify data’s genesis and lineage.
• Raw data that is not prepared for business intelligence use: Data that is not prepared, cleansed, or optimized is unable to be used for business intelligence purposes, such as analytics and insights.

Until these challenges are addressed, firms are unable to successfully move forward in their digital transformation efforts.

The Solution: PeerNova’s Cuneiform Platform
Providing Continuous Data Quality Monitoring for Successful Digital Transformation

Currently, data quality tools are a dime a dozen. However, not all solutions can successfully support the scale and complexities of today’s digital transformation.

Cuneiform® Data Quality Monitoring is a scalable, zero-code solution that provides data quality monitoring and exception resolution across a firm’s internal and external data sources.

The solution empowers business users to expand their digital transformation efforts, specifically by ensuring end-to-end (E2E) and continuous data quality monitoring.

• Data Quality Automation: Through automation and ongoing data quality checks across the enterprise landscape, the solution not only remedies existing data issues but also continuously manages and monitors data throughout its entire lifecycle.
• Zero-Code: Business users can easily create, configure, and implement a variety of applications and workflows themselves (without IT assistance) through an easy-to-use graphical user interface (GUI).
• Scalability: Currently, digital transformation is moving towards the cloud. PeerNova’s solution allows enterprises to dynamically scale their applications, while amplifying the many benefits of cloud.
• End-to-End Visibility: By unifying the siloed landscape and providing an E2E view across the enterprise, the platform syncs enterprise knowledge and reduces manual efforts for faster root-cause analysis. With increased efficiency and lowered cost, substantial time and money can be refocused on discovering and implementing digital transformation initiatives.
• Business Workflow Lineage: Firms are able to confidently track the lineage of their data and metadata across workflows to ensure data quality and process correctness/

Cuneiform Data Quality Monitoring instills confidence in data by measuring data quality metrics and allowing business users to resolve data quality errors quickly. This enables firms to increase their operational efficiency, improve business performance, and address executive, stakeholder, and regulatory inquiries confidently and promptly. With zero-code, firms can more easily create, configure, and deploy applications at the drop of a hat, accelerating their footprint in the wave of digital transformation.

Data isn’t anything new. Ensuring its quality has been a consistent problem for decades. As companies quickly scale, so does their data. Therefore, monitoring and ensuring end-to-end data quality must be a top priority for businesses of all sizes.

At the end of the day, data quality isn’t just the key to successful digital transformation. It is the key to better operations, compliance, and business decision-making. Experience the Cuneiform Platform for yourself and request a demo today!