As organisations invest in data analytics, ensuring data quality has become a key concern highlighted in recent findings by Collibra.
As businesses increasingly rely on data to shape their strategies, ensuring data quality has surfaced as a pivotal concern. A recent study cited by Collibra, a data governance platform, reveals that while 88% of companies prioritise investments in data and analytics, only 37% report success in their efforts to enhance data quality.
In response to these findings, Collibra hosted a webinar to discuss essential trends and strategies that organisations should adopt to fortify their data quality by 2025. The session outlined five critical trends expected to shape the data landscape in the upcoming year:
1. Accurate AI and Analytics
Experts emphasised the necessity for organizations to proactively identify potential data quality issues before they escalate into significant business challenges. This assurance of reliable data is vital for both established machine learning models and innovative AI technologies, such as generative AI. Key strategies include profiling data to detect issues like missing values and outliers, which can distort models, as well as identifying hidden anomalies in data pipelines. Notifications regarding data quality problems should be accelerated to ensure timely responses, and seamless integration with data science workflows is crucial for operational efficiency.
2. Quality in Data Products
As the emphasis on data products intensifies, ensuring their data quality is paramount. A recommended best practice involves pinpointing vital business entities—such as customers and products—that contribute foundational data for these products. Organisations are encouraged to leverage tools for automatically tagging sensitive data and linking governance policies to ensure proper handling. Collibra’s capabilities in documenting data transformations provide transparency for auditors, allowing verification of compliance with established business rules.
3. Audit-Ready Reporting
The need for organisations to establish broad connectivity with diverse data sources and file types will persist in 2025. A centralised approach to data classification, alongside automated data quality checks, will contribute to consistency and reliability across reports. The webinar highlighted that Collibra’s rule writer solution can assist users lacking SQL knowledge in creating custom rules, thereby enhancing visibility and automated controls necessary for regulatory compliance.
4. Data Quality During Cloud Migration
Ensuring data quality during migrations to cloud environments emerged as a critical focus, particularly for businesses transitioning from legacy SAP systems to SAP S/4HANA. Addressing data quality before and during cloud migrations can significantly assist organisations to manage cloud expenditure more effectively. By maintaining data integrity throughout the process, companies can mitigate potential migration errors and avoid unexpected costs associated with cloud storage and processing.
5. Holistic Governance
The webinar concluded with a discussion on the benefits of a holistic governance platform, which could unify various aspects of data management. This platform would offer centralised management, policy enforcement, and integrated data quality alongside collaborative governance, thus eliminating the inefficiencies associated with siloed tools.
According to SAPinsider research, data quality ranks as the most critical element influencing data governance and quality strategies among SAP users, accounting for 35% of strategic focus. The study advises that plans for data governance should be integral to any future data, integration, and platform strategies.
As the influence of AI expands within the business realm, the importance of ensuring robust data quality across organisations is becoming increasingly apparent. In response to this momentum, Collibra recently unveiled its EU AI Act Assessment Tool, aimed at enhancing compliance efforts and fostering responsible AI deployment while bolstering internal trust. This development indicates a growing recognition of the indispensable role of data quality in harnessing the full potential of emerging technologies.
Source: Noah Wire Services
- https://www.collibra.com/us/en/use-cases/solution/enterprise-wide-data-quality – This URL supports the claim about Collibra’s role in data governance and quality, highlighting its capabilities in monitoring data quality and detecting anomalies.
- https://www.collibra.com/us/en/blog/q4-2023-collibra-release-helping-customers-reduce-data-risks-and-improve-productivity – This article discusses Collibra’s efforts to improve data quality and security, aligning with the trends outlined in the webinar.
- https://www.collibra.com/us/en/blog/collibra-a-leader-in-the-forrester-wave-data-governance-solutions-q3-2023 – This blog post highlights Collibra’s leadership in data governance, emphasizing its strong policy management and stewardship capabilities.
- https://www.sapinsideronline.com/ – SAPinsider research is mentioned as emphasizing data quality’s critical role in data governance strategies among SAP users.
- https://www.collibra.com/us/en/products/data-intelligence-cloud – This page provides information on Collibra’s Data Intelligence Cloud, which supports holistic data governance and quality management.
- https://www.collibra.com/us/en/products/data-quality – This URL supports Collibra’s focus on data quality, including tools for profiling and anomaly detection.
- https://www.collibra.com/us/en/products/data-governance – This page explains Collibra’s data governance solutions, which are integral to ensuring data quality across organizations.
- https://www.collibra.com/us/en/blog/eu-ai-act-assessment-tool – This blog post discusses Collibra’s EU AI Act Assessment Tool, highlighting its role in enhancing AI compliance and data quality.
- https://www.collibra.com/us/en/products/data-quality-pushdown – This URL supports Collibra’s Data Quality Pushdown feature, which improves efficiency in processing large datasets.
- https://www.collibra.com/us/en/products/resident-enterprise-architect – This page provides details on Collibra’s Resident Enterprise Architect program, which aids in implementing data governance strategies.
- https://www.collibra.com/us/en/products/dashboard-ux-accelerators – This URL discusses Collibra’s Dashboard UX accelerators, which help in creating personalized experiences for data governance and quality monitoring.
Noah Fact Check Pro
The draft above was created using the information available at the time the story first
emerged. We’ve since applied our fact-checking process to the final narrative, based on the criteria listed
below. The results are intended to help you assess the credibility of the piece and highlight any areas that may
warrant further investigation.
Freshness check
Score:
8
Notes:
The narrative references trends expected for 2025, indicating it is relatively recent. However, there is no specific mention of recent events or updates that would confirm its absolute freshness.
Quotes check
Score:
10
Notes:
There are no direct quotes in the narrative, so there is no risk of recycled or misattributed quotes.
Source reliability
Score:
7
Notes:
The narrative originates from SAPinsider, which is a known platform focused on SAP-related content. However, it may have a specific audience focus and could be influenced by its association with SAP.
Plausability check
Score:
9
Notes:
The trends discussed align with current industry concerns about data quality and AI integration. The narrative seems plausible and consistent with expected developments in the field.
Overall assessment
Verdict (FAIL, OPEN, PASS): PASS
Confidence (LOW, MEDIUM, HIGH): HIGH
Summary:
The narrative appears to be recent and relevant to current trends in data quality and AI. It lacks direct quotes, which eliminates the risk of misattribution. While the source is focused on SAP-related content, the information seems plausible and aligns with industry expectations.
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