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Beyond Paper Policies: Building a Living Data Policy Framework
Data policies serve as the guardrails for how organizations manage their most valuable asset: data. Just as communities establish guidelines for shared community spaces, data policies provide the framework for how teams access, utilize, and govern their collective and shared data resources.  These policies aren’t merely bureaucratic exercises. They establish the rules of engagement for […]


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Author: Subasini Periyakaruppan

A Data Value Manifesto
If you haven’t already heard, a number of organizations have laid off their CDOs and CDO groups and data teams because of a perceived lack of significant or measurable business value. In addition, a recently released report from MIT Sloan delivers some very depressing numbers about the efficacy of CDO groupsi:  The average tenure of […]


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Author: Larry Burns

Living the Ungoverned Life
Organizations often assume they have data governance under control, but in reality, many are simply reacting to data chaos rather than actively managing it. This isn’t due to negligence or a lack of concern — rather, it’s because they don’t recognize that governance is already happening, albeit informally and inconsistently. Every day, employees make critical […]


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Author: Robert S. Seiner

The Serviceberry Mindset: How Nature’s Gift Economy Can Reshape Data Governance
The Death of the Data Silo Is Not the End of the Problem For years, we’ve heard that breaking down data silos is the holy grail of business transformation. We’ve been told that better pipelines, integrated analytics, and AI-driven decision-making will finally unlock the full potential of enterprise data. But here’s the question no one […]


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Author: Christine Haskell

Reimagining Data Preparation for High-Impact Decision-Making
Data often arrives from multiple sources in inconsistent forms, including duplicate entries from CRM systems, incomplete spreadsheet records, and mismatched naming conventions across databases. These issues slow analysis pipelines and demand time-consuming cleanup. Organizations now use machine learning-assisted data preparation to address these challenges, which automatically standardizes formats, detects anomalies, and applies business rules.  Data […]


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Author: Ainsley Lawrence

The Art of Lean Governance: Moving Beyond Governance Buzzwords and Bling
This column will expand on a Systems Thinking approach to Data Governance and focus on process control. The vendors of myriad governance tools focus on metadata, dictionaries, and quality metrics. Their marketing is a sea of buzzwords and bling — bells and whistles. Yet, where is the evidence of adding actual business value, defined as […]


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Author: Steve Zagoudis

Celebrating a Year of Excellence: EDM Council’s Data Excellence Program
The EDM Council’s Data Excellence Program has reached a significant milestone: its first anniversary. The program is proving to be a game-changer in the data management landscape for promoting commitment to best practices and data excellence at the organizational level. Designed to recognize and support organizations dedicated to elevating their data management capabilities, the program […]


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Author: EDM Council

Empowering Data Stewards: Building a Forum That Drives Value
Data steward forums are catalysts for organizational data wisdom and cultural transformation. When executed thoughtfully, they become your strongest asset in building a data-driven organization. However, their success hangs delicately on implementation — the difference between fostering lasting engagement and watching enthusiasm fade lies in the fundamental framework you establish from day one.  1. Building […]


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Author: Subasini Periyakaruppan

The State of Data Governance
In 2024, our research at Dresner Advisory Services revealed that only 32% of organizations have a formal data governance organization in place. This statistic highlights a critical gap, especially as machine learning (ML) and artificial intelligence (AI) are increasingly integrated into operations, expanding business reliance on data and analytic content. Despite the growing importance of […]


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Author: Myles Suer

Data Speaks for Itself: Data Quality Management in the Age of Language Models
Unsurprisingly, my last two columns discussed artificial intelligence (AI), specifically the impact of language models (LMs) on data curation. My August 2024 column, “The Shift from Syntactic to Semantic Data Curation and What It Means for Data Quality,” and my November 2024 column, “Data Validation, the Data Accuracy Imposter or Assistant?” addressed some of the […]


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Author: Dr. John Talburt

Empowering Organizations Through Data Literacy, Governance, and Business Literacy
In my journey as a data management professional, I’ve come to believe that the road to becoming a truly data-centric organization is paved with more than just tools and policies — it’s about creating a culture where data literacy and business literacy thrive.  Data governance, long regarded as a compliance-driven function, is now the backbone […]


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Author: Gopi Maren

Identifying and Addressing Data Overload
Increased data generation requires modern businesses to manage vast volumes of information. All this data holds immense potential for insights and informed decision-making, but its value depends on effective utilization. Without the right tools, frameworks, and strategies, even established companies risk being overwhelmed by data overload.  Let’s take a closer look at data overload and […]


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Author: Irfan Gowani

Data Professional Introspective: Your Organization Can’t Create an EDM Strategy
Some countries successfully create long-term strategic plans. For example, China’s first 100-year plan was aimed at the elimination of extreme poverty by 2020. In 1980, there were 540M people living in extreme poverty; by 2014, there were only 80 million. The second 100-year plan, targeted for 2050, calls for achieving 30% of global GDP, to […]


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Author: Melanie Mecca

The 7 Fundamentals That Are Crucial for CDO Success in 2025

As data volumes continue to rapidly grow and organizations become increasingly data driven in the AI age, the data landscape of 2025 is poised to be more dynamic and complex than ever before.

For businesses to excel in this fast-evolving environment, chief data officers (CDOs) of the future must move beyond their traditional roles to become strategic transformation leaders. Key priorities will shape their agenda and be a driving force for success in an era of sweeping change.

The eBook “Seven Chief Data Officer (CDO) Priorities for 2025,” explores seven key priorities that will define successful data leadership in 2025. From crafting unified data strategies that feel less like governance manifestos and more like business transformation blueprints, to preparing trusted data for the AI revolution, you will learn:

  1. What tomorrow’s successful CDOs look like.
  2. The seven fundamentals that are crucial for CDO success.
  3. Practical strategies for data management in 2025.

Expanding from Data Custodian to Strategic Visionary

The role of the CDO has undergone a significant change over the last few years—and it’s continuing to be redefined as CDOs prove their value. CDOs are now unlocking competitive advantages by implementing and optimizing comprehensive data initiatives. That’s part of the reason why organizations with a dedicated CDO are better equipped to handle the complexities of modern data ecosystems and maintain a competitive edge than those without this role.

As noted in our eBook “Seven Chief Data Officer (CDO) Priorities for 2025,” this critical position will become even more strategic. The role will highlight a distinct difference between good companies that use data and great companies that rely on data to drive every business decision, accelerate growth, and confidently embrace whatever is next.

The idea for this eBook began with a simple observation: The role of CDO has become a sort of organizational Rorschach test. Ask 10 executives what a CDO should do, and you’ll get 11 different answers, three strategic frameworks, and at least one person insisting it’s all about AI (it’s not).

While researching this piece, a fascinating pattern emerged. Data strategy isn’t just about governance and quality metrics, but about fundamental business transformation. But perhaps most intriguing is the transformation of the CDO role itself. What started as a data custodian and governance guru has morphed into something far more nuanced: Part strategist, part innovator, part ethicist, and increasingly, part business transformer.

The eBook dives deeper into these themes, offering insights and frameworks for navigating this evolution. But more than that, it attempts to capture this moment of transformation–where data leadership is becoming something new and, potentially, revolutionary.

The seven priorities outlined in the eBook aren’t just predictions; they’re emerging patterns. When McKinsey tells us that 72% of organizations struggle with managing data for AI use cases, they’re really telling us something profound about the gap between our technological ambitions and our organizational readiness. We’re all trying to build the plane while flying it–and some of us are still debating whether we need wings.

This eBook is for leaders who find themselves at this fascinating intersection of technology, strategy, and organizational change. Whether you’re a CDO looking to validate your roadmap, or an executive trying to understand why your data initiatives feel like pushing boulders uphill, we hope you’ll find something here that makes you think differently about the journey ahead.

Download the eBook if you’re curious about what data leadership looks like when we stop treating it like a technical function and start seeing it as a strategic imperative.

The post The 7 Fundamentals That Are Crucial for CDO Success in 2025 appeared first on Actian.


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Author: Dee Radh

The Data-Centric Revolution: Putting Knowledge Into Our Knowledge Graphs
I recently gave a presentation called “Knowledge Management and Knowledge Graphs” at a KMWorld conference, and a new picture of the relationship between knowledge management and knowledge graphs gradually came into focus. I recognized that the knowledge graph community has gotten quite good at organizing and harmonizing data and information, but there is little knowledge […]


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Author: Dave McComb

Accelerating Innovation: Data Discovery in Manufacturing

The manufacturing industry is in the midst of a digital revolution. You’ve probably heard these buzzwords: Industry 4.0, IoT, AI, and machine learning– all terms that promise to revolutionize everything from assembly lines to customer service. Embracing this digital transformation is key in improving your competitive advantage, but new technology doesn’t come without its own challenges. Each new piece of technology needs one thing to deliver innovation: data.

Data is the fuel powering your tech engines. Without the ability to understand where your data is, whether it’s trustworthy, or who owns the datasets, even the most powerful tools can overcomplicate and confuse the best data teams. That’s where modern data discovery solutions come in. They’re like the backstage crew making sure everything runs smoothly– connecting systems, tidying up the data mess, and making sure everyone has exactly what they need, when they need it. That means faster insights, streamlined operations, and a lower total cost of ownership (TCO). In other words, data access is the key to staying ahead in today’s fast-paced, highly competitive, increasingly sensitive manufacturing market. 

The Problem

Data from all aspects of your business is siloed– whether it’s coming from sensors, legacy systems, cloud applications, suppliers or customers– trying to piece it all together is daunting, time-consuming, and just plain hard. Traditional methods are slow, cumbersome, and definitely not built for today’s needs. This fragmented approach not only slows down decision-making, but keeps you from tapping into valuable insights that could drive innovation. And in a market where speed is everything, that’s a recipe for falling behind. 

So the big question is: how can you unlock the true potential of your data?

The Solution

So how do you make data intelligence into a streamlined, efficient process? The answer lies in modern data discovery solutions– the unsung catalyst of a digital transformation motion. Rather than simply integrating data sources, data discovery solutions excel in metadata management, offering complete visibility into your company’s data ecosystem. They enable users– regardless of skill level– to locate where data resides and assess the quality and relevance of the information. By providing this detailed understanding of data context and lineage, organizations can confidently leverage accurate, trustworthy datasets, paving the way for informed decision-making and innovation, 

Key Components

Easy-to-Connect Data Sources for Metadata Management

 One of the biggest hurdles in data integration is connecting to a variety of data sources, including legacy systems, cloud applications, and IoT devices. Modern data discovery tools like Zeenea offer easy connectivity, allowing you to extract metadata from various sources seamlessly. This unified view eliminates silos and enables faster, more informed decision-making across the organization.

Advanced Metadata Management

Metadata is the backbone of effective data discovery. Advanced metadata management capabilities ensure that data is well-organized, tagged, and easily searchable. This provides a clear context for data assets, helping you understand the origin, quality, and relevance of your data. This means better data search and discoverability.

Data Discovery Knowledge Graph

A data discovery knowledge graph serves as an intelligent map of your metadata, illustrating the intricate relationship and connections between data assets. It provides users with a comprehensive view of how data points are linked across systems, offering a clear picture of data lineage– from origin to current state. The visibility into the data journey is invaluable in manufacturing, where understanding the flow of information between production data, supply chain metrics, and customer feedback is critical. By tracing the lineage of data, you can quickly assess its accuracy, relevance, and context, leading to more precise insights and informed decision-making.

Quick Access to Quality Data Through Data Marketplace

A data marketplace provides a centralized hub where you can easily search, discover, and access high-quality data. This self-service model empowers your teams to find the information they need without relying on IT, accelerating time to insight. The result? Faster product development cycles, improved process efficiency, and enhanced decision-making capabilities.

User-Friendly Interface With Natural Language Search

Modern data discovery platforms prioritize user experience with intuitive, user-friendly interfaces. Features like natural language search allow users to query data using everyday language, making it easier for non-technical users to find what they need. This democratizes access to data across the organization, fostering a culture of data-driven decision-making.

Low Total Cost of Ownership (TCO)

Traditional metadata management solutions often come with a hefty price tag due to high infrastructure costs and ongoing maintenance. In contrast, modern data discovery tools are designed to minimize TCO with automated features, cloud-based deployment, and reduced need for manual intervention. This means more efficient operations and a greater return on investment.

Benefits

By leveraging a comprehensive data discovery solution, manufacturers can achieve several key benefits:

Enhanced Innovation

With quick access to quality data, teams can identify trends and insights that drive product development and process optimization.

Faster Time to Market

Automated implementation and seamless data connectivity reduce the time required to gather and analyze data, enabling faster decision-making.

Improved Operational Efficiency

Advanced metadata management and knowledge graphs help streamline data governance, ensuring that users have access to reliable, high-quality data.

Increased Competitiveness

A user-friendly data marketplace democratizes data access, empowering teams to make data-driven decisions and stay ahead of industry trends.

Cost Savings

With low TCO and reduced dependency on manual processes, manufacturers can maximize their resources and allocate budgets towards strategic initiatives.

Data is more than just a resource—it’s a catalyst for innovation. By embracing advanced metadata management and data discovery solutions, you can find, trust, and access data. This not only accelerates time to market but also drives operational efficiency and boosts competitiveness. With powerful features like API-led automation, a data discovery knowledge graph, and an intuitive data marketplace, you’ll be well-equipped to navigate the challenges of Industry 4.0 and beyond.

Call to Action

Ready to accelerate your innovation journey? Explore how Actian Zeenea can transform your manufacturing processes and give you a competitive edge.

Learn more about how our advanced data discovery solutions can help you unlock the full potential of your data. Sign up for a live product demo and Q&A. 

 

The post Accelerating Innovation: Data Discovery in Manufacturing appeared first on Actian.


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Author: Kasey Nolan

Mind the Gap: Architecting Santa’s List – The Naughty-Nice Database


You never know what’s going to happen when you click on a LinkedIn job posting button. I’m always on the lookout for interesting and impactful projects, and one in particular caught my attention: “Far North Enterprises, a global fabrication and distribution establishment, is looking to modernize a very old data environment.” I clicked the button […]

The post Mind the Gap: Architecting Santa’s List – The Naughty-Nice Database appeared first on DATAVERSITY.


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Author: Mark Cooper

From Silos to Synergy: Data Discovery for Manufacturing

Introduction

There is an urgent reality that many manufacturing leaders are facing, and that’s data silos. Valuable information remains locked within departmental systems, hindering your ability to make strategic, well-informed decisions. A data catalog and enterprise data marketplace solution provides a comprehensive, integrated view of your organization’s data, breaking down silos and enabling true collaboration. 

The Problem: Data Silos Impede Visibility

In your organization, each department maintains its own critical datasets– finance compiles detailed financial reports, sales leverages CRM data, marketing analyzes campaign performance, and operations tracks supply chain metrics. But here’s the challenge: how confident are you that you even know what data is available, who owns it, or if it’s quality?

The issue goes beyond traditional data silos. It’s not just that the data is isolated– it’s that your teams are unaware of what data even exists. This lack of visibility creates a blind spot. Without a clear understanding of your company’s data landscape, you face inefficiencies, inconsistent analysis, and missed opportunities. Departments and up duplicating work, using outdated or unreliable data, and making decisions based on incomplete information.

The absence of a unified approach to data discovery and cataloging means that even if the data is technically accessible, it remains hidden in plain sight, trapped in disparate systems without any context or clarity. Without a comprehensive search engine for your data, your organization will struggle to:

  • Identify data sources: You can’t leverage data if you don’t know it exists. Without visibility into all available datasets, valuable information often remains unused, limiting your ability to make fully informed decisions.
  • Access data quality: Even when you find the data, how do you know it’s accurate and up-to-date? Lack of metadata means you can’t evaluate the quality or relevance of the information, leading to analysis based on faulty data.
  • Understand data ownership: when it’s unclear who owns or manages specific datasets, you waste time tracking down information and validating its source. This confusion slows down projects and introduces unnecessary friction. 

The Solution

Now, imagine the transformative potential if your team could search for and discover all available data across your organization as easily as using a search engine. Implementing a robust metadata management strategy—including data lineage, discovery, and cataloging—bridges the gaps between disparate datasets, enabling you to understand what data exists, its quality, and how it can be used. Instead of chasing down reports or sifting through isolated systems, your teams gain an integrated view of your company’s data assets.

  • Data Lineage provides a clear map of how data flows through your systems, from its origin to its current state. It allows you to trace the journey of your data, ensuring you know where it came from, how it’s been transformed, and if it can be trusted. This transparency is crucial for verifying data quality and making accurate, data-driven decisions.
  • Data Discovery enables teams to quickly search through your company’s data landscape, finding relevant datasets without needing to know the specific source system. It’s like having a powerful search tool that surfaces all available data, complete with context about its quality and ownership, helping your team unlock valuable insights faster.
  • A Comprehensive Data Catalog serves as a central hub for all your metadata, documenting information about the datasets, their context, quality, and relationships. It acts as a single source of truth, making it easy for any team member to understand what data is available, who owns it, and how it can be used effectively.

Revolutionizing Your Operations With Metadata Management

This approach can transform the way each department operates, fostering a culture of informed decision-making and reducing inefficiencies:

  • Finance gains immediate visibility into relevant sales data, customer demand forecasts, and historical trends, allowing for more accurate budgeting and financial planning. With data lineage, your finance team can verify the source and integrity of financial metrics, ensuring compliance and minimizing risks.
  • Sales can easily search for and access up-to-date product data, customer insights, and market analysis, all without needing to navigate complex systems. A comprehensive data catalog simplifies the process of finding the most relevant datasets, enabling your sales team to tailor their pitches and close deals faster.
  • Marketing benefits from an integrated view of customer behavior, campaign performance, and product success. Using data discovery, your marketing team can identify the most impactful campaigns and refine strategies based on real-time feedback, driving greater engagement and ROI.
  • Supply Chain Leaders can trace inventory data back to its origin, gaining full visibility into shipments, supplier performance, and potential disruptions. With data lineage, they understand the data’s history and quality, allowing for proactive adjustments and optimized procurement.
  • Manufacturing Managers have access to a clear, unified view of production data, demand forecasts, and operational metrics. The data catalog offers a streamlined way to integrate insights from across the company, enabling better decision-making in scheduling, resource allocation, and quality management.
  • Operations gains a comprehensive understanding of the entire production workflow, from raw materials to delivery. Data discovery and lineage provide the necessary context for making quick adjustments, ensuring seamless production and minimizing delays.

This strategy isn’t about collecting more data—it’s about creating a clearer, more reliable picture of your entire business. By investing in a data catalog, you turn fragmented insights into a cohesive, navigable map that guides your strategic decisions with clarity and confidence. It’s the difference between flying blind and having a comprehensive navigation system that leads you directly to success.

The Benefits: From Fragmentation to Unified Insight

When you prioritize data intelligence with a catalog as a cornerstone, your organization gains access to a powerful suite of benefits:

  1. Enhanced Decision-Making: With a unified view of all data sources, your team can make well-informed decisions based on real-time insights. Data lineage allows you to trace back the origin of key metrics, ensuring the accuracy and reliability of your analysis.
  2. Improved Collaboration Across Teams: With centralized metadata and clear data relationships, every department has access to the same information, reducing silos and fostering a culture of collaboration.
  3. Greater Efficiency and Reduced Redundancies: By eliminating duplicate efforts and streamlining data access, your teams can focus on strategic initiatives rather than time-consuming data searches.
  4. Proactive Risk Management: Full visibility into data flow and origins enables you to identify potential issues before they escalate, minimizing disruptions and maintaining smooth operations.
  5. Increased Compliance and Data Governance: Data lineage provides a transparent trail for auditing purposes, ensuring your organization meets regulatory requirements and maintains data integrity.

Conclusion

Data silos are more than just an operational inconvenience—they are a barrier to your company’s growth and innovation. By embracing data cataloging, lineage, and governance, you empower your teams to collaborate seamlessly, leverage accurate insights, and make strategic decisions with confidence. It is time to break down the barriers, integrate your metadata, and unlock the full potential of your organization’s data.

Call to Action

Are you ready to eliminate data silos and gain a unified view of your operations? Discover the power of metadata management with our comprehensive platform. Visit our website today to learn more and sign up for a live product demo and Q&A.

The post From Silos to Synergy: Data Discovery for Manufacturing appeared first on Actian.


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Author: Kasey Nolan

5 Data Management Tool and Technology Trends to Watch in 2025


The market surrounding data management tools and technologies is quite mature. After all, the typical business has been making extensive use of data to help streamline its operations and decision-making for years, and many companies have long had data management tools in place. But that doesn’t mean that little is happening in the world of […]

The post 5 Data Management Tool and Technology Trends to Watch in 2025 appeared first on DATAVERSITY.


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Author: Matheus Dellagnelo

How to Foster a Cross-Organizational Approach to Data Initiatives


In today’s business landscape, data reigns supreme. It is the cornerstone of effective decision-making, fuels innovation, and drives organizational success. However, despite its immense potential, many organizations struggle to harness the full power of their data due to a fundamental disconnect between IT and business teams. This division not only impedes progress but also undermines […]

The post How to Foster a Cross-Organizational Approach to Data Initiatives appeared first on DATAVERSITY.


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Author: Abhas Ricky

5 Reasons to Invest in a Next-Gen Data Catalog

Organizations across every vertical face numerous challenges managing their data effectively and with full transparency. That’s at least partially due to data often being siloed across multiple systems or departments, making it difficult for employees to find, trust, and unlock the value of their company’s data assets.

Enter the Actian Zeenea Data Discovery Platform. This data intelligence solution is designed to address data issues by empowering everyone in an organization to easily find and trust the data they need to drive better decision-making, streamline operations, and ensure compliance with regulatory standards.

The Zeenea platform serves as a centralized data catalog and an enterprise data marketplace. By improving data visibility, access, and governance, it provides a scalable and efficient framework for businesses to leverage their data assets. The powerful platform helps organizations explore new and sustainable use cases, including these five:

1. Overcome Data Silo and Complexity Challenges

Data professionals are well familiar with the struggles of working in environments where data is fragmented across departments and systems. This leads to data silos that restrict access to critical information, which ends up creating barriers to fully optimizing data.

Another downside to having barriers to data accessibility is that users spend significant time locating data instead of analyzing it, resulting in inefficiencies across business processes. The Zeenea platform addresses accessibility issues by providing a centralized, searchable repository of all data assets.

The repository is enriched with metadata—such as data definitions, ownership, and quality metrics—that gives context and meaning to the organization’s data. Both technical and non-technical users can quickly find and understand the data they need, either by searching for specific terms, filtering by criteria, or through personalized recommendations. This allows anyone who needs data to quickly and easily find what they need without requiring IT skills or relying on another team for assistance.

For example, marketing analysts looking for customer segmentation data for a new campaign can quickly locate relevant datasets in the Zeenea platform. Whether analysts know exactly what they’re searching for or are browsing through the data catalog, the platform provides insights into each dataset’s source, quality, and usage history.

Based on this information, analysts can decide whether to request access to the actual data or consult the data owner to fix any quality issues. This speeds up the data usage process and ensures that decision-makers have access to the best available data relevant for the campaign.

2. Solve the Issue of Limited Data Access for Business Users

In many organizations, data access is often limited to technical teams such as IT or data engineering. Being dependent on specialty or advanced skills creates bottlenecks because business users must request data from other teams. This reliance on IT or engineering departments leads to delayed insights and increases the workload on technical teams that may already be stretched thin.

The Zeenea platform helps by democratizing data access by enabling non-technical users to explore and “shop” for data in a self-service environment. With Zeenea’s Enterprise Data Marketplace, business users can easily discover, request, and use data that has been curated and approved by data governance teams. This self-service model reduces the reliance on IT and data specialists, empowering all employees across the organization to make faster, data-driven decisions.

Barrier-free data access can help all users and departments. For instance, sales managers preparing for a strategy meeting can use the Enterprise Data Marketplace to access customer reports and visualizations—without needing to involve the data engineering team.

By using the Zeenea platform, sales managers can pull data from various departments, such as finance, sales, or marketing, to create a comprehensive view of customer behavior. This allows the managers to identify opportunities for improved engagement as well as cross-sell and upsell opportunities.

3. Gain Visibility Into Data Origins and Compliance Requirements

As organizations strive to meet stringent and regulatory requirements that seem to be constantly changing, having visibility into both data origins and data transformations becomes essential. Understanding how data has been sourced, modified, and managed is crucial for compliance and auditing processes. However, without proper tracking systems, tracing this information accurately can be extremely difficult.

This is another area where the Zeenea platform can help. It provides detailed data lineage tracking, allowing users to trace the entire lifecycle of a dataset. From data’s origin to its transformation and usage, the platform offers a visual map of data flows, making it easier to troubleshoot errors, detect anomalies, and verify the accuracy of reports.

With this capability, organizations can present clear audit trails to demonstrate compliance with regulatory standards. A common use case is in the financial sector. A bank facing a regulatory audit can leverage Zeenea’s data lineage feature to show auditors exactly how financial data has been handled.

By comprehensively tracing each dataset, the bank can easily demonstrate compliance with industry regulations. Plus, having visibility into data reduces the complexity of the audit process and builds trust in data management practices.

4. Provide Ongoing Data Governance

Managing data governance in compliance with internal policies and external regulations is another top priority for organizations. With laws such as GDPR and HIPAA that have strict penalties, companies must ensure that sensitive data is handled securely and data usage is properly tracked.

The Zeenea platform delivers capabilities to meet this challenge head-on. It enables organizations to define and enforce governance rules across their data assets, ensuring that sensitive information is securely managed. Audit trail, access control, and data lineage features help organizations comply with regulatory requirements. These features also play a key role in ensuring data is properly cataloged and monitored.

Organizations in industries like healthcare that handle highly sensitive information can benefit from the Zeenea platform. The platform can help companies, like those in healthcare, manage access controls, encryption, and data monitoring. This ensures compliance with HIPAA and other regulations while safeguarding patient privacy. Additionally, the platform streamlines internal governance practices, ensuring that all data users follow established guidelines for data security.

5. Build a Data-Driven Organization

The Actian Zeenea Data Discovery Platform offers a comprehensive solution to solve modern data management challenges. By improving data discovery, governance, and access, the Zeenea platform removes barriers to data usage, making it easier for organizations to unlock the full value of their data assets.

Whether it’s giving business users self-service capabilities, streamlining compliance efforts, or supporting a data mesh approach that decentralizes data management, the platform gives individual departments the ability to manage their own data while maintaining organization-wide visibility. Additionally, the platform provides the tools and infrastructure needed to thrive in today’s data-driven world.

Experience a Live Demo

Organizations looking to improve their data outcomes should consider the Zeenea platform. By creating a single source of truth for data across the enterprise, the solution enables faster insights, smarter decisions, and stronger compliance—all key drivers of business success in the digital age. Find out more by joining a live product demo.

The post 5 Reasons to Invest in a Next-Gen Data Catalog appeared first on Actian.


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Author: Dee Radh

Data Speaks for Itself: Data Validation – Data Accuracy Imposter or Assistant?
In my last article, “The Shift from Syntactic to Semantic Data Curation and What It Means for Data Quality” published in the August 2024 issue of this newsletter, I argued how the adoption of generative AI will change the focus and scope of data quality management (DQM). Because data quality is measured in the degree […]


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Author: Dr. John Talburt

Data Errors in Financial Services: Addressing the Real Cost of Poor Data Quality
Data quality issues continue to plague financial services organizations, resulting in costly fines, operational inefficiencies, and damage to reputations. Even industry leaders like Charles Schwab and Citibank have been severely impacted by poor data management, revealing the urgent need for more effective data quality processes across the sector.  Key Examples of Data Quality Failures  — […]


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Author: Angsuman Dutta

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