Search for:
Customer Data Breaches


In 2023, data breaches surged significantly, with a 20% increase from the previous year, compromising over 5 billion records. This rise is largely attributed to cloud misconfigurations, which account for over 80% of breaches, and the growing prevalence of ransomware attacks, which intensified by 50% in the first half of the year. The average ransom payment escalated dramatically, indicating that these attacks are becoming both more frequent and financially burdensome.

Cybercriminals are employing increasingly sophisticated tactics. Phishing schemes and stolen credentials remain common entry points for attacks. Additionally, application-layer attacks have surged by 80%, exposing vulnerabilities in web applications critical to business operations. The financial impact of these breaches is substantial, with the average cost per breach reaching approximately $4.5 million.

Customer data is a prime target for theft due to its sensitive nature and high value. This data often includes personal identifiable information (PII) such as names, addresses, and financial details. Insider threats also pose significant risks, contributing to about 43% of data loss incidents.

To combat these threats, organisations should adopt a comprehensive cybersecurity strategy. This includes implementing multi-factor authentication, developing incident response plans, conducting regular security audits, and investing in employee training on cybersecurity awareness.

Engaging with law enforcement and utilising advanced security technologies can further enhance protection against data breaches.
Pretectum CMDM offers solutions to enhance customer data management while addressing privacy concerns. It provides a single customer view by integrating data from various sources, enabling businesses to tailor their services effectively.

The platform also features blockchain technology for secure data management, ensuring integrity and compliance through an immutable ledger that tracks all changes to customer information.

For businesses looking to safeguard their customer data and improve their cybersecurity posture, adopting these measures is essential in today’s evolving threat landscape.

Read more at https://www.pretectum.com/customer-data-breaches-how-they-happen/

Customer Master Data and the Informed Decision


Pretectum’s Customer Master Data Management (CMDM) system is a comprehensive solution designed to centralize and standardize customer data across various organizational departments and systems. This approach enables businesses to maintain a Single Customer View (SCV), which is critical for informed decision-making and enhancing customer interactions.

Overview
Pretectum CMDM acts as a SaaS-based centralized repository for customer data, integrating information from multiple sources to provide a holistic view of each customer. This integration facilitates improved organizational decision-making, marketing strategies, and personalized customer experiences by ensuring that all departments access the same up-to-date and reliable information.

Key Features
Single Source of Truth (SSoT): Pretectum CMDM establishes a unified database that minimizes discrepancies in customer profiles, ensuring consistency across sales, marketing, and support functions.

Golden Record Management: The system creates a "golden nominal" record for each customer, consolidating all relevant data into a single authoritative source. This enhances operational efficiency and enables deeper customer engagement.

Real-time Data Synchronization: Customer data is continuously updated across all systems, which supports timely and informed decision-making.

Robust Data Governance: Pretectum CMDM maintains high data quality while complying with security and privacy regulations, which is essential for effective management of customer information.

Benefits of Using Pretectum CMDM
Enhanced Customer Experience: By leveraging accurate and comprehensive customer data, businesses can tailor their marketing campaigns and improve service interactions, leading to greater customer satisfaction and loyalty.

Operational Efficiency: The system reduces data redundancies and streamlines processes by maintaining clean and consistent customer profiles, which optimizes resource allocation.

Compliance Assurance: Pretectum CMDM helps organizations adhere to various data protection regulations (like GDPR and CCPA), safeguarding sensitive information while maintaining customer trust.

Data Integration Capabilities: The platform seamlessly integrates with other systems (like CRMs and ERPs), ensuring synchronized updates across platforms for better data analysis and strategic decision-making.

Pretectum’s CMDM system not only centralizes customer data but also enhances the overall capability of organizations to manage their customer relationships effectively. By providing a reliable framework for data management, it supports informed decision-making that can lead to improved business outcomes.
Learn more at www.pretectum.com

Our Digital Dataome – we are our data

The concept of the dataome refers to the vast array of non-genetic information that humans generate and carry, both internally and externally.

This includes everything from digital data to cultural artifacts, and it plays a crucial role in shaping our identity and interactions. This includes commercial, social, economic, medical, educational, and civic profiles. Understanding how this data is managed is crucial for us both as consumers and for the organizations that might consider leveraging that data to forge long lasting mutually-beneficial relationships. #LoyaltyIsUpForGrabs

  • The term “dataome” is analogous to “genome,” representing the complete set of data that individuals or societies generate. This includes everything from social media posts and digital communications to scientific research and cultural artifacts.

Customer Master Data Management (MDM)

Customer Master Data Management (CMDM) is a systematic approach to managing customer data across a given organization. CMDM drives toward ensuring that all customer-related information is accurate, consistent, and accessible, creating a unified view of each customer. This process is essential for leveraging consumer data effectively and involves several key components:

  1. Unique Identifiers: Establishing persistent IDs that link customer records across different systems ensures a cohesive view of the customer.
  2. Data Integration: Integrating customer data from various sources helps maintain accuracy and consistency. This integration allows organizations to have real-time updates on customer interactions and preferences.
  3. Data Governance: Implementing robust data governance processes ensures that customer data remains accurate and compliant with regulations. This includes defining roles for data management, establishing quality standards, and maintaining security protocols.
  4. Self-Service Capabilities: Allowing consumers to manage their own data through self-service portals empowers them to keep their information current, enhancing the overall quality of the data collected.

The Digital Dataome

The dataome encompasses all forms of information that we as humans have externalized throughout history, starting from ancient cave paintings to modern digital communications. In aggregate, it represents a living system that is intricately linked to human existence, much like the microbiome, which consists of microorganisms living within us. This relationship is symbiotic; while we create and propagate the dataome, it also influences our behaviors, thoughts, and societal structures.

The concept of a Digital Dataome emphasizes the idea that we are fundamentally intertwined with the vast amounts of data we generate and interact with in our digital lives. This notion extends beyond mere data collection; it encapsulates how our identities, behaviors, and societal structures are shaped by this information.

As a consumer, your dataome comprises all the information related to your interactions across various life domains:

Characteristics of our Digital Dataome

  • Interconnectedness: digital dataomes have a symbiotic relationship between humans and technology. Just as microbiomes influence health, the dataome affects our social interactions and decision-making processes.
  • Exponential Growth: The volumes of data we generate daily is staggering—it is estimated at over 2,000 exabytes per year. This rapid accumulation surpasses all spoken words by humanity throughout history.
  • Dependency: Our reliance on this digital information system is profound; shaping our understanding of the world and informing our actions and those of others. We depend on the dataome for communication, learning, and even survival strategies in our increasingly complex society.
Digital DataOme
(c) 2024 Pretectum.com

Implications of our Digital Dataome

Recognizing ourselves as part of some digital dataome carries some significant implications for how we think about our daily choices. Every day we are challenged to opt-in/out of one thing or another, we receive unsolicited communiques from brands we have never heard of.

We view weird and wonderful targeted ads that seem to simply “know what we are thinking”. For many of us, there is a feeling of hopeless about our ability to control the data that we have out there. And then there are the data breaches, we may never hear about some of them but we don’t really know how they happen or what their implications are for us individually.

  • Identity Formation: Our digital footprints contribute to our identities. The way we present ourselves online can influence how we perceive ourselves and how others perceive us.
  • Social Dynamics: The interactions within the Digital Dataome can lead to shifts in cultural norms and values. Information dissemination can amplify voices or create echo chambers that affect public opinion.
  • Sustainability Concerns: As the dataome expands, so does its energy consumption. Projections suggest that energy demands for maintaining this digital ecosystem could rival total global energy production in the coming decades, so right there we even have a greater concern around the implications of all the data related to us, consuming energy seemingly pointlessly.

Importance of Managing Your Dataome

For organizations, effective management of your personal Dataome through CMDM practice is important. Not all organizations offer consumers the ability to manage their personal digital dataome, but Pretectum CMDM does.

Being able to curate content about yourself, offers several advantages to you as a consumer, and to organizations too.

  • Enhanced Personalization: Organizations that offer this capability can more precisely tailor their services based on a comprehensive understanding of your preferences and behaviors.
  • Improved Decision-Making: Access to accurate and timely data in various engagements will allow organizations to make better informed decisions that benefit both them and the consumer.
  • Increased Trust: Transparent management of personal data fosters improved trust between consumers and organizations by ensuring compliance with privacy regulations.

By understanding the significance of your dataome and how it is managed through CMDM practices, you can better navigate our complex digital landscape all the while ensuring that your personal information is utilized ethically and effectively, because you have the control and Pretectum CMDM powers it.

Beyond Ownership: Scaling AI with Optimized First-Party Data


Brands, publishers, MarTech vendors, and beyond recently gathered in NYC for Advertising Week and swapped ideas on the future of marketing and advertising. The overarching message from many brands was one we’ve heard before: First-party data is like gold, especially for personalization. But it takes more than “owning” the data to make it valuable. Scale and accuracy […]

The post Beyond Ownership: Scaling AI with Optimized First-Party Data appeared first on DATAVERSITY.


Read More
Author: Tara DeZao

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.


Read More
Author: Kasey Nolan

Ask a Data Ethicist: How Can You Learn More About Data and AI Ethics?


It was about this time last year that I pitched the team at DATAVERSITY the idea of this monthly column on data ethics. There’s certainly been no shortage of interesting questions to cover and I’ve enjoyed writing about both the practical and more philosophical aspects of this topic. As we wrap up this year and […]

The post Ask a Data Ethicist: How Can You Learn More About Data and AI Ethics? appeared first on DATAVERSITY.


Read More
Author: Katrina Ingram

The Hidden Infrastructure Crisis: Why CIOs Face a Perfect Storm in IT Talent Management


As organizations navigate the complex landscape of digital transformation, CIOs are confronting an unprecedented crisis that extends far beyond the typical challenges of recruitment and retention. At its core, this crisis represents a fundamental misalignment between traditional IT infrastructure management and modern development practices – a gap that threatens to widen as experienced IT professionals retire […]

The post The Hidden Infrastructure Crisis: Why CIOs Face a Perfect Storm in IT Talent Management appeared first on DATAVERSITY.


Read More
Author: Daniel Clydesdale-Cotter

Navigating the Complex Landscape of Data Sovereignty


In today’s rapidly evolving global landscape, data sovereignty has emerged as a critical challenge for enterprises. Businesses must adapt to an increasingly complex web of requirements as countries around the world tighten data regulations in an effort to ensure compliance and protect against cyberattacks. Data sovereignty regulations significantly impact an organization’s ability to conduct data […]

The post Navigating the Complex Landscape of Data Sovereignty appeared first on DATAVERSITY.


Read More
Author: Mark Cusack

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.


Read More
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.


Read More
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.


Read More
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.


Read More
Author: Abhas Ricky

Data Governance Defying Gravitas
“Defying Gravity,” the show-stopping anthem from the musical “Wicked,” captures the essence of breaking free from conventions and soaring beyond expectations. Just as Elphaba, the protagonist witch from “Wicked,” refuses to be bound by the weight of societal norms, Non-Invasive Data Governance (NIDG) offers organizations a way to defy the gravitas of traditional governance frameworks. […]


Read More
Author: Robert S. Seiner

Through the Looking Glass: What Does Data Quality Mean for Unstructured Data?
I go to data conferences. Frequently. Almost always right here in NYC. We have lots of data conferences here. Over the years, I’ve seen a trend — more and more emphasis on AI.   I’ve taken to asking a question at these conferences: What does data quality mean for unstructured data? This is my version of […]


Read More
Author: Randall Gordon

Data Governance Best Practices: Lessons from Anthem’s Massive Data Breach
In the insurance industry, data governance best practices are not just buzzwords — they’re critical safeguards against potentially catastrophic breaches. The 2015 Anthem Blue Cross Blue Shield data breach serves as a stark reminder of why robust data governance is crucial.  The Breach: A Wake-Up Call  In January 2015, Anthem, one of the largest health […]


Read More
Author: Christine Haskell

Data Insights Ensure Quality Data and Confident Decisions
Every business (large or small) creates and depends upon data. One hundred years ago, businesses looked to leaders and experts to strategize and to create operational goals. Decisions were based on opinion, guesswork, and a complicated mixture of notes and records reflecting historical results that may or may not be relevant to the future.  Today, […]


Read More
Author: Kartik Patel

Combining IoT and Blockchain Technology to Enhance Security
The Internet of Things (IoT) technology has taken the world by storm. From smart homes and wearables to connected cars and fitness trackers, IoT devices are becoming prevalent across various industries and aspects of daily life. There are approximately 15.14 billion connected IoT devices in 2023, and this number is expected to grow to around […]


Read More
Author: Hazel Raoult

Preparing Your Data Infrastructure for 2025: Lessons from the Past, Strategies for the Future


When I broke into the data world, everyone wanted to hire data scientists that would let their companies become more data driven. There were statistics about the exabytes of data that we were creating and the value it would provide. However, a few years into my career, the data world started to make a pivot…
Read more

The post Preparing Your Data Infrastructure for 2025: Lessons from the Past, Strategies for the Future appeared first on Seattle Data Guy.


Read More
Author: research@theseattledataguy.com

Securing Your Data With Actian Vector

The need for securing data from unauthorized access is not new. It has been required by laws for handling personally identiable information (PII) for quite a while. But the increasing use of data services in the cloud for all kinds of proprietary data that is not PII now makes data security an important part of most data strategies.

This is the start of a series of blog posts that take a detailed look at how data security can be ensured with Actian Vector. The first post explains the basic concept of encryption at rest and how Actian Vector’s Database Encryption functionality implements it.

Understanding Encryption at Rest

Encryption at rest refers to encryption of data at rest, which means data that is persisted, usually on disk or in cloud storage. This encryption can be used in a database system that is mainly user data in tables and indexes, but also includes the metadata describing the organization of the user data. The main purpose of encryption at rest is to secure the persisted data from unauthorized direct access on disk or in cloud storage, that is without a connection to the database system.

The encryption can be transparent to the database applications. In this case, encryption and decryption is managed by the administrator, usually at the level of databases. The application then does not need to be aware of the encryption. It connects to the database to access and work with the data as if there is no encryption at all. In Actian Vector, this type of encryption at rest is called database encryption.

Encryption at the application level, on the other hand, requires the application to handle the encryption and decryption. Often this means that the user of the application has to provide an encryption key for both, the encryption (e.g. when data is inserted) and the decryption (e.g. when data is selected). While more complicated, it provides more control to the application and the user.

For example, encryption can be applied more fine grained to specific tables, columns in tables, or even individual record values in table columns. It may be possible to use individual encryption keys for different data values. Thus, users can encrypt their private data with their own encryption key and be sure that without having this encryption key, no other user can see the data in clear text. In Actian Vector, encryption at the application level is referred to as function-based encryption.

Using Database Encryption in Actian Vector

In Actian Vector, the encryption that is transparent to the application works at the scope of a database and therefore is called database encryption. Whether a database is encrypted or not is determined with the creation of the database and cannot be changed later. When a database is created with database encryption, all the persisted data in tables and indexes, as well as the metadata for the database, is encrypted.

The encryption method is 256-bit AES, which requires a 32 byte symmetric encryption key. Symmetric means that the same key is used to encrypt and decrypt the data. This key is individually generated for each encrypted database and is called a database (encryption) key.

To have the database key available, it is stored in an internal system le of the database server, where it is protected by a passphrase. This passphrase is provided by the user when creating the database. However, the database key is not used to directly encrypt the user data. Instead, it is used to encrypt, i.e. protect, yet another set of encryption keys that in turn are used to encrypt the user data in the tables and indexes. This set of encryption keys is called table (encryption) keys.

Once the database is created, the administrator can use the chosen passphrase to “lock” the database. When the database is locked, the encrypted data cannot be accessed. Likewise, the administrator also uses the passphrase to “unlock” a locked database and thus re-enable access to the encrypted data. When the database is unlocked, the administrator can change the passphrase. If desired, it is also possible to rotate the database key when changing the passphrase.

The rotation of the database key is optional, because it means that the whole container of the table keys needs to be decrypted with the old database key to then re-encrypt it with the new database key. Because this container of the table keys also contains other metadata, it can be quite large and thus the rotation of the database key can become a slow and computationally expensive operation. Database key rotation therefore is only recommended if there is a reasonable suspicion that the database key was compromised. Most of the time, changing only the passphrase should be sufficient. And it is done quickly.

With Actian Vector it is also possible to rotate the table encryption keys. This is done independently from changing the passphrase and the database key, and can be performed on a complete database as well as on individual tables. For each key that is rotated, the data must be decrypted with the old key and re-encrypted with the new key. In this case, we are dealing with the user data in tables and indexes. If this data is very large, the key rotation can be very costly and time consuming. This is especially true when rotating all table keys of a database.

A typical workflow of using database encryption in Actian Vector:

  • Create a database with encryption:
      1. createdb -encrypt <database_name>

This command prompts the user twice for the passphrase and then creates the database with encryption. The new database remains unlocked, i.e. it is readily accessible, until it is explicitly locked or until shutdown of the database system.

It is important that the creator of the database remembers the provided passphrase because it is needed to unlock the database and make it accessible, e.g. after a restart of the database system.

  • Lock the encrypted database:
      1. Connect to the unlocked database with the Terminal Monitor:
        sql <database_name>
      2. SQL to lock the database:
        DISABLE PASSPHRASE '<user supplied passphrase>'; g

The SQL statement locks the database. New connect attempts to the database are rejected with a corresponding error. Sessions that connected previously can still access the data until they disconnect.

To make the database lock also immediately effective for already connected sessions, additionally issue the following SQL statement:

      1. CALL X100(TERMINATE); g
  • Unlock the encrypted database:
      1. Connect to the locked database with the Terminal Monitor and option “-no_x100”:
        sql -no_x100 <database_name>
      2. SQL to unlock the database:
        ENABLE PASSPHRASE '<user supplied passphrase>'; g

The connection with the “-no_x100” option connects without access to the warehouse data, but allows the administrative SQL statement to unlock the database.

  • Change the passphrase for the encrypted database:
      1. Connect to the unlocked database with the Terminal Monitor:
        sql <database_name>
      2. SQL to change the passphrase:
        ALTER PASSPHRASE '<old user supplied passphrase>' TO
        '<new passphrase>'; g

Again, it is important that the administrator remembers the new passphrase.

After changing the passphrase for an encrypted database, it is recommended to perform a new database backup (a.k.a. “database checkpoint”) to ensure continued full database recoverability.

  • When the database is no longer needed, destroy it:
      1. destroydb <database_name>

Note that the passphrase of the encrypted database is not needed to destroy it. The command can only be performed by users with the proper privileges, i.e. the database owner and administrators.

This first blog post in the database security series explained the concept of encryption at rest and how transparent encryption — in Actian Vector called Database Encryption — is used.

The next blog post in this series will take a look at function-based encryption in Actian Vector.

The post Securing Your Data With Actian Vector appeared first on Actian.


Read More
Author: Martin Fuerderer

Synthetic Data Generation: Addressing Data Scarcity and Bias in ML Models


There is no doubt that machine learning (ML) is transforming industries across the board, but its effectiveness depends on the data it’s trained on. The ML models traditionally rely on real-world datasets to power the recommendation algorithms, image analysis, chatbots, and other innovative applications that make it so transformative.  However, using actual data creates two significant challenges […]

The post Synthetic Data Generation: Addressing Data Scarcity and Bias in ML Models appeared first on DATAVERSITY.


Read More
Author: Anshu Raj

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.


Read More
Author: Dee Radh

Book of the Month: “AI Governance Comprehensive”


Welcome to December 2024’s “Book of the Month” column. This month, we’re featuring “AI Governance Comprehensive: Tools, Vendors, Controls, and Regulations” by Sunil Soares, available for free download on the YourDataConnect (YDC) website.  This book offers readers a strong foundation in AI governance. While the emergence of generative AI (GenAI) has brought AI governance to […]

The post Book of the Month: “AI Governance Comprehensive” appeared first on DATAVERSITY.


Read More
Author: Mark Horseman

Technical and Strategic Best Practices for Building Robust Data Platforms


In the AI era, organizations are eager to harness innovation and create value through high-quality, relevant data. Gartner, however, projects that 80% of data governance initiatives will fail by 2027. This statistic underscores the urgent need for robust data platforms and governance frameworks. A successful data strategy outlines best practices and establishes a clear vision for data architecture, […]

The post Technical and Strategic Best Practices for Building Robust Data Platforms appeared first on DATAVERSITY.


Read More
Author: Alok Abhishek