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Data Security: The Advantages of Hybrid vs. Public Clouds

As an industry, we often discuss proper and effective data analysis, however data security is actually even more important. After all, what good is effective analysis without securing the foundational data? Additionally, in 2024 there are numerous clouds one can persist data within including public, private, and hybrid cloud environments. This raises the natural question of how to properly secure your data for the cloud.

Public, Multi-Cloud, and Hybrid Clouds

It helps to start with a baseline of common terminology used throughout the industry. Public clouds are publicly accessible compute and storage services provided by third-party cloud providers. Multi-cloud is simply an architecture composed of services originating from more than one public cloud.

A hybrid cloud is composed of different interconnected public and private clouds that work together sharing data and processing tasks. Interconnectivity between hybrid environments is established with local area networks, wide area networks, VPNs, and APIs. Like all cloud environments, hybrid environments leverage virtualization, containerization, and software-defined networking and storage technologies. And dedicated management planes allow users to allocate resources and scale on-demand.

Security Benefits of Hybrid Cloud Architecture

A hybrid cloud is ideal when you want to leverage both the scale of public cloud services while also securing and retaining a subset of your data on-premises. This helps an organization retain and secure compliance and to address data security policies. Sensitive datasets can be retained on-premises while less sensitive assets may be published to public cloud services.

Hybrid clouds provide the ability to scale on-demand public services during peak workloads. Organizations reap cost optimization by being able to leverage both on-premises and public cloud services and storage assets. And there are disaster recovery and geographic failover benefits to hybrid cloud solutions. Finally, a hybrid cloud enables businesses to gradually migrate legacy applications and datasets from on-premises to public cloud environments.

Actian’s Cloud Data Platform

The Actian Data Platform coupled with DataConnect provides no-code, low-code and pro-code data integrations that enable hybrid cloud data solutions. Actian DataConnect provides enterprise-grade integration with connectivity support for both our public and private cloud data platforms. Public cloud data services can be provisioned using SOAP or REST API access with configurable authentication. Users are able to schedule and execute data integration jobs that securely move data across all Actian Data Platform environments. Both at-rest and in-flight data encryption can also be implemented.

The Actian Data Platform’s data warehousing component can be scaled up and down in real-time, this helps greatly with right-sizing workload scale. The Actian public cloud data warehouse is built on decades of patented real-time query processing and optimizer innovations. In summary, the Actian Data Platform is unique in its ability to collect, manage, and analyze data in real-time, leveraging its native data integration, data quality, and data warehouse capabilities in an easy-to-use single platform.

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Author: Actian Corporation

How to Easily Add Modern User Interfaces to Your Database Applications

Modernizing legacy database applications brings all the advantages of the cloud alongside benefits such as faster development, user experience optimization, staff efficiency, stronger security and compliance, and improved interoperability. In my first blog on legacy application modernization with OpenROAD, a rapid database application development tool, I drilled into the many ways it makes it easier to modernize applications with low risk by retaining your existing business logic. However, there’s still another big part of the legacy modernization journey, the user experience.

Users expect modern, intuitive interfaces with rich features and responsive design. Legacy applications often lack these qualities, which can often require significant redesign and redevelopment during application modernization to meet modern user experience expectations. Not so with OpenROAD! It simplifies the process of creating modern, visually appealing user interfaces by providing developers with a range of tools and features discussed below.

The abf2or Migration Utility

The abf2or migration utility modernizes Application-By-Forms (ABF) applications to OpenROAD frames, including form layout, controls, properties, and event handlers. It migrates business logic implemented in ABF scripts to equivalent logic in OpenROAD. This may involve translating script code and ensuring compatibility with OpenROAD’s scripting language. The utility also handles the migration of data sources to ensure that data connections and queries function properly and can convert report definitions.

WebGen

WebGen is an OpenROAD utility that lets you quickly generate web and mobile applications in HTML5 and JavaScript from OpenROAD frames allowing OpenROAD applications to deployed on-line and on mobile devices.    

OpenROAD and Workbench IDE 

The OpenROAD Workbench Integrated Development Environment (IDE) is a comprehensive toolset for software development, particularly for creating and maintaining applications built using the OpenROAD framework. It provides tools specifically designed to migrate partitioned ABF applications to OpenROAD frames. Developers can then use the IDE’s visual design tools to further refine and customize the programs.   

Platform and Device Compatibility

Multiple platform support, including Windows and Linux, lets developers create user interfaces that can run seamlessly across different operating systems without significant modification. Developers can deliver applications to a desktop or place them on a web server for web browser access; OpenROAD installs them automatically if not already installed. The runtime for Windows Mobile enables deploying OpenROAD applications to mobile phones and Pocket PC devices.

Visual Development Environment

OpenROAD provides a visual development environment where developers can design user interface components using drag-and-drop tools, visual editors, and wizards. This makes it easier for developers to create complex user interface layouts without writing extensive code manually.   

Component Library

OpenROAD offers a rich library of pre-built user interface components, such as buttons, menus, dialog boxes, and data grids. Developers can easily customize and integrate these components into applications, saving time and user interface design effort.

Integration with Modern Technologies

Integration with modern technologies and frameworks such as HTML5, CSS3, and JavaScript allows developers to incorporate modern user interface design principles, such as responsive design and animations, into their applications.

Scalability and Performance

OpenROAD delivers scalable and high-performance user interfaces capable of handling large volumes of data and complex interactions. It optimizes resource utilization and minimizes latency, ensuring a smooth and responsive user experience.

Modernize Your OpenROAD applications

Your legacy database applications may be stable, but most will not meet the expectations of users who want modern user interfaces. You don’t have to settle for the status quo. OpenROAD makes it easy to deliver what your users are asking for with migration tools to convert older interfaces, visual design tools, support for web and mobile application development, an extensive library of pre-built user interface components, and much more.

The post How to Easily Add Modern User Interfaces to Your Database Applications appeared first on Actian.


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Author: Teresa Wingfield

How GenAI Bridges the Data Gap Between CMOs and CFOs


Marketing budgets are never entirely safe. While it may seem like pressure is easing as global economic estimates turn slightly sunnier, consumer demand is still getting more expensive to capture and close – which means scrutiny from finance chiefs is as tough as ever. To keep investment flowing, CMOs need to get better at not only boosting […]

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Author: Harriet Durnford-Smith

Successful low-risk Customer Master Data implementation
STrategy and Tactics jigsaw pieces

Setting precise objectives is an indispensable factor in the successful implementation of Customer Master Data Management (CMDM).

The fundamental threat to a burgeoning CMDM program lies in its initiation with unclear or ambiguous business objectives. Although overarching goals such as enhancing data quality, supporting informed decision-making, achieving a unified truth, or obtaining a 360-degree customer view might seem logically sound, they often lack the specificity required for the effective execution of a CMDM program.

Gartner, a leading research and advisory company, highlights four key reasons for Master Data Management (MDM) program failures, among them insufficient executive sponsorship, inadequate adjustment of business processes, a lack of validation, and the potential pitfalls of an “all at once” or “big-bang” implementation strategy. These pitfalls underscore the critical importance of a carefully structured and well-defined approach in implementing CMDM initiatives.

One notable aspect contributing to failure might be the absence of a structured framework to measure the value of data management for an organization, particularly within the domain of customer data. Without well-defined objectives, CMDM initiatives often struggle to progress beyond their initial stages or may fail outright during implementation.

To mitigate the risk of CMDM failure and ensure the success of the program, it is imperative to follow a systematic approach. The first step involves defining measurable business outcomes related specifically to customer data. The litmus test for these objectives lies in the ability to articulate CMDM outcomes in non-technical terms that resonate with both business and IT stakeholders. If an organization cannot express its objectives without relying on technical jargon, it raises a red flag, indicating the need for re-evaluation.

A helpful technique in this regard is to encourage organizations to state their objectives without using the word “data” Instead, the focus should be on articulating business objectives related to customer data that CMDM aims to address.

  • Increasing customer retention rates: Achieved by reducing customer service response times to a specific duration, for example.
  • Augmenting cross-sell opportunities: Achieved through a more personalized enhancement of the customer experience. This might be another.
  • Improving CSAT scores: As a lagging indicator through more accurate and timely responses to customer interactions.

By steering away from technical language and concentrating on specific business outcomes linked to customer data, organizations can ensure that CMDM objectives are clear, understandable, and relevant to all stakeholders.

Understanding the core motivations behind CMDM initiatives is paramount. Whether the objective is to increase customer loyalty, optimize marketing strategies, or personalize customer interactions, there must be a compelling business reason underpinning CMDM efforts. Organizations need to document these customer-centric business challenges and connect them to the “what” and “how” of the CMDM project.

Failure to establish this connection can lead to confusion and a loss of focus. To prevent this, organizations must emphasize the value of CMDM by demonstrating its ability to drive customer-centric outcomes, such as personalized marketing campaigns, improved customer service, or enhanced customer loyalty programs. Identifying specific quick wins related to customer data is crucial to showcasing the tangible value of the CMDM program.

Beyond traditional Return on Investment (ROI) studies, CMDM initiatives focused on customer data require a roadmap that outlines the core business problem and provides a detailed plan to address it. This roadmap should encompass stakeholder engagement and commitment strategies, ensuring that the CMDM program progresses smoothly from conception to implementation, specifically in the domain of customer master data.

An effective “Strategic Outcomes Blueprint” (SOB) is instrumental in identifying quick wins related to customer data that prioritize business outcomes, thereby highlighting the value of the CMDM program.

A “Strategic Outcomes Blueprint” should include:

  • A clear description of the customer-centric business opportunity, such as increasing customer lifetime value or improving customer retention rates.
  • Prioritized initiatives and resource allocation focusing on customer data management.
  • Key performance indicators specific to customer data quality, customer satisfaction, or customer engagement.
  • Quantification of projected ROI related to customer-centric outcomes.

By creating a compelling business case through the SOB, organizations can think big while starting small, focusing on targeted problem-solving related to customer data and demonstrating the immediate value of the CMDM program.

It’s crucial to recognize that CMDM in the context of customer master data is not a one-time project but a continuous journey. By tying CMDM implementations to real-world business challenges specific to customer data and showcasing their value through quick wins, organizations can establish CMDM as an ongoing initiative. Celebrating achievements and sharing insights derived from clean, trusted customer data helps maintain momentum and enthusiasm among stakeholders.

Furthermore, CMDM programs related to customer data often involve multi-domain challenges, such as customer relationships, product preferences, and service histories. By mastering one customer data domain at a time and celebrating successes, organizations can expand their CMDM efforts gradually, addressing various aspects of customer interactions. This incremental approach enables businesses to build expertise, tackle specific challenges related to customer data, and continuously demonstrate value to stakeholders.

Any successful CMDM program focused on customer master data necessitates clear and customer-centric objectives, active collaboration between business and IT teams, a deep understanding of underlying customer-centric business challenges, and a well-defined roadmap specific to customer data management.

By following these steps, organizations can steer clear of potential pitfalls, reduce risks, and ensure that CMDM initiatives focused on customer data deliver meaningful and measurable results. Implementation of CMDM in the context of customer master data is not merely a project; it’s a continuous journey toward customer data excellence, personalized customer experiences, and sustainable growth in today’s customer-centric business landscape.

Protecting Your Data: 5 IAM Trends to Watch


In our increasingly digital world, organizations recognize the importance of securing their data. As cloud-based technologies proliferate, the need for a robust identity and access management (IAM) strategy is more critical than ever. IAM serves as the gatekeeper to an organization’s sensitive information, ensuring that only authorized individuals have an appropriate level of access. With […]

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Author: Jackson Shaw

The Link Between Trusted Data and Expanded Innovation

One highlight of my job is being able to talk to customers and prospective customers throughout the year at various events. What I keep hearing is that data is hard, and this holds true for companies of all sizes. And they’re right. Data can be hard. It can be hard to integrate, manage, govern, secure, and analyze. Building pipelines to new data sources can also be hard.

Business and IT both need data to be accessible to all users and applications, cost-effective to store, and deliver real-time insights. Any data challenges will limit these capabilities and present major barriers to innovation. That’s why we’ve made it our mission to make data easy and trustworthy.

Actian exists to provide the most trusted, flexible, and easy-to-use data platform on the market. We know that’s a bold promise and requires solving a lot of your data pain points. Yet we also know that to be truly data driven, you must have uninterrupted access to trusted data.

Overcoming the Trust Barrier

At Actian, we’ve been saying for a long time that you need to be able to trust your data. For too many companies, that’s not happening or it’s not happening in a timely manner. For example, nearly half—48%—of CEOs worry about data accuracy, according to IBM, while Gartner found that less than half of data and analytics teams—just 44%—are effectively providing value to their organization.

These numbers are unacceptable, especially in the age of technology. Everyone who uses data should be able to trust it to deliver ongoing value. So, we have to pause and ask ourselves why this isn’t happening. The answer is that common barriers often get in the way of reaching data goals, such as:

  • Silos that create isolated, outdated, and untrustworthy data.
  • Quality issues, such as incomplete, inaccurate, and inconsistent data.
  • Users do not have the skills needed to connect and analyze data, so they rely on IT.
  • Latency issues prevent real-time data access, which limits timely insights.
  • Data management problems that existed on-premises were migrated to the cloud.

Organizations know they have some or all of these problems, but they often don’t know what steps are needed to resolve them. Actian can help. We have the technology and expertise to enable data confidence—regardless of where you are on your data journey.

Innovation Starts with Trustworthy Data

What if you could swiftly go from data to decision with full confidence and ease? It doesn’t have to be a pipe dream. The solution is readily available now. It ensures you’re using high-quality, accurate data so you have full confidence in your decision-making. It simplifies data transformations, empowering you to get the data you want, when and how you want it, regardless of your skill level, and without relying on IT. Plus, you won’t have to wait for data because it gets delivered in real-time.

The Actian Data Platform makes data easy-to-use, allowing you to meet the needs of more business users, analysts, and data-intensive applications. You can collect, manage, and analyze data in real-time with our transactional database, data integration, data quality, and data warehouse capabilities working together in a single, easy-to-use platform.

The platform lets you manage data from any public cloud, multi- or hybrid cloud, and on-premises environment through a single pane of glass. The platform’s self-service data integration lowers costs while enabling you to perform more use cases without needing multiple data products.

What does all of this mean for your business? It means that data integration, access, and quality are easier than ever. It also means that you can trust your data to make confident decisions that accelerate your organization’s growth, foster new levels of innovation, support your digital transformation, and deliver other business value.

Enabling a Data-Driven Culture

With data volumes becoming more robust, having immediate access to high-quality data is essential, but challenging. Any problems with quality, latency, or integration will compound as data volumes grow, leading to potentially misinformed decision-making and mistrust in the data. Establishing data quality standards, making integration and access easy, and putting data in the hands of everyone who needs it advances the business, promotes a data-driven culture, and drives innovation. And this is where Actian can play a critical role.

What makes the Actian Data Platform unique, at a high level, is its ability to consolidate various data functions into a single platform, making data readily available and easy to use across your organization.

The platform handles extract, transform, and load (ETL), data transformation, data quality checks, and data analytics all in one place. Bringing everything and everyone together on a single platform lowers costs and reduces the resources needed to manage your data system. You benefit from real-time, trustworthy data across the entire organization, giving you full confidence in your data.

When you trust your data, you have the ability—and the confidence—to explore more use cases, increase revenues, reduce costs, fast-track innovation, win market share, and more for a strategic edge in your industry. Our customers are using data to drive new successes everyday!

Related resources you may find useful:

Top Capabilities to Look for in Database Management Tools

The Actian Data Platform’s Superior Price-Performance

How to Build an Effective Data Management Project Plan

The post The Link Between Trusted Data and Expanded Innovation appeared first on Actian.


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Author: Actian Corporation

Strategies for Closing the Digital Transformation Gap in Healthcare


There’s no need to sugarcoat it – in the U.S., a widening digital gap is carving up the healthcare industry. AVIA Research recently found that only 10-40% of health systems are actively making a direct financial impact in areas where digital transformation can make a difference. In practice, the disparity looks like this: Non-traditional high-tech players like […]

The post Strategies for Closing the Digital Transformation Gap in Healthcare appeared first on DATAVERSITY.


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Author: Sridhar Yerramreddy

Alternatives to SSIS(SQL Server Integration Services) – How To Migrate Away From SSIS


SQL Server Integration Services (SSIS) comes with a lot of functionality useful for extracting, transforming, and loading data. It can also play important roles in application development and other projects. But SSIS is far from the only platform that can provide these services. You might seek alternatives to SSIS because you want a more agile…
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The post Alternatives to SSIS(SQL Server Integration Services) – How To Migrate Away From SSIS appeared first on Seattle Data Guy.


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Author: research@theseattledataguy.com

5 Data Management Trends Data Practitioners and CIOs Should Know in 2024 and 2025


Data has always been a driving factor for organizations. Over the past decade, the value of data has increased exponentially. Organizations across all categories and sizes (MNCs and SMEs) have started making critical business decisions based on insights gathered from collected data. The data, most commonly referred to as historical data, is collected over sufficient […]

The post 5 Data Management Trends Data Practitioners and CIOs Should Know in 2024 and 2025 appeared first on DATAVERSITY.


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Author: Yash Mehta

Effective Code Documentation for Data Science Projects


Code documentation is a detailed explanation of how the code works. It is a comprehensive guide that helps developers understand and use the code effectively. It is like a manual for your source code, providing information on the purpose of the code, how it is structured, and how it can be modified. Many developers might […]

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Author: Gilad David Maayan

5 Key Strategies for Making Data Visualization Accessible


“If I can’t picture it, I can’t understand it.” —Albert Einstein Research has found that 65% of the general population are visual learners, meaning they need to see information as images to understand it. The business world confirms this: Visualization is essential in driving success. Take, for instance, data visualization, or, the art of translating data into […]

The post 5 Key Strategies for Making Data Visualization Accessible appeared first on DATAVERSITY.


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Author: Daniel Jebaraj

2024’s Predominant Technology Trend? The Cloud


As AI becomes an integral part of business processes and strategic planning, organizations have increasingly based their data strategies around its capabilities. Businesses are generating more data than ever from sources like IoT sensors, customer transactions, social media, and more; managing and extracting value from this explosion of big data has become a key priority. […]

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Author: Chris Heard

Measuring and Reporting on Supply Chain Sustainability the Right Way

In an era where sustainability is not just a buzzword but a strategic imperative, the supply chain plays a pivotal role in shaping an organization’s environmental and social footprint. Here are some ways to guide your business on the essential aspects of measuring and reporting sustainability within the supply chain, focusing on data management, goal and metric definitions, and adherence to reporting standards.

Data Management: Unraveling the Threads of Sustainability

In the intricate web of supply chain operations, data serves as the thread that weaves together the fabric of sustainability. Comprehensive data management is essential for measuring, monitoring, and optimizing sustainability initiatives within all aspects of your organization’s supply chain.

The first step in sustainable data management is collecting relevant information across the organization. Some examples of this data include energy consumption, water usage, waste generation, emissions, and social impact factors such as labor practices and community engagement. The challenge, however, is gathering data from diverse sources—including suppliers, manufacturers, logistics partners, and internal operations. Strategies for overcoming this include implementing data-sharing agreements with vendors, conducting regular audits, and leveraging emerging technologies like Internet of Things (IoT) sensors, blockchain, and the API integration capabilities of your data platform to track and trace environmental and social performance throughout the supply chain.

Once collected, sustainability data must be organized coherently and structured to facilitate fast analysis and decision-making. This means establishing a clear taxonomy and data schema that categorizes information according to relevant sustainability indicators, like carbon emissions or waste generation. This is where data visualization tools and dashboards come in handy because they will help present the information in a user-friendly format.

Defining Goals and Metrics: Charting a Course for Sustainable Success

Once the data is collected and integrated, the next step is to establish goals and metrics for meaningful action and measurable progress. By breaking down silos and integrating data from various departments, sources, and stakeholders, organizations can gain a comprehensive understanding of their environmental and social impact across the entire supply chain. This integrated approach allows you to identify and establish goals that address the most significant areas of opportunity and risk.

Implementing policies to act on the data requires a strategic and proactive approach that aligns with your defined goals and metrics. Best practices include setting ambitious, yet achievable, targets based on data-driven insights and industry benchmarks. These targets should provide clear direction and accountability for sustainability efforts. Additionally, your organization should develop policies and procedures to track progress toward these targets, leveraging technology and data analytics to monitor performance in real-time to course correct as needed.

Establishing a culture of continuous improvement and accountability is essential, with regular reviews and updates to policies and targets based on evolving data insights and stakeholder expectations.

Reporting Standards: Navigating the Landscape of Transparency

Established reporting frameworks such as the Global Reporting Initiative (GRI) and the Sustainability Accounting Standards Board (SASB) play a crucial role in guiding organizations toward transparent and consistent sustainability reporting. These frameworks provide comprehensive guidelines and standardized metrics for measuring and disclosing environmental, social, and governance (ESG) performance.

Adhering to recognized reporting standards helps organizations enhance credibility and comparability in the eyes of stakeholders—including investors, customers, employees, and regulators. Consistent reporting enables investors to make informed investment decisions, customers to make ethical purchasing choices, and regulators to enforce compliance with environmental and social regulations.

The emergence of integrated reporting represents a paradigm shift in how organizations disclose their performance and make holistic decisions, moving beyond traditional financial metrics to encompass broader value creation for all stakeholders. Integrated reporting seeks to present financial and sustainability performance cohesively, acknowledging the interconnectedness between financial success and environmental and social impact.

By integrating financial and non-financial data into a single, comprehensive report, organizations can provide stakeholders with a holistic view of their long-term value-creation strategy. Integrated reporting encourages a more balanced and sustainable approach to business decision-making, where financial considerations are complemented by environmental and social considerations. As organizations increasingly recognize the importance of holistic value creation, integrated reporting, and integrated data in general, is the key for communicating sustainability performance and demonstrating long-term resilience and viability.

Integration is Hard, but Actian Can Help

The Actian Data Platform offers invaluable capabilities to companies striving to enhance their ESG efforts and reporting accuracy. By providing a unified platform for data management, integration, and analytics, Actian empowers organizations to access, analyze, and leverage sustainability-related data from across the entire supply chain in real-time.

With these real-time insights into key ESG metrics, your company can make informed decisions that drive sustainable practices and optimize resource usage. Actian’s advanced integration capabilities empower your organization to identify trends, patterns, and opportunities for improvement, facilitating proactive interventions to minimize environmental impact and maximize social responsibility. Moreover, by streamlining data collection and aggregation, Actian enhances confidence that sustainability reports are comprehensive, accurate, and timely, bolstering credibility and trust with stakeholders.

Measuring and reporting sustainability in the supply chain requires a strategic and holistic approach. By mastering data management, defining clear goals and metrics, and adhering to reporting standards, businesses can not only enhance their environmental and social impact but also build trust with stakeholders. By making data easy, the Actian Data Platform enables you to drive and monitor sustainability initiatives across your entire supply chain.

The post Measuring and Reporting on Supply Chain Sustainability the Right Way appeared first on Actian.


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Author: Actian Corporation

How DSPM Fits into Your Cloud Security Stack


DSPM solutions provide unique security capabilities and are specifically tailored to addressing sensitive data in the cloud, but also to supporting a holistic cloud security stack. As the variety and sophistication of attacks increase over time, new challenges arise that the existing security stack can hardly keep up with. A new, more aligned, and holistic […]

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Author: Gad Rosenthal

7 Ways AI Will Transform Data Storage


The rapid adoption of artificial intelligence and machine learning (AI/ML) over the past year has transformed just about everything – ushering in a new era of innovation and growth the world has never seen. The same goes for data storage, where the technologies’ impact will be transformative, enabling greater business agility that companies need to […]

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Author: Scott Hamilton

Documenting Critical Data Elements
Many Data Governance or Data Quality programs focus on “critical data elements,” but what are they and what are some key features to document for them? A critical data element is any data element in your organization that has a high impact on your organization’s ability to execute its business strategy. An example is Customer Email […]


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Author: Mark Horseman

The Art of Lean Governance: Addressing the Elephant in the Room
Hands down one of the most frequent observations when walking the data factory at different clients is the excessive use of spreadsheets for data collection and purification. These spreadsheets are part of a critical data enrichment process for getting reports out the door on time. However, these same spreadsheets represent a significant control problem exposing […]


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Author: Steve Zagoudis

Automating Privacy and Compliance
In the digital age, the deluge of data is relentless. This burgeoning data realm, bolstered by the dawn of generative AI, demands meticulous choreography to remain coherent and valuable. As the complexity of ecosystems multiplies, so does the imperative to tether this wealth of information to the bedrock of privacy and protection. Michelle Dennedy, Jonathan […]


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Author: Myles Suer

AI Could Save Your Data Governance Program, but It’s Unlikely
In the 1980s, there was a flurry of movies about robots coming to imprison or terrorize humanity. Forty years later, almost every business and technology publication seems to have reimagined the army of robots and artificial intelligence as trading their quest for world domination for the exciting world of business processing. It’s unlikely that most […]


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Author: Carmen Robinson

Eyes on Data: Transforming Data Challenges into Real Progress
In a world increasingly dominated by data, organizations are grappling with the need to effectively manage and harness this valuable asset. And with increased regulations and compliance, opportunities for innovation and AI, digital transformation initiatives, and data-driven decision-making, the demands for accurate, accessible, protected data are increasing exponentially. At the same time, the data management […]


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Author: EDM Council

Explainable AI: 5 Open-Source Tools You Should Know
Explainable AI refers to ways of ensuring that the results and outputs of artificial intelligence (AI) can be understood by humans. It contrasts with the concept of the “black box” AI, which produces answers with no explanation or understanding of how it arrived at them. Explainable AI tools are software and systems that provide transparency […]


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Author: Gilad David Maayan

A Day in the Life of a Chief Digital Officer

Almost every organization is embarking on some sort of digital transformation initiative. The role of a Chief Digital Transformation Officer (CDO) has emerged to lead and oversee success. Major responsibilities of the CDO include:

  • Define and implement a digital strategy for the company’s future that includes technologies such as the cloud, artificial intelligence, automation, Internet of Things (IoT), and social media.
  • Integrate digital initiatives with strategic planning to gain executive leadership commitment and budget, and resource allocation.
  • Work with cross-functional teams to generate innovative digital solutions for products, services, customer experiences, sales, marketing, and optimized business processes
  • Own, prioritize, monitor, and manage the company’s digital innovation project portfolio.
  • Serve as an evangelist and a change agent, championing the use of digital technology and practices.

Top Challenges for the CDO

Executing the above activities is a demanding job. While specific challenges may vary based on the industry and organizational context, some common challenges faced by the CDO include resistance to change, budget justification, hard-to-replace legacy technologies, the skills gap, and demonstrating success as discussed below.

Resistance to Change

A general sentiment expressed as “if it ain’t broke don’t fix it” competes with an overarching sense of urgency created by the need for digital transformation. To overcome the status quo, CDOs are constantly engaged in identifying and clearly communicating the pain points stagnation is causing. These often include compatibility and obsolescence issues, security and compliance risks, missing functionality, lack of scalability to meet business growth, expensive maintenance, inefficient workflows, and processes that hamper business agility, and poor user experiences.

Budget Justification

It can be challenging to show that the cost of modernization is significantly less than maintaining legacy systems over time. The budget justification challenge is compounded by maintenance and innovation budgets that are usually separate along with the sentiment that money might be better spent on opportunities other than what is working as intended, especially if the return on investment of modernization will take time to materialize.

These issues place a heavy onus on CDOs to highlight the opportunities that digital transformation presents. By embracing digital transformation, CDOs elaborate on the business value, such as operational efficiency, optimizing the customer experience, product innovation, data-driven decision making, business agility, sustainability, and staff productivity.

Plus, it’s a lot easier to integrate digital technologies with a wide range of systems, processes, and functions across an organization than to integrate legacy ones. This is important because digital technologies play a critical role in optimizing the supply chain by improving visibility, efficiency, and collaboration. Legacy modernization in the realm of electronic commerce is another key example that can lead to a more agile and user-friendly online shopping experience that supports a greater choice of web and mobile interfaces.

Hard-to-Replace Legacy Technologies

As businesses attempt to modernize, many have legacy systems and infrastructure that are hard to replace. On-premises to cloud migration can be a long and risky journey. Migrating or replacing these systems while ensuring business continuity requires careful planning and resources. The CDO often oversees the development of a data migration strategy to ensure a smooth transition from legacy systems to modern platforms and their integration with existing applications, databases, and platforms. Identifying and mitigating risks associated with legacy system replacement is critical to avoid disruption of mission-critical systems. 

Talent Acquisition and Skill Gaps

Not only is attracting, developing, and retaining talent with the right digital skills a constant challenge, but existing legacy staff will need to be retrained and/or upskilled. Layoffs in technology may be in full swing, but demand in 2024 for digital transformation technical skills such as cloud, DevOps, security, privacy, development, artificial intelligence, automation, system updates, data integration, and analytics is high according to Robert Half Technology’s 2024 IT salary report.

Showing Success

Demonstrating positive business outcomes is critical to continued success, but how to measure them isn’t easy. CDOs often use these types of key performance indicators (KPIs) to gauge impact:

  • Percentage increase in digital sales or revenue.
  • Customer satisfaction scores (CSAT), Net Promoter Score (NPS), and other customer engagement metrics.
  • Time to launch for digital products and services
  • Percentage of users or employees adopting new digital tools and processes.
  • Cost savings achieved through process automation or efficiency gains.

Digital Transformation with Actian

Actian transforms business by enabling customers to make confident, data-driven decisions that accelerate their organization’s growth. We are committed to helping our customers secure their digital future by making it easy to modernize their databases and database applications, including flexible choices for on-premises to cloud migration.

Related Resources

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Author: Teresa Wingfield

How to Achieve Self-Service Data Transformation for AI and Analytics


Data transformation is the critical step that bridges the gap between raw data and actionable insights. It lays the foundation for strong decision-making and innovation, and helps organizations gain a competitive edge. Traditionally, data transformation was relegated to specialized engineering teams employing complex extract, transform, and load (ETL) processes using highly complex tooling and code. […]

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Author: Raj Bains

Unveiling the Power of Dark Data in Strategic Decision-Making


If you’ve never heard of dark data, you’re not alone. Setting aside the ominous name, dark data isn’t something that is inherently bad – although, in practice, it usually does end up this way. Dark data is usually unstructured data, though it can also be semi-structured or structured data that a business collects and stores but […]

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Author: Nahla Davies

4 Reasons Businesses Are Implementing Data Management Systems


Enterprises today face the complex challenge of effectively managing an ever-growing, diverse, and rapidly changing trove of data. This reality of handling vast and varied data sets is pivotal for businesses aiming to stay competitive and informed. The strategic management of data is crucial in shaping business success. That’s why implementing innovative data management systems […]

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Author: David Whitt

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