ACTIAN – 🔴 Red Button Data

AI analytics Analytics Blogs Analytics News, Articles, & Education Data Blogs | Information From Enterprise Leaders Data Education DATAVERSITY Enterprise Information Management Information Management Blogs predictive analytics predictive maintenance

Apr 25 2024

Preparing for La Niña: Adopting Predictive Maintenance Before Hurricane Season

With a La Niña watch issued for the summer, businesses operating in hurricane-prone regions face heightened concerns about the impending storm season. La Niña heavily impacts the wind shear and atmospheric conditions over the Atlantic, where most hurricanes form thanks to its warm waters. It’s rare to go a year without a hurricane hitting some part of […]

The post Preparing for La Niña: Adopting Predictive Maintenance Before Hurricane Season appeared first on DATAVERSITY.

Signal vs. Noise: Balancing On-Call Hygiene for Data-Driven Teams

In the real-time software world, 24×7 uptime is critical for core software where millions of transactions occur every second. In 2018, Amazon’s Prime Day event experienced a 13-minute outage that, according to some estimates, may have cost the company up to $99 million in lost sales. Reliability is paramount when the business depends on it […]

The post Signal vs. Noise: Balancing On-Call Hygiene for Data-Driven Teams appeared first on DATAVERSITY.

Good Data Quality Is the Secret to Successful GenAI Implementation

You wouldn’t build a house without a concrete foundation. So why are many technology leaders attempting to adopt GenAI technologies before ensuring their data quality can be trusted? Reliable and consistent data is the bedrock of a successful AI strategy. Incomplete or inconsistent data prompts GenAI models to propose equally unreliable outputs, calling the basic […]

The post Good Data Quality Is the Secret to Successful GenAI Implementation appeared first on DATAVERSITY.

Data-Driven Defense: AI as the New Frontier in Business Security

Major business setbacks due to risk management failures happen every year. They are also some of the costliest, adding up to millions of dollars in regulatory fines, lawsuits, payouts, and lost brand value. Leaders want to avoid these types of issues and rely on sound internal data management to mitigate risk and maintain confidence and […]

The post Data-Driven Defense: AI as the New Frontier in Business Security appeared first on DATAVERSITY.

The End of Agile – Part 3 (What Is Agile Really?)

In the first article, I laid out the basic premise for this series: an examination of how Agile has gone from the darling of the application development community to a virtual pariah that nobody wants to be associated with, and an exploration of the very important question of what we should replace it with. We […]

Data Lifecycle Management: Optimizing Data Storage, Usage, and Disposal

The use of data worldwide for business and recreation has exploded in the last decade, with an estimated 328.77 million terabytes of data created every single day globally. In 2024, experts predict that nearly 120 zettabytes of new data will be created. All of this data creation has also created a substantial storage problem for […]

Data Governance Made Simple

Those of us in the field of enterprise data management are familiar with the many authors contributing their knowledge and expertise to the data management body of knowledge.[1] We are also very familiar with the many, varied, and often conflicting ways in which data management terms are used. “Data architecture,” “data integration,” and even terms […]

Data Professional Introspective: The Data Management Education Program

In my work with the EDM Council’s Data Management Capability Assessment Model (DCAM) 3.0 development group, we are adding a capability that has remained under the radar in our industry: the responsibility of the Data Management Program to determine concept and knowledge gaps within its staff resources. The organization should then plan, organize, and make […]

Data Crime: Arizona Is Not Arkansas

I call it a “data crime” when someone is abusing or misusing data. When we understand these stories and their implications, it can help us learn from mistakes and prevent future data crimes. The stories can also be helpful if you have to explain the importance of data management to someone. The Story After a series […]

Overcoming Real-Time Data Integration Challenges to Optimize for Surgical Capacity

In the healthcare industry, surgical capacity management is one of the biggest issues organizations face. Hospitals and surgery centers must be efficient in handling their resources. The margins are too small for waste, and there are too many patients in need of care. Data, particularly real-time data, is an essential asset. But it is only […]

The post Overcoming Real-Time Data Integration Challenges to Optimize for Surgical Capacity appeared first on DATAVERSITY.

Actian Platform Receives Data Breakthrough Award for Innovative Integration Capabilities

Data integration is a critical capability for any organization looking to connect their data—in an era when there’s more data from more sources than ever before. In fact, data integration is the key to unlocking and sustaining business growth. A modern approach to data integration elevates analytics and enables richer, more contextual insights by bringing together large data sets from new and existing sources.

That’s why you need a data platform that makes integration easy. And the Actian Data Platform does exactly that. It’s why the platform was recently honored with the prestigious “Data Integration Solution of the Year” award from Data Breakthrough. The Data Breakthrough Aware program recognizes the top companies, technologies, and products in the global data technology market.

Whether you want to connect data from cloud-based sources or use data that’s on-premises, the integration process should be simple, even for those without advanced coding or data engineering skill sets. Ease of integration allows business analysts, other data users, and data-driven applications to quickly access the data they need, which reduces time to value and promotes a data-driven culture.

Access the Autonomy of Self-Service Data Integration

Being recognized by Data Breakthrough, an independent market intelligence organization, at its 5th annual awards program highlights the Actian platform’s innovative capabilities for data integration and our comprehensive approach to data management. With the platform’s modern API-first integration capabilities, organizations in any industry can connect and leverage data from diverse sources to build a more cohesive and efficient data ecosystem.

The platform provides a unified experience for ingesting, transforming, analyzing, and storing data. It meets the demands of your modern business, whether you operate across cloud, on-premises, or in hybrid environments, while giving you full confidence in your data.

With the Actian platform, you can leverage a self-service data integration solution that addresses multiple use cases without requiring multiple products—one of the benefits that Data Breakthrough called out when giving us the award. The platform makes data easy to use for analysts and others across your organization, allowing you to unlock the full value of your data.

Making Data Integration Easy

The Actian Data Platform offers integration as a service while making data integration, data quality, and data preparation easier than you may have ever thought possible. The recently enhanced platform also assists in lowering costs and actively contributes to better decision making across the business.

The Actian platform is unique in its ability to collect, manage, and analyze data in real time with its transactional database, data integration, data quality, and data warehouse capabilities. It manages data from any public cloud, multi or hybrid cloud, and on-premises environments through a single pane of glass.

All of this innovation will be increasingly needed as more organizations—more than 75% of enterprises by 2025—will have their data in data centers across multiple cloud providers and on-premises. Having data in various places requires a strategic investment in data management products that can span multiple locations and have the ability to bring the data together.

This is another area where the Actian Data Platform delivers value. It lets you connect data from all your sources and from any environment to break through data silos and streamline data workflows, making trusted data more accessible for all users and applications.

Try the Award-Winning Platform With a Guided Experience

The Actian Data Platform also enables you to prep your data to ensure it’s ready for AI and also help you use your data to train AI models effectively. The platform can automate time-consuming data preparation tasks, such as aggregating data, handling missing values, and standardizing data from various sources.

One of our platform’s greatest strengths is its extreme performance. It offers a nine times faster speed advantage and 16 times better cost savings over alternative platforms. We’ve also made recent updates to improve user friendliness. In addition to using pre-built connectors, you can easily connect data and applications using REST- and SOAP-based APIs that can be configured with just a few clicks.

Are you interested in experiencing the platform for yourself? If so, we invite you to participate in a guided free trial. For a limited time, we’re offering a 30-day trial with our team of technical experts. With your data and our expertise, you’ll see firsthand how the platform lets you go from data source to decision quickly and with full confidence.

The post Actian Platform Receives Data Breakthrough Award for Innovative Integration Capabilities appeared first on Actian.

Managing Software Entitlements and Billing: How Usage Data Supports Streamlined Processes

At some point in your life, you’ve probably joined a gym. In doing so, you had to decide what type of membership was right for your fitness goals and at the right price point for your budget. Maybe it was an all-access pass, billed monthly or annually, with unlimited use of the facility, including the […]

The post Managing Software Entitlements and Billing: How Usage Data Supports Streamlined Processes appeared first on DATAVERSITY.

Maximizing Business Value with Generative AI

Have we ever seen something get adopted so quickly as generative AI (GenAI) compared to the past? Think about it: ChatGPT launched in 2022 and gained 100 million users in two months. In comparison, we have been hearing about AI for a few years, but the adoption rates of AI have varied from 25% to […]

The post Maximizing Business Value with Generative AI appeared first on DATAVERSITY.

Why It’s Time to Rethink Generative AI in the Enterprise

If you’ve been keeping an eye on the evolution of generative AI (GenAI) technology recently, you’re likely familiar with its core concepts: how GenAI models function, the art of crafting prompts, and the types of data GenAI models rely on. While these fundamental components within GenAI remain constant, the way they’re applied is transforming. The […]

The post Why It’s Time to Rethink Generative AI in the Enterprise appeared first on DATAVERSITY.

Demystifying Data Analytics Models

In today’s global landscape, organizations worldwide are increasingly turning to data analytics to enhance their business performance. Research conducted by McKinsey Consulting revealed that data-driven companies not only experience above-market growth but also witness EBITDA (Earnings Before Interest, Taxes, Depreciation, and Amortization) increases of up to 25% [1]. Additionally, Forrester’s findings indicate that organizations utilizing […]

The post Demystifying Data Analytics Models appeared first on DATAVERSITY.

Why the Rise of LLMs and GenAI Requires a New Approach to Data Storage

The new wave of data-hungry machine learning (ML) and generative AI (GenAI)-driven operations and security solutions has increased the urgency for companies to adopt new approaches to data storage. These solutions need access to vast amounts of data for model training and observability. However, to be successful, ML pipelines must use data platforms that offer […]

The post Why the Rise of LLMs and GenAI Requires a New Approach to Data Storage appeared first on DATAVERSITY.

The End of Agile – Part 2 (Critiques of Agile)

Data Governance Gets a New Impetus

Data governance has often been met with furrowed brows among CIOs — sometimes seen as the broccoli of the IT dinner plate: undoubtedly good for you, but not always eagerly consumed. CIOs often bore the brunt from organizations that were forced to do top-down data governance. With this said, defensive data governance has been a […]

The Importance of Data Due Diligence

Acquiring an existing business can be an exceptional way to make your entrepreneurial dreams come to life — or even diversify your investment portfolio. But, unless you do your research well, you’re opening yourself up to a lot of unnecessary risk. The process of due diligence involves the appraisal and assessment of a potential investment, […]

Unveiling the ROI Dilemma: How Data Blind Spots Impact Asset Owners’ Bottom Line

In today’s fast-moving investment world, corporate and insurance asset owners are operating in the dark, hindered by the absence of a standardized industry benchmark for an overall asset performance assessment. Asset owners usually have many other responsibilities beyond managing portfolio strategies, affecting their ability to allocate time to comprehensively evaluate and optimize the performance of […]

The post Unveiling the ROI Dilemma: How Data Blind Spots Impact Asset Owners’ Bottom Line appeared first on DATAVERSITY.

How Artificial Intelligence Will First Find Its Way Into Mental Health

Artificial intelligence (AI) startup Woebot Health made the news recently for some of its disastrously flawed artificial bot responses to text messages that were sent to it mimicking a mental health crisis. Woebot, which raised $90 million in a Series B round, responded that it is not intended for use during crises. Company leadership woefully […]

The post How Artificial Intelligence Will First Find Its Way Into Mental Health appeared first on DATAVERSITY.

Strategies for Midsize Enterprises to Overcome Cloud Adoption Challenges

While moving to the cloud is transformative for businesses, the reality is that midsize enterprise CIOs and CDOs must consider a number of challenges associated with cloud adoption. Here are the three most pressing challenges we hear about – and how you can work to solve them.

Leveraging existing data infrastructure investments
Closing technical skills gap
Cloud cost visibility and control

Recommendations

Innovate with secure hybrid cloud solutions
Choose managed services that align with the technical ability of your data team
Maintain cost control with a more streamlined data stack

Innovate With Secure Hybrid Cloud Solutions

There is no denying that cloud is cheaper in the long run. The elimination of CapExcosts enables CIOs to allocate resources strategically, enhance financial predictability, and align IT spending with business goals. This shift toward OpEx-based models is integral to modernizing IT operations and supporting organizational growth and agility in today’s digital economy.

But migrating all workloads to the cloud in a single step carries inherent risks including potential disruptions. Moreover, companies with strict data sovereignty requirements or regulatory obligations may need to retain certain data on-premises due to legal, security, or privacy considerations. Hybrid cloud mitigates these risks by enabling companies to migrate gradually, validate deployments, and address issues iteratively, without impacting critical business operations. It offers a pragmatic approach for midsize enterprises seeking to migrate to the cloud while leveraging their existing data infrastructure investments.

How Actian Hybrid Data Integration Can Help

The Actian Data Platform combines the benefits of on-premises infrastructure with the scalability and elasticity of the cloud for analytic workloads. Facilitating seamless integration between on-premises data sources and the cloud data warehouse, the platform enables companies to build hybrid cloud data pipelines that span both environments. This integration simplifies data movement, storage and analysis, enabling organizations to extend the lifespan of existing assets and deliver a cohesive, unified and resilient data infrastructure. To learn more read the ebook 8 Key Reasons to Consider a Hybrid Data Integration Solution

Choose Managed Services That Align With the Technical Ability of Your Data Team

Cloud brings an array of new opportunities to the table, but the cloud skills gap remains a problem. High demand means there’s fierce market competition for skilled technical workers. Midsize enterprises across industries and geos are struggling to hire and retain top talent in the areas of cloud architecture, operations, security, and governance, which in turn severely delays their cloud adoption, migration, and maturity. This carries the potential greater risk of falling behind competitors.

Bridging this skills gap requires strategic investments in HR and Learning and Development (L&D), but the long-term solution has to go simply beyond upskilling employees. One such answer is managed services that are typically low- or no-code, thus enabling even non-IT users to automate key BI, reporting, and analytic workloads with proper oversight and accountability. Managed solutions are typically designed to handle large volumes of data and scale seamlessly as data volumes grow—perfect for midsize enterprises. They often leverage distributed processing frameworks and cloud infrastructure to ensure high performance and reliability, even with complex data pipelines.

Actian’s Low-Code Solutions

The Actian Data Platform was built for collaboration and governance midsize enterprises demand. The platform comes with more than 200 fully managed pre-built connectors to popular data sources such as databases, cloud storage, APIs, and applications. These connectors eliminate the need for manual coding to interact with different data systems, speeding up the integration process and reducing the likelihood of errors. The platform also includes built-in tools for data transformation, cleansing, and enrichment. Citizen integrators and business analysts can apply various transformations to the data as it flows through the pipeline, such as filtering, aggregating and cleansing, ensuring data quality and reliability—all without code.

Maintain Cost Control with a More Streamlined Data Stack

Midsize enterprises are rethinking their data landscape to reduce cloud modernization complexity and drive clear accountability for costs across their technology stack. This complexity arises due to various factors, including the need to refactor legacy applications, integrate with existing on-premises systems, manage hybrid cloud environments, address security and compliance requirements, and ensure minimal disruption to business operations.

Point solutions, while helpful for specific problems, can lead to increased operational overhead, reduced data quality, and potential points of failure, increasing the risk of data breaches and regulatory violations. Although the cost of entry is low, the ongoing support, maintenance, and interoperability cost of these solutions are almost always high.

A successful journey to cloud requires organizations to adopt a more holistic approach to data management, with a focus on leveraging data across the entire organization’s ecosystem. Data platforms can simplify data infrastructure, thus enabling organizations to migrate and modernize their data systems faster and more effectively in cloud-native environments all while reducing licensing costs and streamlining maintenance and support.

How Actian’s Unified Platform Can Help

The Actian Data Platform can unlock the full potential of the cloud and offers several advantages over multiple point solutions with its centralized and unified environment for managing all aspects of the data journey from collection through to analysis. The platform reduces the learning curve for users, enabling them to derive greater value from their data assets while reducing complexity, improving governance, and driving efficiency and cost savings.

Getting Started

The best way for data teams to get started is with a free trial of the Actian Data Platform. From there, you can load your own data and explore what’s possible within the platform. Alternatively, book a demo to see how Actian can accelerate your journey to the cloud in a governed, scalable, and price-performant way.

The post Strategies for Midsize Enterprises to Overcome Cloud Adoption Challenges appeared first on Actian.

Migrate Your Mission-Critical Database to the Cloud with Confidence

Is your company contemplating moving its mission-critical database to the cloud? If so, you may have concerns around the cloud’s ability to provide the performance, security, and privacy required to adequately support your database applications. Fortunately, it’s a new day in cloud computing that allows you to migrate to the cloud with confidence! Here are some things to keep in mind that will bring you peace of mind for cloud migration.

Optimized Performance

You may enjoy faster database performance in the cloud. Cloud service providers (CSPs) offer varying processing power, memory, and storage capacity options to meet your most demanding workload performance requirements. Frequently accessed data can be stored in high-speed caches closer to users, minimizing latency and improving response times. Load balancers distribute processing across servers within the cloud infrastructure to prevent server overload and bottlenecks. Some CSPs also have sophisticated monitoring tools to track resource usage and identify performance bottlenecks.

Enhanced Security

Data isn’t necessarily more secure in your on-premises data center than in the cloud. This is because CSPs invest heavily in advanced security controls to protect their infrastructure and have deep security expertise. They constantly update and patch their systems, often addressing vulnerabilities faster than on-premises deployments. Some CSPs also offer free vulnerability scanning and penetration testing.

However, it’s important to keep in mind that you are also responsible for security in the cloud. The Shared Responsibility Model (SRM) is a cloud security approach that states that CSPs are responsible for securing their service infrastructure and customers are responsible for securing their data and applications within the cloud environment. This includes tasks such as:

- Patching and updating software
- Properly configuring security settings
- Implementing adequate access controls
- Managing user accounts and permissions

Improved Compliance

Organizations with strict data privacy requirements have understandably been reluctant to operate their mission-critical databases with sensitive data in the cloud. But with the right CSP and the right approach, it is possible to implement a compliant cloud strategy. CSPs offer infrastructure and services built to comply with a wide range of global security and compliance standards such as GDPR, PCI DSS, HIPAA, and others, including data sovereignty requirements:

Data Residency Requirements: You can choose among data center locations for where to store your data to meet compliance mandates. Some CSPs can prevent data copies from being moved outside of a location.

Data Transfer Requirements: These include the legal and regulatory rules that oversee how personal data can be moved across different jurisdictions, organizations, or systems. CSPs often offer pre-approved standard contractual clauses (SCCs) and support Binding Corporate Rules (BCRs) to serve compliance purposes for data transfers. Some CSPs let their customers control and monitor their cross-border data transfers.

Sovereign Controls: Some CSPs use hardware-based enclaves to ensure complete data isolation.

Additionally, many CSPs, as well as database vendors, offer features to help customers with compliance requirements to protect sensitive data. These include:

Data encryption at rest and in transit protects data from unauthorized access
Access controls enforce who can access and modify personal data
Data masking and anonymization de-identify data while still allowing analysis
Audit logging: tracks data access and activity for improved accountability.

Microsoft Cloud for Sovereignty provides additional layers of protection through features like Azure Confidential Computing. This technology utilizes hardware-based enclaves to ensure even Microsoft cannot access customer data in use.

Cloud Migration Made Easy

Ingres NeXt delivers low-risk database migration from traditional environments to modern cloud platforms with web and mobile client endpoints. Since no two journeys to the cloud are identical, Actian provides the infrastructure and tooling required to take customers to the cloud regardless of what their planned journey may look like.

Here are additional articles on database modernization benefits and challenges that you may find helpful:

The post Migrate Your Mission-Critical Database to the Cloud with Confidence appeared first on Actian.

How to Effectively Prepare Your Data for Gen AI

Many organizations are prioritizing the deployment of generative AI for a number of mission-critical use cases. This isn’t surprising. Everyone seems to be talking about Gen AI, with some companies now moving forward with various applications.

While company leaders may be ready to unleash the power of Gen AI, their data may not be as ready. That’s because a lack of proper data preparation is setting up many organizations for costly and time-consuming setbacks.

However, when approached correctly, proper data prep can help accelerate and enhance Gen AI deployments. That’s why preparing data for Gen AI is essential, just like for other analytics, to avoid the “garbage in, garbage out” principle and to prevent skewed results.

As Actian shared in our presentation at the recent Gartner Data & Analytics Summit, there are both promises and pitfalls when it comes to Gen AI. That’s why you need to be skeptical about the hype and make sure your data is ready to deliver the Gen AI results you’re expecting.

Data Prep is Step One

We noted in our recent news release that comprehensive data preparation is the key to ensuring generative AI applications can do their job effectively and deliver trustworthy results. This is supported by the Gartner “Hype Cycle for Artificial Intelligence, 2023” that says, “Quality data is crucial for generative AI to perform well on specific tasks.”

In addition, Gartner explains that “Many enterprises attempt to tackle AI without considering AI-specific data management issues. The importance of data management in AI is often underestimated, so data management solutions are now being adjusted for AI needs.”

A lack of adequately prepared data is certainly not a new issue. For example, 70% of digital transformation projects fail because of hidden challenges that organizations haven’t thought through, according to McKinsey. This is proving true for Gen AI too—there are a range of challenges many organizations are not thinking about in their rush to deploy a Gen AI solution. One challenge is data quality, which must be addressed before making data available for Gen AI use cases.

What a New Survey Reveals About Gen AI Readiness

To gain insights into companies’ readiness for Gen AI, Actian commissioned research that surveyed 550 organizations in seven countries—70% of respondents were director level or higher. The survey found that Gen AI is being increasingly used for mission-critical use cases:

44% of survey respondents are implementing Gen AI applications today.
24% are just starting and will be implementing it soon.
30% are in the planning or consideration stage.

The majority of respondents trust Gen AI outcomes:

75% say they have a good deal or high degree of trust in the outcomes.
5% say they do not have very much or not much trust in them.

It’s important to note that 75% of those who trust Gen AI outcomes developed that trust based on their use of other Gen AI solutions such as ChatGPT rather than their own deployments. This level of undeserved trust has the potential to lead to problems because users do not fully understand the risk that poor data quality poses to Gen AI outcomes in business.

It’s one issue if ChatGPT makes a typo. It’s quite another issue if business users are turning to Gen AI to write code, audit financial reports, create designs for physical products, or deliver after-visit summaries for patients—these high value use cases do not have a margin for error. It’s not surprising, therefore, that our survey found that 87% of respondents agree that data prep is very or extremely important to Gen AI outcomes.

Use Our Checklist to Ensure Data Readiness

While organizations may have a high degree of confidence in Gen AI, the reality is that their data may not be as ready as they think. As Deloitte notes in “The State of Generative AI in the Enterprise,” organizations may become less confident over time as they gain experience with the larger challenges of deploying generative AI at scale. “In other words, the more they know, the more they might realize how much they don’t know,” according to Deloitte.

This could be why only four percent of people in charge of data readiness say they were ready for Gen AI, according to Gartner’s “We Shape AI, AI Shapes Us: 2023 IT Symposium/Xpo Keynote Insights.” At Actian, we realize there’s a lot of competitive pressure to implement Gen AI now, which can prompt organizations to launch it without thinking through data and approaches carefully.

In our experience at Actian, there are many hidden risks related to navigating and achieving desired outcomes for Gen AI. Addressing these risks requires you to:

Ensure data quality and cleanliness
Monitor the accuracy of training data and machine learning optimization
Identify shifting data sets along with changing use case and business requirements over time
Map and integrate data from outside sources, and bring in unstructured data
Maintain compliance with privacy laws and security issues
Address the human learning curve

Actian can help your organization get your data ready to optimize Gen AI outcomes. We have a “Gen AI Data Readiness Checklist” that includes the results of our survey and also a strategic checklist to get your data prepped. You can also contact us and then our experts will help you find the fastest path to the Gen AI deployment that’s right for your business.

The post How to Effectively Prepare Your Data for Gen AI appeared first on Actian.

Creative Ways to Surf Your Data Using Virtual and Augmented Reality

Organizations often struggle with finding nuggets of information buried within their data to achieve their business goals. Technology sometimes comes along to offer some interesting solutions that can bridge that gap for teams that practice good data management hygiene. We’re going to take a look deep into the recesses of creativity and peek at two […]

🔴 Red Button Data