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 Int ..read more

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 Innova ..read more

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 stora ..read more

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 ..read more

With organizations using an average of 130 apps, the problem of data fragmentation has become increasingly prevalent. As data production remains high, data engineers need a robust data integration strategy. A crucial part of this strategy is selecting the right data integration tool to unify siloed data. Assessing Your Data Integration Needs Before selecting a data integration tool, it’s crucial to understand your organization’s specific needs and data-driven initiatives, whether they involve improving customer experiences, optimizing operations, or generating insights for strategic decisions ..read more

In our modern business world, where new trends, demands, and innovation can happen at lightning-fast speed, sustainability has become a top focus for executives and customers. In response, forward-thinking organizations are looking for ways to minimize their global impact, reduce carbon emissions, and implement sustainability best practices to optimize efficiency without sacrificing profitability. As noted in Harvard Business Review (HBR), consumers are viewing sustainability as a baseline requirement when making purchases. “Our research suggests we’re on the brink of a major shift in consumpt ..read more

Data preparation is a critical step in the data analysis workflow and is essential for ensuring the accuracy, reliability, and usability of data for downstream tasks. But as companies continue to struggle with data access and accuracy, and as data volumes multiply, the challenges of data silos and trust become more pronounced. According to Ventana Research, data teams spend a whopping 69% of their time on data preparation tasks. Data preparation might be the least enjoyable part of their job, but the quality and cleanliness of data directly impacts analytics, insights ..read more

Data preparation is a critical step in the data analysis workflow and is essential for ensuring the accuracy, reliability, and usability of data for downstream tasks. But as companies continue to struggle with data access and accuracy, and as data volumes multiply, the challenges of data silos and trust become more pronounced. According to Ventana Research, data teams spend a whopping 69% of their time on data preparation tasks. Data preparation might be the least enjoyable part of their job, but the quality and cleanliness of data directly impacts analytics, insights ..read more

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 ..read more

In the data-driven automotive industry, a modern data management strategy is needed to oversee and drive data usage to improve operations, spark innovation, meet customer demand for features and services, create designs and safety features, and inform decisions. Keeping the strategy up to date ensures it meets your current data needs and aligns with business priorities. With so many data sources now available—and new ones constantly emerging—in addition to data volumes growing rapidly, companies in the automotive industry need a data management strategy that supports this modern real ..read more