As technology expands, at TechD, we know that the quality of generative AI (gen AI) depends on accurate data sourcing. A reliable and trustworthy data source is essential for sharing information across departments. Through the implementation of generative AI we are able to expand our knowledge to many individuals easily, quickly and efficiently becoming a resource. In today’s rapidly evolving digital world, immediate responses are crucial for delivering outstanding user experiences. Our partnership with IBM facilitates the delivery of scalable solutions, rapidly implementable by organizations ..read more

In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. They provide the backbone for a range of use cases such as business intelligence (BI) reporting, dashboarding, and machine-learning (ML)-based predictive analytics, that enable faster decision making and insights. The rise of cloud has allowed data warehouses to provide new capabilities such as cost-effective data storage at petabyte scale, highly scalable compute and storage, pay-as-you-go pricing and fully managed service delivery. Companies are shifting their investments to cloud software ..read more

After developing a machine learning model, you need a place to run your model and serve predictions. If your company is in the early stage of its AI journey or has budget constraints, you may struggle to find a deployment system for your model. Building ML infrastructure and integrating ML models with the larger business are major bottlenecks to AI adoption [1,2,3]. IBM Db2 can help solve these problems with its built-in ML infrastructure. Someone with the knowledge of SQL and access to a Db2 instance, where the in-database ML feature is enabled, can easily learn to build and use a machine lea ..read more

IT architectures have witnessed an increasing amount of dispersal and segmentation over the last decade of their life cycle as new data and new technology have made their impact with 62% of enterprises planning to modernize their existing on-premises data platforms[1]. These changes are needed in order to address the lack of cohesion and widespread data repositories and to meet business needs around data and analytics. Of course, doing so can also be difficult without the right planning and experience. This is leading to abandoning modernization efforts or not starting them at all rather than ..read more

In today’s world of complex data architectures and emerging technologies, databases can sometimes be undervalued and unrecognized. The fact is that databases are truly the engine driving better outcomes for businesses — they’re running your cloud-native apps, generating returns on your investments in AI, and the backbone supporting your data fabric strategy. IBM has been the pioneer in paving the way for data management technologies and advancements for decades, from the first commercial database to quantum computing systems. A crucial part of that journey has been the invention of IBM Db2, a ..read more

Traditional Customer Segmentation techniques involve the use of common customer features like customer income, demographics, life stage, attitude, and behavior to help segment target audiences. According to a recent IBM report, these features make up just 20% of data and the other “80 percent of data comes from previously untapped, unstructured information from the web such as imagery, social media channels, news feeds, emails, journals, blogs, images, sounds and videos. Relying only on a traditional segmentation approach misses the mark on garnering high-quality marketing opportunit ..read more

High licensing and maintenance fees Gartner, Inc. defines the TCO for enterprise software as the total cost an organization incurs to use and maintain software technology over time. To calculate TCO, companies consider direct costs, such as hardware, software and administration, and indirect costs, including human resources, project management and downtime. But there’s one key cost that is often overlooked or underestimated: ongoing licensing and maintenance fees. Why does licensing get neglected? Perhaps it’s because some vendors have made their licensing requirements and fee structures so co ..read more

Your data and AI tools are important, and outcomes are critical, but with today’s data-driven world, businesses must accelerate outcomes while improving IT cost efficiency. But how do you achieve this? First, Data and AI initiatives must have intelligent workflows where the data lifecycle can work for various personas of the organization. It’s beyond just tool collaboration and consolidation, but it is also the collaboration of teams, streamlining of processes and interoperability of capabilities that improve outcomes. Since the arrival of IBM Cloud Pak for Data two years ago, the key points i ..read more