The role of the chief information officer has evolved from managing IT to maximizing technology for business value. Many organizations launch digital transformation programs to identify and deliver the desired value but discover that digital transformation is a complex, lengthy process. Budgets and resources can be quickly exhausted with little to show for the investment. Yet business objectives remain.
Intelligent automation is a powerful tool that can help the CIO and IT leaders optimize business processes and outcomes while reducing costs, risks and errors. Automation takes many forms, each with its own applications, benefits and limitations. In a previous perspective, I shared how technology helps organizations automate processes and enhance workflow efficiency. This perspective explains the various types of automation enabled by artificial intelligence technologies and their applications...
Automation uses technology to perform tasks or functions that would otherwise require human intervention or effort. Automation has existed for decades, and it takes many forms. It handles routine tasks, freeing time for knowledge workers to perform other activities that require creativity, subjectivity or empathy. Automation can also improve the quality, efficiency and consistency of business processes as well as enhance customer satisfaction and brand loyalty.
The publication of Ventana Research’s 2023 Operational Data Platforms Value Index earlier this year highlighted the importance of incorporating analytic processing into operational applications to deliver personalization and recommendations for workers, partners and customers. This importance is being accelerated by interest in generative AI, especially large language models. The emergence of intelligent applications has impacted the requirements for operational data platforms with the need to...
Despite best intentions, many organizations still struggle with some fundamental aspects of data processing and analytics. Taking data from operational applications and making it available for analysis is a first step, but data management remains a perennial challenge. Data movement and transformation difficulties can lead to delays and data quality problems that prevent organizations from generating value from data. The inability to govern and integrate data from multiple data sources prevents...
Cloud computing has emerged as the catalyst for a shift from digital transformation to digital modernization. This technology offers many advantages, including heightened agility, cost reduction, improved collaboration, enhanced security and accelerated innovation. Hybrid and multi-cloud strategies offer distinctive strengths that enable organizations to optimize the IT infrastructure necessary for digital transformation and modernization efforts.
I previously explained the arguments in favor of adoption of distributed SQL databases, the new generation of operational data platforms designed to combine the benefits of the relational database model and native support for distributed cloud architecture. It is critical for distributed SQL vendors to engage with developers to ensure they are considering the importance of resilience that spans multiple data centers and/or cloud regions as they choose the databases that will underpin...
A lot has been written about the definition of generative artificial intelligence (AI) and large language models (LLMs), though less has been written about the business considerations for an organization to evaluate adopting and implementing these technologies. And more importantly, does the technology align with the Office of the CIO objectives and the goals of the business? The value of generative AI software must be put into terms that all stakeholders can relate to. And organizations cannot...
Data fabric has grown in popularity as organizations struggle to manage data spread across multiple data centers, systems and applications. By providing a technology-driven approach to automating data management and governance across distributed environments, data fabric is attractive to organizations seeking to simplify and standardize data management. I assert that by 2025, more than 6 in 10 organizations will adopt data fabric technologies to facilitate the management and processing of data...
The digital transformation movement was about making wholesale changes in the use of technology across all lines of business and functions. It required organizational change on a large scale, including adapting the organization’s culture, retraining or rehiring the workforce and process realignment. Change management and a significant time commitment to implement change were necessary while maintaining existing operations.
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