In these uncertain times, organizations need the ability to adjust their plans and forecasts in real time to address changing demands and maintain business continuity. Lengthy, labor-intensive, siloed planning processes, often the result of using spreadsheets or sub-par planning software, are too
IDC’s report, “Choosing the Right Database Technology in the Age of Digital Transformation” highlights the expanse of data management options as well as how that can cause confusion. Having clarity when looking to build new data applications or modernize workloads already in existence is essential
More companies are choosing to implement multicloud platforms that include software as a service (SaaS) due to the many opportunities, advantages, and benefits they provide. However, a recent ISG report, “Multi-Cloud Adoption Accelerates,” notes that a lack of proper planning could introduce
A modern enterprise IT platform often needs to be all things to all people: to accommodate both new and legacy workloads and be managed by both internal and external experts. To achieve this breadth of capabilities, many businesses have augmented their existing platforms with cloud capabilities
In a previous blog, I explained how data science capabilities, massive parallel processing (MPP)
and usability improvements in data warehouse appliances can help the bottom line—and why old-fashioned architectures might not cut it. But what does that look like in practice?
Research firm Quark +
How do businesses address the challenges of growing volume and variety of data? How can I introduce new data sources and workloads into my architecture? How do I achieve better time to value and agility in my infrastructure?
If you're wrestling with these and other related questions, I recommend