Notes about Cutting-Edge Technologies and Everything

DataOps techniques can provide a more agile and collaborative approach to building and managing data pipelines. The pandemic has accelerated the need for data and analytics leaders to deliver data and analytics insight faster, with higher quality and resiliency in the face of constant change. Organizations need to make better-informed and faster decisions with a focus on automation, real-time risk assessment and mitigation, continuous value delivery and agility. The point of DataOps is to change how people collaborate around data and how it is used in the organization  As a result, data and analytics leaders are increasingly applying DataOps techniques that provide a more agile and collaborative approach to building and managing data pipelines. What is DataOps? Gartner defines DataOps as a collaborative data management practice focused on improving the communication, integration and automation of data flows between data managers and data consumers across an organization. “The poi...

Digital society expects its citizens to “speak data.” Unless data and analytics  leaders treat information as the new second language of business,  government and communities, they will not be able to deliver the  competitive advantage and agility demanded by their enterprises. Key Challenges ■ Poor data literacy is the second highest inhibitor to progress, as reported by respondents to Gartner’s third annual Chief Data Oficer Survey, behind culture change and just ahead of lack of t alent and skills. ■ An information language barrier exists across business units and IT functions, rooted in ineffective communication across a wide range of diverse stakeholders. As a result, data and analytics leaders struggle to get their message across and information assets go underutilized. ■ Although academic and professional programs are beginning to address the disparity in talent  and skills, in many cases they reinforce the information language barrier with narrow content...