How successful a brand is today, depends heavily on how well the organization can manage and balance the primary pillars of people, data and technology. With the workplace more diverse, dynamic and dispersed than ever, companies need to be able to focus on inclusivity at work, leveraging AI tools and data resources, and staying connected to their employees and customers alike.
Business success has looked different through different eras as the concept of success and the metrics that define it have continued to evolve. To succeed today, organizations need to adeptly manage the pillars that the business rests upon – people, data, and technology. In our roundup this week on SpiceworksNews and Insights, we turn the spotlight on the undeniable importance of supporting generational inclusivity at work, eliminating the issue of data sprawl, understanding TensorFlow and the latest programming trends in AI, and gleaning valuable insights from connected intelligence frameworks.
Read on to know more.
Enabling Generational Inclusivity at Work
We are all a part of a distinctly diverse workplace. Moreover, while there are Millennials, GenZ and even younger generations joining the workforce, the more senior generations are still a part of it too and often returning to work after a hiatus. An age difference usually comes with differences in maturity, working styles, thought processes and technological prowess. How can companies enable generational inclusivity? Chelsea Pyrzenski, chief people officer, WalkMe, outlines strategies to make each generation feel included and valued.Â
Tackling the Business Momentum-busting Problem of Database Sprawl
With companies using several special-purpose databases, there is rising complexity in moving data between the myriad systems. Rick Negrin, VP of product management, SingleStore, discusses what database sprawl is and what companies can do to avoid it. The complexity of data infrastructure is only going to increase if present trends are to be followed. How can companies protect their data from this impending mess while still making the most of its potential?
Understanding New Programming Languages for AI Applications
AI and ML are quickly becoming a part of our homes, offices, schools, and hospitals. Every aspect of our lives has come to depend in some way on these technologies. Tools like TensorFlow, used for developing ML applications, are thus gaining popularity quickly. Pohan Lin, senior web marketing and localization manager at Databricks, discusses TensorFlow in detail and the role such tools will play in a future where ML tech can predict our behavior and where we depend on digital assistants for aspects of our daily lives.
Gleaning Actionable Insights from Connected Intelligence Frameworks
For data collection to be optimized effectively, data silos need to be removed, discusses Joseph Rymsza, VP of global safety, regulatory and quality technology at IQVIA. This will help organizations glean actionable insights to strategize effectively and mitigate compliance risk, which would, in turn, yield better business success. In a world where data integrity is key, a secure, robust data platform is essential to meet strict regulatory submission requirements while enabling advanced analytics and smarter decision-making.
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