Since the widespread adoption of the internet and cloud computing, data growth has exploded: today every 60 seconds, at least 160 million emails are sent around the world, and 1,820 Terabytes of data is created. (more)
Data lakes are everywhere now that cloud services make it so easy to launch one. Secure cloud data lakes store all the data you need to become a data-driven enterprise. And data lakes break down the canonical data structures of enterprise data warehouses, enabling users to describe their data better, gain better insights and make better decisions. (more)
Four ways enterprises can strengthen their data management processes with the cloud. Digital transformation is the top priority for over 40 percent of CEOs and corporate boards, and most CEOs are leading the initiative personally, according to a recent survey by British Telecom. And it’s no wonder—because the excitement is driven by what Mckinsey & Co. calls “a mass extinction event”—where over 50 percent of Fortune 500 companies have been acquired, merged, or have declared bankruptcy since 2000. (more)
Four key areas of your data worth looking into for workplace diversity transformation. For decades, organizations around the world have suffered from a lack of workforce diversity in race, gender, age, and more. In America alone, men named John outnumber all women in leadership roles. (more)
The average enterprise manages over 350 Terabytes of data—seven times as much as a small business. With so much data, modern enterprises should seek creative and smart ways to manage the wealth of information they collect on a daily basis, while being mindful about important factors like compliance. With the help of AI and Machine Learning, an enterprise virtual assistant can tap into enterprise data and help augment common human processes across many departments, including finance, HR, and leadership. Below is a step by step guide to optimizing your infrastructure for virtual assistants, and specific use cases. (more)
It has been well over a decade since the cloud was popularized by giants like Amazon. With cloud technology now widely adopted across many industries, enterprises, in particular, have been looking at a cloud-first approach to their infrastructures—83% of enterprise architecture workloads will be in the cloud by 2020. And as data continues to grow at historical rates (globally increasing 61% to 175 Zettabytes by 2025), it is now more important than ever for enterprises to enable a virtually limitless influx and analysis of data in the cloud. (more)
As we approach the second half of 2020, we’re gaining a good sense of how this year is shaping up in terms of the biggest trends for enterprise professionals. Here’s a quick overview of just a few of the topics we believe are going to be transformational for technology professionals and organizations working in artificial intelligence, big data, and the cloud. (more)
Some 60 years ago the early adopters of data-driven enterprise implemented Material Requirements Planning (MRP) to improve manufacturing throughput and efficiency. For the first time plant managers used a data platform to foresee outcomes based on optimized plans and schedules. From this great success, the data-driven enterprise evolved to Enterprise Resource Planning (ERP) and Enterprise Data Warehousing (EDW) to meet the ever-growing demands for online reporting, analytics, and improved business intelligence. (more)
Nearly every organization today is data-driven, and the pharmaceutical industry is no exception — however, traditional data technologies and methods have failed the industry, leading to poor efficiency and optimization, often leading to high costs. (more)
This is the time-tested axiom of risk management that holds true across business verticals, from insurance and banking to healthcare and manufacturing. If you can identify risk by predicting failure, you can, to a large extent, prevent undesirable outcomes such as litigation, fraud, and lost revenue. (more)
