Analytics of Things for Insurance Industry

whitePaper | November 18, 2022

For decades, the lack of visibility into the health of our data has led to data downtime in companies around the world. When data is missing, inaccurate, or erroneous, data quality initiatives are doomed to fail, leaving enterprises at a privacy compliance and business disadvantage.

whitePaper | January 11, 2023

The world of master data management (MDM) is a complicated place to navigate and its native speakers use a language sometimes only they themselves understand. It is packed with complex descriptions, esoteric lingo and acronyms.

whitePaper | June 3, 2022

Analyzing data has been a unique business activity for at least 5,000 years, and possibly as long ago as 20,000 years. We have come a long way in how we count, summarize, analyze, predict, and prescribe upcoming courses of action in science, business, and all fields of human endeavor. In the past 75 years, the progress in how we analyze data has increased exponentially. We now regularly build analytical models and complete applications that analyze massive amounts of data.

whitePaper | August 25, 2022

Most organizations realize data governance is necessary - if not indispensable - for mitigating data risk while sustaining its longterm value. However, there’s still a fair amount of ambiguity around what exactly data governance is and how to best implement it. By definition, data governance is an enterprise-wide initiative for formalizing the processes, people, and protocols for using data. It reduces risk while increasing data’s ultimate value: consistent reusability for achieving mission critical objectives. Data governance is a strategic approach for creating unassailable trust in data throughout the enterprise.

whitePaper | November 23, 2022

Artificial intelligence (AI) and machine learning (ML), along with data analytics, are widely seen as a way to tackle everything from daily inefficiencies and low productivity, to advancing healthcare and climate change mitigation. As more organisations look to leverage their data more effectively, demand for people with data capabilities is only going to grow

whitePaper | June 16, 2022

It seems like the business world has gone crazy for machine learning (ML) and artificial intelligence (AI), viewing the technologies as the essential keys to the very future of the enterprise. In fact, a recent survey from ESIThoughtLab found that two-thirds of business leaders see AI as critically important for their future. And yet, the respondents report that only 25% of AI projects are in widespread deployment and 40% of all projects are generating negative or no returns.