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The Value of Options in the Data Integration and Analytics Supply Chain

Over the course of my career in Financial Services, I have struggled with how few options I really had when it came to delivering the right information, to the right people, at the right time. It sounds sort of ridiculous considering how much time, money and effort the firms, for which I worked, spent on data warehouses, reporting systems, business intelligence tools and advanced analytics.

How Florida State University is Boosting Student Success and Addressing Data Challenges

For public universities, metrics such as retention rate and graduation rate are important indicators for standing out in the competitive landscape. These success metrics are paramount to bringing in more students, making them successful, and continuing to grow a strong alumni network.

Fresh Features: automated data discovery goes prime time

Here’s part 2 of ‘Fresh Features’ of Yellowfin 9. And this week, we’re looking at Signals. Signals is Yellowfin’s unique and powerful automated data discovery product. It will automatically scan your dimensional data and find any significant changes in your data. Then, it automatically sends you an alert, complete with analysis and correlations to help you take swift action to nip issues in the bud or build on successes.

From GDPR to CCPA, the right to data access is the Achilles' Heel of data privacy compliance and customer trust - Part 3

In the first and second blog posts we explained the importance of DSAR as well as how the customer experience can be impacted if the process is not well managed. In this last part, we will go through a few tips that could help you to be DSAR champions!

How Cloudera Enables R Users to Optimize Their Data Science and Machine Learning Workflows

This week, R users from around the world convene in San Francisco for rstudio::conf 2020. With a packed agenda of new package announcements and case studies highlighting successful applications of R across different industries, it’s evident that R and the ecosystem of tools around it make up a vital part of the data science and machine learning landscape.

Deep Learning for Anomaly Detection

We are excited to release Deep Learning for Anomaly Detection, the latest applied machine learning research report from Cloudera Fast Forward Labs. Anomalies, often referred to as outliers, are data points or patterns in data that do not conform to a notion of normal behavior. Anomaly detection, then, is the task of finding those patterns in data that do not adhere to expected norms. The capability to recognize or detect anomalous behavior can provide highly useful insights across industries.

Understanding Healthcare's New Industry Imperative: Data Chain of Custody

One of the first recorded medical devices was the stethoscope in 1816. Fast forward more than a century to 2019, where the world witnessed the creation of an award-winning multi-sensor, implantable cardiac device able to predict potential heart failure weeks in advance. The data and analytics streamed and analyzed from new connected devices are transforming healthcare as we know it. However, a real challenge in this environment is the sheer volume and scope of data that must be managed and protected.

Fresh Features: Yellowfin 9 Charts

With so much packed into the latest Yellowfin 9 release, we figured it would be great to let you know about some of the coolest features (which will really transform how you do analytics!) in this series of blog posts - Fresh Features. At Yellowfin, we’re super excited that you will be benefiting from the huge amount of work our development team have been doing behind the scenes to complete revamp Yellowfin’s look, feel, and functionality.

Insurance in 2020 & Beyond - Learning from the past decade to plan for the next

Like many other people, I used time over the recent holidays to clean out and organize my digital files. In that process, I finally trashed the speaking notes for a panel I participated in at SMA’s (Strategy Meets Action) first summit in 2012 when I worked at a large global insurer. During that session, a gentleman in the audience asked me what I thought about “big data” and its implications for Insurance.