Blend, cleanse and prepare data for analytics, reporting or data modernization efforts
The idea of running software in a self-contained package took off with the launch of Docker in 2013 and has become a hot topic in the application development and DevOps community. In a recent survey by Red Hat, 57 percent of companies questioned said they use containers for some workloads
Data scientists spend a lot of their time using data. Data quality is essential for applying machine learning models to solve business questions and training AI models. However, analytics and data science do not just make demands on data quality. They can also contribute a lot to improving the quality
Over the past couple of years, I've written about a variety of use cases and value props regarding SAS® Customer Intelligence 360. As powerful as words and images can be, let's transition to the ultimate show – the demo. In the forty minute video below, observe how SAS Customer Intelligence
Además de mejorar la eficiencia de las organizaciones, con el aprovechamiento del Big Data, las instituciones pueden gestionar información que los ayude a responder a las necesidades de los ciudadanos. Su uso en el sector del gobierno, por ejemplo, contribuye a mejorar la comprensión de los fenómenos sociales y apoyar
SAS Decision Manager enables you to build and test decisions to use in batch processes, real-time web applications or with SAS Event Stream Processing. In this blog, I explain how to use Rulesets in an Event Stream Process project. If you are streaming data using SAS Event Stream Processing and
Artificial intelligence (AI) offers many opportunities for innovation. It already allows us to improve traffic flows, safely manage large crowds of people at events, analyze automated MRI scans for particular diseases and disorders, and check the effectiveness of treatment. However, new privacy legislation – such as the European General Data
I am obsessed with jigsaw puzzles. Specifically, 1000-piece mystery puzzles, entertaining not just for their pictorial humor, but also for the challenge. Unlike traditional puzzles, you don't know what you are putting together because the completed puzzle isn't pictured on the box. Mystery puzzles are constructed so that you must
The reach of sports analytics is growing by the day. Increasingly, fans expect access to additional information when viewing their favourite sport. The Premier League has started to provide information about distance run, completed passes and penalty placement history. The Australian Football League shows—on live TV—the heart rate of a
Learn why Jason Simon from UNT calls data governance critical.
There's a chasm in today's business world between "can" and "should." Let's hope that gap closes soon.
Learn about the role data classification plays when governing a diversity of data policies.
Expect to lose time if you don't include a data steward in your project until you're reviewing the data model.
Recently, I worked on a cybersecurity project that entailed processing a staggering number of raw text files about web traffic. Millions of rows had to be read and parsed to extract variable values. The problem was complicated by the varying records composition. Each external raw file was a collection of
New technologies promise to achieve what no politician has yet managed in the 70-year history of the UK’s National Health Service (NHS): improving patient care while simultaneously saving money. In the government’s 10-year-plan announcement this month, far-reaching new technological measures were announced. They demonstrate just how key digital transformation will
Todd Wright says questions from the C-suite morph as the complex data and analytics landscape evolves.
Jim Harris discusses a key role of the data engineer – protecting sensitive personal data.
Recently, as a result of the EU’s General Data Protection Regulation (GDPR) and other regulations, new governance requirements for data management have emerged. These have had some interesting effects on the data preparation process. This post is the third in a series on data preparation (Data preparation in the Analytics
This post is the second in a series on data preparation based on a webinar about its role in the analytical life cycle. The first discussed how data preparation fit into the analytical life cycle. This post considers some trends in data preparation and some of the structures and processes
Guest blogger Khari Villela says data lakes are not a cure-all – they're just one part of a comprehensive, strategic architecture.
Data preparation is often seen by companies as a difficult and dangerous job, one best left to IT. However, business departments often do not want to wait for their data, so thick SQL books and spreadsheet applications are booming in most offices. This does not really make sense, however you
Data may be expanding exponentially, but this expansion in itself is not the be-all and end-all. Data is very important, but only because it enables organisations to learn more about their customers and offer them a better service. Therefore – and this is crucial – data allows organisations to make
My New Year's resolution: “Unclutter your life” and I hope this post will help you do the same. Here I share with you a data preparation approach and SAS coding technique that will significantly simplify, unclutter and streamline your SAS programming life by using data templates. Dictionary.com defines template as
David Loshin examines various aspects of data governance that are essential for regulatory compliance.
Encouraging data sharing can sometimes feel like refereeing kids on Christmas morning. “Mom said you have to SHARE!” my sister bawled, grabbing at the Game Boy in my hand as I held the toy just out of her reach. I had just gotten it as a Christmas present and had