Blend, cleanse and prepare data for analytics, reporting or data modernization efforts
Jim Harris shares examples of how and why AI applications are dependent on high-quality data.
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
The broad CCPA definition of personal information could open a can of worms for compliance and governance.
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
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
Jim Harris says curating AI’s curriculum is the responsibility of data stewards.
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.
불과 몇 년 전 까지만 해도 ‘데이터 사이언티스트’라는 단어는 많은 사람들에게 꽤나 생소한 단어였을 것입니다. 하지만 4차 산업혁명이 이미 산업 전반에 깊숙이 자리한 오늘날, 빅데이터 분석이 핵심 역량으로 부상하며 데이터 과학자(data scientist)의 인지도 역시 굉장히 높아졌습니다. 단순히 인지도뿐만이 아닙니다. 세계 최대 취업 정보 사이트 글래스도어(Glassdoor)가 발표한 2019년 ‘미국 최고 직업
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
Todd Wright says questions from the C-suite morph as the complex data and analytics landscape evolves.
Brush up on the latest news around data privacy. Todd Wright shares his top 10 picks.
Jim Harris discusses a key role of the data engineer – protecting sensitive personal data.
Guest blogger Khari Villela says data lakes are not a cure-all – they're just one part of a comprehensive, strategic architecture.
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.
Joyce Norris-Montanari discusses data engineers in the second of her two-part series.
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
Phil Simon raises two key questions to ask in his second post on data literacy.
K(o)ennen Sie schon „DevOps“? Machen Sie SAS? Dann lohnt sich eventuell ein frischer Blick auf die Kombination! Denn immer mehr Unternehmen probieren, ihren produktiven Betrieb auch in die Hände der Software-Entwickler zu legen (2 von 3 laut Jenkins) – speziell in der Analyse, insbesondere beim agilen Modellieren und dem Veredeln
By now you’ve seen the headlines and the hype proclaiming data as the new oil. The well-meaning intent of these proclamations is to cast data in the role of primary economic driver for the 21st century, just as oil was for the 20th century. As analogies go, it’s not too
The data revolution is causing disruption everywhere. Even governments are feeling the effects. While the public sector may be less prepared for the impending changes, government has good reasons to embrace the data revolution. First, governments have been collecting data for years. They have lots of data. This supports programs,
Todd Wright shares results of a SAS survey about consumers' data privacy concerns.
Phil Simon chimes in on the increasingly important topic of data literacy.
Data scientists need good skills in communication, data mining, data wrangling and more. Joyce Norris-Montanari explains.
Jim Harris says data stewards are essential to analytics, providing life cycle management for data across the enterprise.
