Welcome back to my SAS Users blog series CAS Action! - a series on fundamentals. If you'd like to start by learning more about the distributed CAS server and CAS actions, please see CAS Actions and Action Sets - a brief intro. Otherwise, let's learn how to rename columns in CAS tables.
Have you ever heard the phrase “beggars can’t be choosers”? Basically, it means that if you ask for something, be grateful for what you get, especially if you don’t have the means to acquire it yourself. This phrase can be widely applicable to most areas of our lives, but when
Higher education institutions are some of the most data-rich entities in the world. Postsecondary leaders need high-quality, consistent and accurate insights to make the best decisions for their institution, students and constituents. Data governance is a topic that may seem technical in nature and perhaps important to only the IT
Welcome back to my SAS Users blog series CAS Action! - a series on fundamentals. This post builds upon CAS-Action! Create Columns in CAS Tables - Part 1 by showing how to add formats and modify the length of computed columns. I'll start by building off the following code where I
Welcome back to my SAS Users blog series CAS Action! - a series on fundamentals. I've broken the series into logical, consumable parts. If you'd like to start by learning a little more about what CAS Actions are, please see CAS Actions and Action Sets - a brief intro. Or if you'd
Leonid Batkhan describes and discusses pros and cons of 3 different algorithms and SAS code implementations to calculate length of overlap of date/time intervals and integer intervals in general.
시각화 분석을 위해서는 빅데이터를 활용할 수 있어야 하며, 시각화 및 고급 분석, 셀프 서비스, 리포팅 기능을 갖춰야 합니다. 아울러 데이터 핸들링, 분석, 리포트 생성에 이르는 전 과정에서 인사이트를 확보하고자 하는 모든 이들이 자유롭게 사용할 수 있어야 합니다. SAS AI 기반의 시각화 솔루션은 완전 초보자도 자동 추천과 자동 예측 기능을 사용하여
Learn why a data catalog is so valuable in helping you find and use big data at your business.
SAS Press author Kim Chantala shows you how to to spend less time preparing data so you can lavish time on analysis.
Nancy Rausch shares 4 examples of the role data management techniques play in responding to COVID-19.
As a long-time SAS 9 programmer, I typically accomplish my data preparation tasks through some combination of the DATA Step, Proc SQL, Proc Transpose and some housekeeping procs like Proc Contents and Proc Datasets. With the introduction of SAS Viya, SAS released a new scripting language called CASL – a
Learn how to get started with self-service data prep in these go-to articles.
Read about the value of data tagging and learn best practices for doing it effectively.
Jeff Stander helps us understand the different options of preparing data for analytics.
A business glossary improves data quality – one of the top five ways it makes analytics better.
Proper data prep means faster, better analytics. Guest blogger Jenine Milum shares tips.
Natural language understanding (NLU) is a subfield of natural language processing (NLP) that enables machine reading comprehension. While both understand human language, NLU goes beyond the structural understanding of language to interpret intent, resolve context and word ambiguity, and even generate human language on its own. NLU is designed for
„Für mich heißt Internet of Things, dass hier alles rotiert wie in einem Wäschetümmler und es weder Durcheinander noch Stillstand gibt.“ Frau Dönmek hatte Lenin und mich am Werkstor in Cedorf abgeholt und uns gleich in die Halle zu ihrer Anlage geführt: „Wir arbeiten an der Kapazitätsgrenze. Was wir wegen
Finanzdienstleister haben aktuell massive Herausforderungen beim Management ihrer Daten: Der Kostendruck zwingt einerseits zu einem hocheffizienten Betrieb („run“). Zugleich wandeln sich andererseits die Prozesse im Business, Stichwort Digitalisierung („change“). Die drückenden Regeln der Aufsicht scheinen sich nicht vereinen zu lassen mit dem Anspruch der Kunden, flexibel, fix und doch datensparsam
How should a data trust process work? David Loshin elaborates.
David Loshin raises questions about what needs to be done to ensure quality analytics.
If you need more than just well-mixed data, take a look at data preparation from SAS.
Did you know that 80 percent of an analytics life cycle is time spent on data preparation? For many SAS users and administrators, data preparation is what you live and breathe day in and day out. Your analysis is only as good as your data, and that's why we wanted
Datenmanagement ist ein alter Bekannter aus der IT – und andererseits ein neuer „Hidden Champion“ im digitalisierten Unternehmen. Warum? Weil Datenintegration und -aufbereitung einerseits eine ureigene und unverzichtbare Aufgabe der IT ist, deren Bedeutung weiter wächst. Andererseits aber stehen vor dem Hintergrund von datenbasierten Geschäftsprozessen und -modellen auch die Mitarbeiter
Jim Harris considers the technical infrastructure challenges of data preparation for streaming data.
Data Preparation wird von Unternehmen bislang oft als Fleißaufgabe gesehen, die man gerne der IT überlässt. Doch weil die Fachabteilungen oftmals nicht lange auf ihre Daten warten wollen, haben dicke SQL-Bücher und Spreadsheet-Anwendungen immer noch Hochkonjunktur in den meisten Büros. Ist das sinnvoll? Nein, das ist nicht sinnvoll. Denn die
Joyce Norris-Montanari says IT and business need to work together when giving business users self-service data preparation tools.
David Loshin describes some steps you can take to ensure that self-service data preparation improves collaboration.
Phil Simon chimes in on the tendency to rely upon these tools too much.
To do their jobs well, Joyce Norris-Montanari says users doing analytical data preparation need access to both standardized and raw data.
