All library posts in SAS Support Communities

Re: Modeling Repeated Measures in Field Trials

JLGenova — Sat, 27 Apr 2024 16:01:02 GMT

Hello experienced!

I've tried everything to analyze my data. I have data from blood samples taken at 3 times (hours, i.e. T1,T2,T3), 2 blocks (rounds in time), and a double factorial (Zn levels x Zn sources), with 5 pigs in each block sampled 3 times. When I try to analyze as repeated measures in time, the following message appears in Proc Mixed: “An infinite likelihood is assumed in iteration 0 because of a nonpositive definite estimated R matrix in SAS”.
I'd really appreciate support, because I've tried everything. In Glimmix the data runs, but the degrees of freedom don't look right.

Re: 4 Tips for a Successful Start with SAS Workload Management

touwen_k — Fri, 26 Apr 2024 08:57:58 GMT

@EdoardoRiva As we do not have experience yet with SAS Workload Orchestrator, we would like to know what the best practice is. We are not going to use preemption yet as you have to find out how to program jobs to restart. So if we schedule priority jobs and the other less important jobs fail because they are too long in a pending state, what is best practice if you want these less important jobs to run as well? Is extending the default time-out of compute session the best practice or are there another solutions? Is it possible to advise as we are eager to use these feature very soon.

Re: SAS® Workload Orchestrator- Associate Kubernetes Cluster Nodes With Queues

touwen_k — Fri, 26 Apr 2024 08:55:13 GMT

@GillesChrzaszcz

As we do not have experience yet with SAs Workload Orchestrator, we would like to know what the best practice is. We are not going to use preemption yet as you have to find out how to program jobs to restart. So if we schedule priority jobs and the other less important jobs fail because they are too long in a pending state, what is best practice if you want these less important jobs to run as well? Is extending the default time-out of compute session the best practice of are there another solutions? Pls advise as we are eager to use these feature.

Re: How to create an audience within SAS 360 Audiences and its advantages for users

LeonoraG — Fri, 26 Apr 2024 08:01:25 GMT

Great news @jcawesome!!

I hope it can make the difference in your daily activities and accelerate the value you are getting from the solution. We are here if you need support!

Re: How to create an audience within SAS 360 Audiences and its advantages for users

jcawesome — Fri, 26 Apr 2024 03:46:56 GMT

Hi @LeonoraG

Yes I am well. Thanks for sharing. I hope you are too.

Thank you for the update regarding Audiences. We have access now to Audience Manager after raising it to the right person in SAS. We're definitely looking forward to the "On-premise Direct Segment Maps" feature in Audiences. This will provide alot of confidence in using Audiences if Engage Direct is already in place (especially since Audiences is currently limited to the possible data sources available).

Regards,

Advanced configuration of a Shock in SAS Risk Factor Manager

MihaiViju — Thu, 25 Apr 2024 20:33:07 GMT

Advanced configuration of a Shock in SAS Risk Factor Manager

Wavelet Analysis using SAS/IML: Thresholding the Detail Coefficients to Remove High-Frequency Noise

AriZitin — Fri, 26 Apr 2024 15:18:39 GMT

Recently in the SAS Community Library: SAS' @AriZitin shows you how wavelets can be used to remove unwanted high-frequency noise from digital signals.

Don’t Listen to Ron White. Cluster Profiling is Right!

MarcHuber — Thu, 25 Apr 2024 19:56:48 GMT

Don’t Listen to Ron White. Cluster Profiling is Right!

Re: Tips and strategies for the A00-231 SAS Base Programming Performance-Based Certification Exam

Mark2010 — Thu, 25 Apr 2024 18:18:18 GMT

Yes, I would say a 44/67 would warrant rescheduling that exam a bit further out, especially if you are struggling with the lab activities. Keep reviewing the topics of the content guide until you are comfortable with all of them.

Re: Tips and strategies for the A00-231 SAS Base Programming Performance-Based Certification Exam

PriyaB — Thu, 25 Apr 2024 04:39:09 GMT

Thank you mark for explaining and correcting me as well. As you have mentioned that "The practice exam should be used as a final check of your knowledge after you feel you have adequate learned the material" that means as I have scored 44/67 so I have not adequate amount of knowledge to appear on exam. That means I still need to work on my skills and take time to appear on the exam Right? because within a week I was planning to appear in the exam.

SAS Viya at SAS Innovate - What’s New in Data & AI

thiago — Wed, 24 Apr 2024 21:22:12 GMT

Want to know what’s new in SAS Viya? In this SAS Viya Release Highlights Show, we’re packing our bags and heading to Las Vegas to showcase the latest SAS Viya announcements. We’ll be covering what’s new when it comes to SAS Viya Workbench, generative AI, copilots and even dive into topics like quantum computing. You’ll hear from SAS experts about how SAS is investing in these exciting technology areas.

Re: Tips and strategies for the A00-231 SAS Base Programming Performance-Based Certification Exam

Mark2010 — Wed, 24 Apr 2024 13:03:17 GMT

@PriyaB - Let's change the paradigm here. Let's not think of it as 'cracking' the exam. What you are trying to do is learn & master the skills that are tested on the exam. I'm sure that is what you meant, just using different words.

This collection of skills has been determined to be critical skills that a new SAS programmer needs to be successful in their roll. Learning the content takes time and the starting point is not the practice exam. The practice exam should be used as a final check of your knowledge after you feel you have adequate learned the material. I'll refer you to these blog posts to help you find the process and resources that we recommend (such as the content guide, training, and prep guides, and practicing SAS):

Steer clear of third party 'practice' exams - they will mislead you and diminish your performance on the actual exam. They are created by unscrupulous individuals trying to take advantage of students.

Re: Tips and strategies for the A00-231 SAS Base Programming Performance-Based Certification Exam

PriyaB — Wed, 24 Apr 2024 12:50:55 GMT

Hi Mark,

Is there any other way except 1 practice exam which is freely available once you enroll for the programming course for preparation or to know where I am standing? like how much preparation I need to crack "Base sas :Perform based exam". please share if there any other sample test or practice video or pdf may be that would be really beneficial and helpful.

Thanks in Advance.

Regards

Priya

Re: How to prompt for a date range in a SAS VA report – Example 3 Drop-down list

Olivier_Deprez — Wed, 24 Apr 2024 12:46:20 GMT

Merci pour toutes ces explications bien explicites.
Mais les périodes de validité se chevauchent, si je choisi une date_begin bien précise, la date de fin va etre filtrée selon ce qu'il y a dans la table.
Alors qu'il y a peut etre une autre ligne qui pourrait etre afichée.
Voici une partie des dates de validité

Re: SAS Viya log-cleanup playbooks

ElsayedAtef — Wed, 24 Apr 2024 10:59:57 GMT

This is a very interesting topic and a great explanation. much appreciated.

there is another part most of my customers complain about it. Service Log files themselves cleaning/log rotation.

for instance: in AML/VI orders, we can notice that the indexing service's latest log can reach 50GB, and accordingly to clean this log need to stop clean then start services.

Most customers seek Log rotation automatically configure "no human intervention " Also they don't have an option for a planned restart for SAS every specific period (In a Weekend or so, Frequency)

Maximize Coding and Data Freedom with SAS, Python and Databricks

larsarne — Wed, 24 Apr 2024 08:49:18 GMT

Freedom of choice is now more important than ever when you want to get the most out of your data and AI specialists. Boasting compatibility with 80+ data sources, including widely adopted open data standards and formats such as Parquet and ORC, the possibilities for data access are virtually limitless with SAS Viya. Check out this blog to look into how this freedom also extends to coding language with SAS Viya - in particular Python.

Re: How to create an audience within SAS 360 Audiences and its advantages for users

LeonoraG — Tue, 23 Apr 2024 15:19:04 GMT

Hi @jcawesome, hope you are well.

As at the moment the data sources for Audiences can be the ones you mentioned (Snowflake and GBQ), as of now we can also support Audience creation and import through API. Next in the roadmap we have On-premise Direct Segment Maps available in Audience Manager, support for Azure SQL, AWS Redshift and others. Hope it helps to understand a bit more of what we have now and what is coming for Audiences capabilities.

Audiences is available for all regions, please be in touch with your SAS Account team to explore how to make this capability available at your tenant.

Kind regards,

Leonora.

Why Do I Need SAS Intelligent Decisioning and SAS Model Manager to Achieve Analytics Success?

Crystal_Baker — Tue, 23 Apr 2024 14:27:49 GMT

Watch this Ask the Expert session to learn how the integration between these SAS solutions helps MLOps engineers, data scientists and business users improve analytics success by working together.

Watch the Webinar

You will learn about:

How SAS® Viya® supports enterprise team collaboration to efficiently build AI and analytics systems.
Core functionality of SAS Model Manager for MLOps engineers, including registration, testing, governance, monitoring and integration with solutions such as SAS Intelligent Decisioning.
Core functionality of SAS Intelligent Decisioning for decision analysts, including rule building, ML/AL implementation, code support, orchestration and deployment.

The questions from the Q&A segment held at the end of the webinar are listed below and the slides from the webinar are attached.

Q&A

After model decay is detected, what are the next steps?

We didn't dive too deep into model decay in this example, but when we develop our machine learning models, they are just representations of a pattern that they detect in the world around us at a specific time point. Our world is ever changing, new things appear all the time, things phase out. So, when our models are trained to work with a specific pattern at a single point in time, it becomes less effective at prediction when that pattern is no longer useful. This is a process called model decay.

Within our SAS model management tool, we have capabilities for setting thresholds for sending tasks or notifications whenever your model decay doesn't meet that threshold, so that users can come in and decide what's next. Do they retrain their models in SAS Model Studio? Do they select a challenger model that looks like it's still performing as well as the champion or better? We do support performance monitoring for multiple models so you can share those challenger models side-by-side those champions. You can quickly see it's time to replace my production model with a challenger or decide to retire the project to build new models. There are a few different options that are available, but we do help with letting individuals know when it is time to address model decay. From there, we can replace production models when we go to deploy; there's a toggle to replace the model or replacing the model with the same name. Or we can just let Crystal know that it's time to swap out that model, as you've seen in the demonstration. We can even very quickly share our models. There's a share button, so we can even share it over teams if I want to speed things along.

What else can I do to ensure my decision flows leverage Responsible and Trustworthy AI best practices?

There are a few things that we can do to better make sure that our decisions fall into that responsible and trustworthy AI category. First, when we are using models within our decisions, we want to make sure that we're working with the data scientists or whoever is developing and maintaining those models. Because a large part of how our decisions depend on the outputs those models. So, we need to make sure that our models are up to date. If there needs to be retraining, retrain the models before our models get stale. In addition, we also want our decisions to be transparent and be able to explain how a decision was made. With SAS intelligent decisioning, there's a few ways we can do this. When we publish decisions, navigate to the Deployments tab to manage the different deployed decisions that we have. We can understand where they've been deployed to, who's deployed them, and the date of publishing. Also, with this, we can get a better understanding of how the decision is running and what it is using to make decisions by easily generating a report that helps us create better transparent decisions.

We can also track decisions with decision path analysis and rule-fired analysis. We can also track decisions with decision path analysis and rule-fired analysis and the output decision variables. With this data we can do analysis to better understand how decisions are made and ensure that we are making responsible decisions.

While developing category models and churn models, do you actually code or is it done by SAS Viya itself?

What's nice about SAS Viya is that it's almost like a choose your own adventure when it comes to how you develop your models. It can be yes code, no code, low code, or somewhere in between. For this particular example, these models that we use were developed using a tool called SAS Model Studio, which is a GUI (Graphical User Interface) based approach where you don't have to do any coding yourself. You can drag and drop nodes into a pipeline, you can use automated machine learning to develop that pipeline for you. You don't actually have to code at all to build out these models we used today. But that doesn't mean you can't code. Users can also code in SAS and Python or R to develop their models. We have a few different options for those users. It is nice and flexible so you can start to bring together skill sets across your organization, whether they can code and enjoy it and just want to stick with that method, or if they prefer to iterate very quickly using a drag and drop tool. There is a variety of different options for how these models can be developed.

How can I learn more?

Sophia: Besides joining us at SAS Innovate, both Model Manager and Intelligent Decisioning are very active on SAS communities. I post under the SAS Model Manager label whenever we have new features, and many of our experts in the community post interesting use cases they come across, and interesting problems they've solved. So, it's definitely worthwhile to subscribe to the SAS Model Manager label on SAS Communities.

Crystal: SAS Communities is always a good one for Model Manager or SAS Intelligent Decisioning. We have some blogs on the sas.com page and then also in SAS Communities. I also suggest taking a look at the previous because we have a lot of good tutorials or how to videos that show you how we move throughout either SAS Model Manager and SAS Intelligent Decisioning. The previous webinars can be especially helpful if you are new to either of these solutions.

SAS Model Manager Communities Link: SAS Communities: SAS Model Manager

SAS Intelligent Decisioning Communities Link: SAS Communities: Decisioning

SAS Ask the Expert Webinars: Ask the Expert - SAS Support Communities

Did you use logistic regression to develop the model?

In this example, the category model is a rules-based text model, and the churn model is a gradient boosting model, but logistic regression models and many other machine learning models are supported.

Recommended Resources

Essential Functions of SAS Intelligent Decisioning

Manage Models in SAS Viya Training

SAS Intelligent Decisioning Homepage

SAS Model Manager Homepage

SAS Viya Homepage

Please see additional resources in the attached slide deck.

Want more tips? Be sure to subscribe to the Ask the Expert board to receive follow up Q&A, slides and recordings from other SAS Ask the Expert webinars.

Email Authentication Mechanisms - an Introduction

DietmarBurgfeld — Tue, 23 Apr 2024 09:10:39 GMT

Email Authentication Mechanisms – an Introduction:

Email authentication is a set of techniques and protocols designed to verify the legitimacy of an email message and to prevent email fraud, such as phishing and spoofing. The goal is to ensure that the sender of an email is who they claim to be and that the content of the email has not been tampered with during transit. Email authentication helps in building trust between senders and recipients, reduces the likelihood of spam and phishing attacks, and improves overall email security. Several key authentication mechanisms are commonly used in email:

SPF (Sender Policy Framework): SPF is a framework that allows domain owners to specify which mail servers are authorized to send emails on behalf of their domain. This is achieved by publishing SPF records in the DNS (Domain Name System). Receiving mail servers can then check the SPF records to verify that an incoming email is sent from an authorized server.
DKIM (DomainKeys Identified Mail): DKIM is a method for associating a domain name with an email message, allowing a person, role, or organization to claim some responsibility for the message. It involves the use of cryptographic signatures that are added to the email headers. The receiving mail server can verify the signature using the public key published in the DNS.
DMARC (Domain-based Message Authentication, Reporting, and Conformance): DMARC builds on SPF and DKIM by providing a way for domain owners to set policies for how their emails should be handled if they fail authentication checks. DMARC also includes reporting features that allow domain owners to receive feedback on email authentication failures.
BIMI (Brand Indicators for Message Identification): BIMI is a relatively newer standard that enables organizations to display their brand logos next to authenticated emails in the recipient's inbox. It relies on the combination of DMARC and a verified logo file that is referenced in the DNS.

By implementing these authentication mechanisms, email senders can demonstrate the legitimacy of their messages, and recipients can have greater confidence that the emails they receive are not forged or manipulated. Additionally, DMARC policies help prevent attackers from abusing a brand's domain for malicious purposes. Overall, email authentication is a crucial aspect of modern email security and is widely used to combat various forms of email fraud.

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SPF:

Sender Policy Framework (SPF) is an email authentication method designed to detect forged sender addresses during the delivery of the email. It is part of the broader set of technologies aimed at preventing email spoofing and phishing. SPF allows the owner of a domain to specify which mail servers are authorized to send emails on behalf of that domain.

How SPF works:

DNS Records: The domain owner publishes SPF information in the Domain Name System (DNS). SPF records are TXT records that contain information about the authorized mail servers for that domain.
Receiving Mail Server Checks SPF Record: When an email is received, the receiving mail server can check the SPF record of the sender's domain by querying the DNS for the SPF TXT record.
Validation: The receiving mail server compares the IP address of the sending server against the list of authorized IP addresses specified in the SPF record. If the IP address matches one of the authorized servers, the email passes the SPF check.
Handling Failures: If the SPF check fails, the receiving mail server can take various actions based on the SPF policy specified by the domain owner. This might include marking the email as suspicious, moving it to the spam folder, or even rejecting it outright.

SPF records use a simple syntax to specify which IP addresses are allowed to send emails on behalf of a domain. For example, a basic SPF record might look like this:

In this example:

v=spf1 indicates the SPF version.
ip4:192.168.1.1 allows the specific IP address 192.168.1.1 to send emails.
include:spf.example.com includes the SPF record of another domain (spf.example.com) in the check.
-all signifies a strict policy, indicating that if the IP address is not listed in the SPF record, the email should be treated as unauthorized.

SPF is just one component of email authentication. Other techniques like DKIM (DomainKeys Identified Mail) and DMARC (Domain-based Message Authentication, Reporting, and Conformance) are often used in conjunction with SPF to enhance email security. These mechanisms collectively help in reducing spam, phishing, and email spoofing.

DKIM

DKIM functions as a cryptographic authentication method. It allows email receivers to verify that an email claiming to have come from a specific domain was indeed authorized by the owner of that domain. This verification process occurs by validating the cryptographic signature included with the email.

How DKIM works:

Message Signing: When an email is sent, the sending mail server adds a unique DKIM signature header to the message. This signature is created using a private cryptographic key associated with the sending domain.

Public Key Retrieval: The receiving mail server, upon receiving the email, retrieves the public key from the DNS records of the sender's domain.
Signature Verification: Using the public key, the receiving server verifies the DKIM signature attached to the email. If the signature is valid and the message has not been altered in transit, the email is deemed authentic.

Benefits of DKIM

Enhanced Email Deliverability: DKIM-signed emails are less likely to be marked as spam or phishing attempts by email filters, thus improving deliverability rates.
Mitigation of Spoofing and Phishing: By verifying the authenticity of the sender, DKIM helps in reducing the risk of email spoofing and phishing attacks.
Builds Trust with Recipients: Implementing DKIM instills confidence in recipients that the emails they receive are indeed from legitimate senders, fostering trust and credibility.
Compliance Requirements: DKIM compliance is often a prerequisite for adhering to various industry regulations and standards, such as GDPR (General Data Protection Regulation) and HIPAA (Health Insurance Portability and Accountability Act).

DMARC

DMARC, which stands for Domain-based Message Authentication, Reporting, and Conformance, is an email authentication protocol and reporting system designed to combat email phishing and fraud. DMARC builds on the existing email authentication mechanisms SPF (Sender Policy Framework) and DKIM (DomainKeys Identified Mail) by providing a way for domain owners to specify how email failures should be handled and by offering reporting capabilities.

Key components of DMARC:

Authentication Mechanisms:

SPF (Sender Policy Framework): Verifies that the sending mail server is authorized by the domain owner.
DKIM (DomainKeys Identified Mail): Ensures that the email content has not been tampered with and is signed by the private key associated with the sending domain.

DMARC Policies:

Domain owners publish DMARC policies in their DNS records. These policies instruct receiving mail servers on how to handle emails that fail SPF and/or DKIM checks.
DMARC policies include:
- p=none (Monitoring Mode): The domain owner is in "monitoring" mode, and no specific action is taken when authentication fails. However, detailed reports are generated and sent to the domain owner.
- p=quarantine: The email should be treated with suspicion. Receiving mail servers may choose to deliver the email to the recipient's spam or quarantine folder.
- p=reject: The email has failed authentication, and the receiving mail server should reject it outright. The strictest setting.

Reporting:

DMARC provides detailed reports (DMARC reports or aggregate reports) to domain owners about email authentication activity. These reports include information on emails that passed or failed authentication, including the sending IP addresses, SPF results, DKIM results, and more.
These reports enable domain owners to monitor and analyze email authentication activity, identify potential issues, and take corrective actions.

DMARC helps prevent email spoofing and phishing attacks by providing a mechanism for domain owners to assert control over their domains and protect their brand reputation. It also allows them to receive valuable feedback on email authentication failures, helping to improve the overall security of their email infrastructure. Many large email providers and organizations have adopted DMARC as part of their email security strategy.

BIMI

BIMI, which stands for Brand Indicators for Message Identification, is an email authentication standard that aims to enhance email security and brand visibility. BIMI allows organizations to display their brand logos next to authenticated emails in the recipient's inbox. This visual indicator helps users quickly recognize legitimate emails from trusted senders and builds trust in the email communication.

Key components of BIMI:

DMARC Authentication:

BIMI relies on the DMARC (Domain-based Message Authentication, Reporting, and Conformance) protocol for email authentication. DMARC helps ensure that the sender's domain is legitimate and prevents email spoofing and phishing attacks.

Verified Mark Certificates (VMC):

To participate in BIMI, organizations need to obtain a Verified Mark Certificate (VMC). A VMC is a digital certificate that confirms the association between the sender's domain, the brand logo, and the DMARC authentication. It acts as a proof of authenticity for the brand logo.

DNS Records:

BIMI information is published in the DNS (Domain Name System) records of the sender's domain. This includes the location of the brand logo and the associated VMC.

Display of Brand Logo:

When an email from a BIMI-enabled sender passes DMARC authentication, and the recipient's email client supports BIMI, the brand logo is displayed next to the email in the recipient's inbox. This provides a visual confirmation of the sender's authenticity.

The benefits of BIMI include:

Brand Trust: The presence of a recognizable brand logo next to an email can enhance trust and help users distinguish legitimate emails from potential phishing attempts.
Improved Email Deliverability: BIMI is an additional incentive for organizations to implement DMARC authentication. Email providers may prioritize the delivery of authenticated emails, contributing to better deliverability rates.
Reduced Phishing Risks: By visually verifying the authenticity of the sender, BIMI helps users identify phishing attempts more easily, reducing the risk of falling victim to fraudulent emails.

BIMI is an emerging standard, and its adoption is gradually increasing. As more organizations implement DMARC and obtain VMCs, BIMI has the potential to become a valuable tool in the fight against email fraud while providing a better user experience in email communication.

Comparing Alerting Capabilities of Alertmanager with Grafana

AjmalFarzam — Mon, 22 Apr 2024 20:12:55 GMT

Comparing Alerting Capabilities of Alertmanager with Grafana