SAS administrators

11月 202020
 

If you’re like me and the rest of the conference team, you’ve probably attended more virtual events this year than you ever thought possible. You can see the general evolution of virtual events by watching the early ones from April or May and compare them to the recent ones. We at SAS Global Forum are studying the virtual event world, and we’re learning what works and what needs to be tweaked. We’re using that knowledge to plan the best possible virtual SAS Global Forum 2021.

Everything is virtual these days, so what do we mean by virtual?

Planning a good virtual event takes time, and we’re working through the process now. One thing is certain -- we know the importance of providing quality content and an engaging experience for our attendees. We want to provide attendees with the opportunity as always, but virtually, to continue to learn from other SAS users, hear about new and exciting developments from SAS, and connect and network with experts, peers, partners and SAS. Yes, I said network. We realize it won’t be the same as a live event, but we are hopeful we can provide attendees with an incredible experience where you connect, learn and share with others.

Call for content is open

One of the differences between SAS Global Forum and other conferences is that SAS users are front and center, and the soul of the conference. We can’t have an event without user content. And that’s where you come in! The call for content opened November 17 and lasts through December 21, 2020. Selected presenters will be notified in January 2021. Presentations will be different in 2021; they will be 30 minutes in length, including time for Q&A when able. And since everything is virtual, video is a key component to your content submission. We ask for a 3-minute video along with your title and abstract.

The Student Symposium is back

Calling all postsecondary students -- there’s still time to build a team for the Student Symposium. If you are interested in data science and want to showcase your skills, grab a teammate or two and a faculty advisor and put your thinking caps on. Applications are due by December 21, 2020.

Learn more

I encourage you to visit the SAS Global Forum website for up-to-date information, follow #SASGF on social channels and join the SAS communities group to engage with the conference team and other attendees.

Connect, learn and share during virtual SAS Global Forum 2021 was published on SAS Users.

11月 192020
 
SAS loves data. It's our raison d'être. We've been dealing with Big Data long before the term was first used in 2005. A brief history of Big Data*:

  • In 1887, Herman Hollerith invented punch cards and a reader to organize census data.
  • In 1937, the US government had a punch-card reading machine created to keep track of 26 M Americans and 3 M employers as a result of the Social Security Act.
  • In 1943, Colossus was created to decipher Nazi codes during World War II.
  • In 1952, the National Security Agency was created to confront decrypting intelligence signals during the Cold War.
  • In 1965, the US Government built the first data center to store 742 M tax returns and 175 M sets of fingerprints.
  • In 1989, British computer scientist Tim Berners-Lee coined the phrase "World Wide Web" combining hypertext with the Internet.
  • In 1995, the first super-computer is built.
  • In 2005 Roger Mougalas from O'Reilly Media coined the term Big Data.
  • In 2006, Hadoop is created.

From

To


The story goes on to the tune of 90 percent of available data today has been created in the last two years!

As SAS (and the computing world) moves to the cloud, the question of, "How do I deal with my data (Big and otherwise), which used to be on-prem, in the cloud?" is at the forefront of many organizations. I ran across a series of relevant articles by my colleague, Nicolas Robert, on the SAS Support Communities on SAS and data access and storage on Google Cloud Storage (GCS). This post organizes the articles so you can quickly get an overview of the various options for SAS to access data in GCS.

Accessing Google Cloud Storage (GCS) with SAS Viya 3.5 – An overview

As the title suggests, this is an overview of the series. Some basic SAS terminology and capabilities are discussed, followed by an overview of GCS data options for SAS. Options include:

  • gsutil - the "indirect" way
  • REST API - the "web" way
  • gcsfuse - the "dark" way
  • BigQuery - the "smart" way.

In the overview Nicolas provides the pros and cons of each offering to help you decide which option works best for your situation. Below is a list of subsequent articles providing technical details, specific steps for usage, and sample code for each option.

Accessing files on Google Cloud Storage (GCS) using REST

The Google Cloud Platform (GCP) provides an API for manipulating objects in Google Cloud Storage. In this article, Nicolas provides step-by-step instructions on using this API to access GCS files from SAS.

Accessing files on Google Cloud Storage (GCS) using SAS Viya 3.5 and Cloud Storage FUSE (gcsfuse)

Cloud Storage FUSE provides a command-line utility, named “gcsfuse”, which helps you mount a GCS bucket to a local directory so the bucket’s contents are visible and accessible locally like any other file. In this article, Nicolas presents rules for CLI usage, options for mounting a GCS bucket to a local directory, and SAS code for accessing the data.

SAS Viya 3.5 and Google Cloud Storage (GCS) Performance Feedback

In this article, Nicolas provides the results of a performance test of GCS integrated with SAS when accessed from cloud instances. New releases of SAS will only help facilitate integration and improve performance.

Accessing files on Google Cloud Storage (GCS) through Google BigQuery

Google BigQuery naturally interacts with Google Cloud Storage using popular big data file formats (Avro, Parquet, ORC) as well as commodity file formats like CSV and JSON. And since SAS can access Google BigQuery, SAS can access those GCS resources under the covers. In the final article, Nicolas debunks the myth that using Google BigQuery as middleware between SAS and GCS is cumbersome, not direct and requires data duplication.

Finally

Being able to access a wide variety of data on the major cloud providers' object storage technologies has become essential if not already mandatory. I encourage you to browse through the various articles, find your specific area of interest, and try out some of the detailed concepts.

* Big Data history compiled from A Short History Of Big Data, by Dr Mark van Rijmenam.

Accessing Google Cloud Storage (GCS) with SAS Viya was published on SAS Users.

11月 192020
 
SAS loves data. It's our raison d'être. We've been dealing with Big Data long before the term was first used in 2005. A brief history of Big Data*:

  • In 1887, Herman Hollerith invented punch cards and a reader to organize census data.
  • In 1937, the US government had a punch-card reading machine created to keep track of 26 M Americans and 3 M employers as a result of the Social Security Act.
  • In 1943, Colossus was created to decipher Nazi codes during World War II.
  • In 1952, the National Security Agency was created to confront decrypting intelligence signals during the Cold War.
  • In 1965, the US Government built the first data center to store 742 M tax returns and 175 M sets of fingerprints.
  • In 1989, British computer scientist Tim Berners-Lee coined the phrase "World Wide Web" combining hypertext with the Internet.
  • In 1995, the first super-computer is built.
  • In 2005 Roger Mougalas from O'Reilly Media coined the term Big Data.
  • In 2006, Hadoop is created.

From

To


The story goes on to the tune of 90 percent of available data today has been created in the last two years!

As SAS (and the computing world) moves to the cloud, the question of, "How do I deal with my data (Big and otherwise), which used to be on-prem, in the cloud?" is at the forefront of many organizations. I ran across a series of relevant articles by my colleague, Nicolas Robert, on the SAS Support Communities on SAS and data access and storage on Google Cloud Storage (GCS). This post organizes the articles so you can quickly get an overview of the various options for SAS to access data in GCS.

Accessing Google Cloud Storage (GCS) with SAS Viya 3.5 – An overview

As the title suggests, this is an overview of the series. Some basic SAS terminology and capabilities are discussed, followed by an overview of GCS data options for SAS. Options include:

  • gsutil - the "indirect" way
  • REST API - the "web" way
  • gcsfuse - the "dark" way
  • BigQuery - the "smart" way.

In the overview Nicolas provides the pros and cons of each offering to help you decide which option works best for your situation. Below is a list of subsequent articles providing technical details, specific steps for usage, and sample code for each option.

Accessing files on Google Cloud Storage (GCS) using REST

The Google Cloud Platform (GCP) provides an API for manipulating objects in Google Cloud Storage. In this article, Nicolas provides step-by-step instructions on using this API to access GCS files from SAS.

Accessing files on Google Cloud Storage (GCS) using SAS Viya 3.5 and Cloud Storage FUSE (gcsfuse)

Cloud Storage FUSE provides a command-line utility, named “gcsfuse”, which helps you mount a GCS bucket to a local directory so the bucket’s contents are visible and accessible locally like any other file. In this article, Nicolas presents rules for CLI usage, options for mounting a GCS bucket to a local directory, and SAS code for accessing the data.

SAS Viya 3.5 and Google Cloud Storage (GCS) Performance Feedback

In this article, Nicolas provides the results of a performance test of GCS integrated with SAS when accessed from cloud instances. New releases of SAS will only help facilitate integration and improve performance.

Accessing files on Google Cloud Storage (GCS) through Google BigQuery

Google BigQuery naturally interacts with Google Cloud Storage using popular big data file formats (Avro, Parquet, ORC) as well as commodity file formats like CSV and JSON. And since SAS can access Google BigQuery, SAS can access those GCS resources under the covers. In the final article, Nicolas debunks the myth that using Google BigQuery as middleware between SAS and GCS is cumbersome, not direct and requires data duplication.

Finally

Being able to access a wide variety of data on the major cloud providers' object storage technologies has become essential if not already mandatory. I encourage you to browse through the various articles, find your specific area of interest, and try out some of the detailed concepts.

* Big Data history compiled from A Short History Of Big Data, by Dr Mark van Rijmenam.

Accessing Google Cloud Storage (GCS) with SAS Viya was published on SAS Users.

9月 042020
 

As SAS Viya adoption increases among customers, many discover that it fits perfectly alongside their existing SAS implementations, which can be integrated and kept running until major projects have been migrated over. Conversely, SAS Grid Manager has been deployed during the past years to countless production sites. Because SAS Viya provides distributed computing capabilities, customers wonder how it compares to SAS Grid Manager.

SAS® Grid Manager and SAS® Viya® implement distributed computing according to different computational patterns. They can complement each other in providing a highly available and scalable environment to process large volumes of data and produce rapid results. At a high level, the questions we get the most from SAS customers can be summarized in four categories:

  1. I have SAS Viya and SAS Grid Manager. How can I get the most value from using them together?
  2. I have SAS Viya. Can I get any additional benefits by also implementing SAS Grid Manager?
  3. I have SAS Grid Manager. Should I move to SAS Viya?
  4. I am starting a new project. Which platform should I use - SAS Viya or SAS Grid Manager?

To better understand how to get the most from both an architecture and an administration perspective, I answer these questions and more in my SGF 2020 paper SAS® Grid Manager and SAS® Viya®: A Strong Relationship, and its accompanying YouTube video:

I’ve also written a three-part series with more details:

SAS Grid Manager and SAS Viya: A Strong Relationship was published on SAS Users.

9月 042020
 

As SAS Viya adoption increases among customers, many discover that it fits perfectly alongside their existing SAS implementations, which can be integrated and kept running until major projects have been migrated over. Conversely, SAS Grid Manager has been deployed during the past years to countless production sites. Because SAS Viya provides distributed computing capabilities, customers wonder how it compares to SAS Grid Manager.

SAS® Grid Manager and SAS® Viya® implement distributed computing according to different computational patterns. They can complement each other in providing a highly available and scalable environment to process large volumes of data and produce rapid results. At a high level, the questions we get the most from SAS customers can be summarized in four categories:

  1. I have SAS Viya and SAS Grid Manager. How can I get the most value from using them together?
  2. I have SAS Viya. Can I get any additional benefits by also implementing SAS Grid Manager?
  3. I have SAS Grid Manager. Should I move to SAS Viya?
  4. I am starting a new project. Which platform should I use - SAS Viya or SAS Grid Manager?

To better understand how to get the most from both an architecture and an administration perspective, I answer these questions and more in my SGF 2020 paper SAS® Grid Manager and SAS® Viya®: A Strong Relationship, and its accompanying YouTube video:

I’ve also written a three-part series with more details:

SAS Grid Manager and SAS Viya: A Strong Relationship was published on SAS Users.

4月 132020
 

Editor’s note: This is the third article in a series by Conor Hogan, a Solutions Architect at SAS, on SAS and database and storage options on cloud technologies. This article covers the SAS offerings available to connect to and interact with the various storage options available in Microsoft Azure. Access all the articles in the series here.

In this edition of the series on SAS and cloud integration, I cover the various storage options available on Microsoft Azure and how connect to and interact with them. I focus on three key storage services: object storage, block storage, and file storage. In my previous articles I have covered topics regarding database as a service (DBaaS) and storage offerings from Amazon Web Services (AWS) as well as DBaaS on Azure.

Object Storage

Azure Blob Storage is a low-cost, scalable cloud object storage service for any type of data. Objects are a great way to store large amounts of unstructured data in their native formats. Individual Azure Blob objects size up to 4.75 terabytes (TB). Azure organizes these objects into different storage accounts. Because a storage account is a globally unique namespace for your data, no two storage accounts can have the same name. The storage account supplies a unique namespace for your data and is accessible from anywhere in the world over HTTP or HTTPS.

A Container organizes a set of Blobs similar to a traditional directory in a file system. You access Azure Blobs directly through an API from anywhere in the world. For security reasons, it is vital to grant least access to a Blob.

Make sure you are being intentional about opening objects up and are not exposing any sensitive data. Security controls are offered within individual blobs and containers that organize them. The default is to create objects and blobs with no public read access, then you may grant permissions to individual users and groups.

The total cost of blob storage depends on volume of data stored, type of operations performed, data transfer costs, and data redundancy choices. You can reduce the number of replicants or use one of the various tiers of archive services to reduce the cost of your object storage. Terabytes of storage used per month determine the calculations on cost. You incur added costs for data requests and transfers over the network. Data movement is an unpredictable expense for many users.

Azure Blob Storage Tiers
Hot Frequently accessed data
Cool Infrequently accessed data – archived at least 30 days
Archive Rarely accessed data – archived at least 180 days

 
In SAS Viya 3.5, direct support is available for objects stored in Azure Data Lake Storage Gen2. Azure Data Lake Storage Gen2 extends Azure Blob Storage capabilities and optimizing it for analytics workloads. If you want to read any SAS datasets, CSV and ORC files from Azure Blob Storage, you can read them directly using a CASLIB statement to Azure Data Lake Storage (ADLS). If you have files in a different format, you can always copy them to a local file system accessible to the CAS controller. Use CAS Actions to load tables into memory. Making HTTP requests directly from within your SAS code using Proc HTTP for the download process favors automation. Remember, no restrictions exist on file types for objects moving into object storage. Hence, this may require a SAS Data Connector to read some local file system filetypes.

Block Storage

Auzre Disks is the block storage service designed for use with Azure Virtual Machines. You may only access block storage when attached to an operating system. When thinking about Azure Disks, treat the storage volumes as an independent disk drive controlled by the server operating system. Mount an Azure Disk to an operating system as if it were a physical disk. Azure Disks are valuable because they are the persisting storage when you terminate your compute instance. You can choose from four different volume types that supply performance levels at corresponding costs.

Azure makes available a choice from HDD or three different performance classes of SSD: Standard, Premium, and Ultra performance. You can use Ultra Disk if you need the lowest latency and scalable performance. Standard SDD is the most cost effective while Premium SSD is the high-performance disk offering. The table below sums up four offerings.

Azure Disk Storage Types
Standard HDD Standard SDD Premium SDD Ultra SDD
Backups and Non critical Development or Test environments and lightly used workloads Production environments and time sensitive workloads High throughput and IOPS - Transaction heavy workloads

 
Azure Disks are the permanent SAS data storage, persisting through a restart of your SAS environment. The disk performance used when selecting from the different Azure Disk type has a direct impact on the performance you get from SAS. A best practice is to use compute instances with enhanced Azure Disks performance or dedicated solid state drive instance storage.

File Storage

Azure Files provides access to data through a shared file system. The elastic network file system grows and shrinks as you add or remove files, so you only pay for the storage you consume. Users create, delete, modify, read, and write files organized logically in a directory structure for intuitive access. This service allows simultaneous access for multiple users to a common set of files data managed by user and group permissions.

Azure Files is a powerful tool, especially if utilizing a SAS Grid architecture. If you have a requirement in your SAS architecture for a shared location where any node in a group can access and write to, then Azure Files could meet your requirement. To access the data stored in your network file system you will have to mount the file system to your operating system. You can mount Azure Files to any Azure Virtual Machine, or even to an on-premise server within your Azure Virtual Network. Azure Files is a fantastic way to setup a shared file system not only for your data but also to share projects and code between users.

Finally

Storage is a key component of cloud computing because it enables users to stop their compute instances while their most important data remains in place. Storage services make it much easier to manage and scale your data. For example, Blob storage is a great place to store files that you want to make available to anyone, anywhere.

Block storage drives the performance of your environment. Abundant and performant block storage is essential to making your application run against the massive scale of data that SAS is eager to consume. Block storage is where your operating system and software ultimately are installed.

File storage is a great service to attach shared file systems to your compute instances. This is a great place to collaborate or migrate file system data from one compute instance to another. SAS is a compute engine running on data.

Without a robust set up storage tools to persist that data you may not get the performance that you desire or the progress you make will be lost when you shut down your compute instances.

Resources

Storage in the Cloud – SAS and Azure was published on SAS Users.

3月 182020
 

Let’s be honest, there is a lot of SAS content available on the web. Sometimes it gets difficult to navigate through everything to find what you need, especially if you are looking for complimentary resources.

Training budgets can be limited or already used for the year, but you’re still interested in learning a new SAS product or diving deeper into a specific subject to facilitate any current projects you are working on. Or you’re a real over-achiever (go, you!) and you’re looking to expand your personal SAS skills outside of your day-to-day work.

You start asking, “How do I find what I need?”

Don’t worry, SAS has you covered!

SAS learn & support

Let’s start with a favorite resource (in a Customer Success Manager’s opinion) – SAS’ learn and support pages. SAS recently released updated learn and support pages for SAS products. These pages provide a great overview of SAS’ product offerings, and they provide resources for those who are new to SAS or those looking to expand their knowledge. The learn and support pages cover the most current product release, information on getting started, tutorials, training courses, books, and documentation for current and past releases.

Not sure how to locate the learn and support page for the SAS product you are using? Search the SAS Product Support A to Z page and select the product of your choice.

SAS documentation

Browsing the web for resources is a great way to find answers to your SAS questions. But as mentioned previously, it can sometimes get tricky to find what you are looking for.

A great place to start your search is on the SAS documentation site. You can use the search bar to enter what you are looking for, or browse by products, titles or system requirements.

What’s new in SAS

You may have heard the saying, “There are three ways to do anything in SAS.” (Or four, or five or six!) Which raises the question, “How do I know what I’m doing is the most efficient?”

One way to stay on top of the most efficient way to do things is to stay current with your SAS knowledge. Knowing what’s new in SAS helps users know and understand what new features and enhancements are available. When a SAS product release occurs, SAS provides documentation on what’s new.

To know what’s new in the SAS release you’re using, check out the What’s New documentation. The documentation is broken into two parts: SAS 9.4 and SAS Viya 3.5. You can use the ‘Version’ tab on the left-hand side of the page to select the version currently installed at your organization.

If you are not sure what version you are running, you can run PROC PRODUCT_STATUS. This PROC will return what version numbers are running for the SAS products installed.

proc product_status;
run;

Another great resource to stay on top of what’s new from SAS is to check out SAS webinars. SAS offers live and on-demand webinars hosted by SAS experts. There are topics for every level of SAS user and every level of an organization, from SAS programmers to executives.

To attend a live webinar, select the webinar of your choice, register to attend, and you will be sent an email with the calendar invite.

If you’re interested in checking out an on-demand webinar, you can search by topic or industry to find a topic that fits what you’re looking for.

Looking for a webinar that focuses on a SAS tool? Check out the SAS Ask the Expert webinars. These are one-hour live and on-demand webinars for SAS users and administrators. The sessions cover a wide range of topics from what’s new in new releases of SAS products, to overviews on getting started, to tips and tricks that help take your SAS knowledge to the next level.

With SAS’ extensive catalog of webinars to choose from you will be a SAS pro in no time!

SAS training and education

Did you know that SAS offers free e-learning for some of our training courses? These courses are self-paced and cover a wide range of topics. With 180 days of access to these courses, it allows you to work through them at your own speed. It’s also very easy to get started!

Step 1: Select a course from the course library

Step 2: Sign into your SAS profile or create one

Step 3: Activate your product(s) and review the License Agreement

Step 4: Work through the course lessons

Step 5: Complete the course and receive your SAS digital Learn Badge and Course Completion Certificate

Leverage expertise worldwide

SAS recently released SAS Analytics Explorer. This is an interactive way to connect with other SAS professionals, expand your SAS knowledge, and access private SAS events and resource all while earning points that can be exchanged for rewards.

Are you up for the challenge? No really, are you? The SAS Analytics Explorer has fun and educational challenges that allow you to showcase your SAS skills to climb the ranks in the network. Show off your SAS talent and get some cool rewards while you’re at it!

Interested in joining? Fill out the form on the bottom of the SAS Analytics Explorer page to request an invitation.

Don’t forget about the SAS Communities! Connect with other SAS professionals and experts to ask questions, assist other SAS professionals with their questions, connect with users, and see what’s going on at SAS.

You can also connect with SAS on our website using the chat feature. We love SAS users, and we are here to help you!

Tips and resources for making the most of your SAS experience was published on SAS Users.

12月 042019
 

Site relaunches with improved content, organization and navigation.

In 2016, a cross-divisional SAS team created developer.sas.com. Their mission: Build a bridge between SAS (and our software) and open source developers.

The initial effort made available basic information about SAS® Viya® and integration with open source technologies. In June 2018, the Developer Advocate role was created to build on that foundation. Collaborating with many of you, the SAS Communities team has improved the site by clarifying its scope and updating it consistently with helpful content.

Design is an iterative process. One idea often builds on another.

-- businessman Mark Parker

The team is happy to report that recently developer.sas.com relaunched, with marked improvements in content, organization and navigation. Please check it out and share with others.

New overview page on developer.sas.com

The developer experience

The developer experience goes beyond the developer.sas.com portal. The Q&A below provides more perspective and background.

What is the developer experience?

Think of the developer experience (DX) as equivalent to the user experience (UX), only the developer interacts with the software through code, not points and clicks. Developers expect and require an easy interface to software code, good documentation, support resources and open communication. All this interaction occurs on the developer portal.

What is a developer portal?

The white paper Developer Portal Components captures the key elements of a developer portal. Without going into detail, the portal must contain (or link to) these resources: an overview page, onboarding pages, guides, API reference, forums and support, and software development kits (SDKs). In conjunction with the Developers Community, the site’s relaunch includes most of these items.

Who are these developers?

Many developers fit somewhere in these categories:

  • Data scientists and analysts who code in open source languages (mainly Python and R in this case).
  • Web application developers who create apps that require data and processing from SAS.
  • IT service admins who manage customer environments.

All need to interact with SAS but may not have written SAS code. We want this population to benefit from our software.

What is open source and how is SAS involved?

Simply put, open source software is just what the name implies: the source code is open to all. Many of the programs in use every day are based on open source technologies: operating systems, programming languages, web browsers and servers, etc. Leveraging open source technologies and integrating them with commercial software is a popular industry trend today. SAS is keeping up with the market by providing tools that allow open source developers to interact with SAS software.

What is an API?

All communications between open source and SAS are possible through APIs, or application programming interfaces. APIs allow software systems to communicate with one another. Software companies expose their APIs so developers can incorporate functionality and send or request data from the software.

Why does SAS care about APIs?

APIs allow the use of SAS analytics outside of SAS software. By allowing developers to communicate with SAS through APIs, customer applications easily incorporate SAS functions. SAS has created various libraries to aid in open source integration. These tools allow developers to code in the language of their choice, yet still interface with SAS. Most of these tools exist on github.com/sassoftware or on the REST API guides page.

A use case for SAS APIs

A classic use of SAS APIs is for a loan default application. A bank creates a model in SAS that determines the likelihood of a customer defaulting on a loan based on multiple factors. The bank also builds an application where a bank representative enters the information for a new potential customer. The bank application code uses APIs to communicate this information to the SAS model and return a credit decision.

What is a developer advocate?

A developer advocate is someone who helps developers succeed with a platform or technology. Their role is to act as a bridge between the engineering team and the developer community. At SAS, the developer advocate fields questions and comments on the Developers Community and works with R&D to provide answers. The administration of developer.sas.com also falls under the responsibility of the developer advocate.

We’re not done

The site will continue to evolve, with additions of other SAS products and offerenings, and other initiatives. Check back often to see what’s new.
Now that you are an open source and SAS expert, please check out the new developer.sas.com. We encourage feedback and suggestions for content. Leave comments and questions on the site or contact Joe Furbee: joe.furbee@sas.com.

developer.sas.com 2.0: More than just a pretty interface was published on SAS Users.

11月 052019
 

Editor’s note: This is the third article in a series by Conor Hogan, a Solutions Architect at SAS, on SAS and database and storage options on cloud technologies. This article covers the SAS offerings available to connect to and interact with the various database options available in Microsoft Azure. Access all the articles in the series here.

The series

This is the next iteration of a series covering database as a service (DBaaS) and storage offerings in the cloud, this time from Microsoft Azure. I have already published two articles on Amazon Web Services. One of those articles covers the DBaaS offerings and the other covers storage offerings for Amazon Web Services. I will cover Google Cloud Platform in future articles. The goal of these articles is to supply a breakdown of these services to better understand the business requirements of these offerings and how they relate to SAS. I would encourage you to read all the articles in the series even if you are already using a specific cloud provider. Many of the core technologies and services are offered across the different cloud providers. These articles focus primarily on SAS Data Connectors as part of SAS Viya, but all the same functionality is available using a SAS/ACCESS Interface in SAS 9.4. SAS In-Database technologies in SAS Viya, called the SAS Data Connect Accelerator, are synonymous with the SAS Embedded Process.

As companies move their computing to the cloud, they are also moving their storage to the cloud. Just like compute in the cloud, data storage in the cloud is elastic and responds to demand while only paying for what you use. As more technologies move to a cloud-based architecture, companies must consider questions like: Where do I store my data? What cloud services best meet my business requirements? Which cloud vendor should I use? Can I migrate my applications to the cloud? If you are looking to migrate your SAS infrastructure to Azure, look at the SAS Viya QuickStart Template for Azure to see a rapid deployment pattern to get the SAS Viya platform up and running in Azure.

SAS integration with Azure

SAS has extended SAS Data Connectors and SAS In-Database Technologies support to Azure database variants. A database running in Azure is much like your on-premise database, but instead Microsoft manages the software and hardware. Azure’s DBaaS offerings takes care of the scalability and high availability of the database with minimal user input. SAS integrates with your cloud database even if SAS is running on-premise or with a different cloud provider.

Azure databases

Azure offers database service technologies familiar to many users. If you read my previous article on SAS Data Connectors and Amazon Web Services, you are sure to see many parallels. It is important to understand the terminology and how the different database services in Azure best meet the demands of your specific application. Many common databases already in use are being refactored and provided as service offerings to customers in Azure. The advantages for customers are clear: no hardware to manage and no software to install. Databases that scale automatically to meet demand and software that updates and creates backups means customers can spend more time creating value from their data and less time managing their infrastructure.

For the rest of this article I cover various database management systems, the Azure offering for each database type, and SAS integration. First let's consider the diagram below depicting a decision flow chart to determine integration points between Azure database services and SAS. Trace you path in the diagram and read on to learn more about connection details.

Integration points between Azure database services and SAS

Relational Database Management System (RDBMS)

In the simplest possible terms, an RDBMS is a collection of managed tables with rows and columns. You can divide relational databases into two functional groups: online transaction processing (OLTP) and online analytical processing (OLAP). These two methods serve two distinct purposes and are optimized depending in how you plan to use the data in the database.

Transactional Databases (OLTP)

Transactional databases are good at processing reads, inserts, updates and deletes. These queries usually have minimal complexity, in large volumes. Transactional databases are not optimized for business intelligence or reporting. Data processing typically involves gathering input information, processing the data and updating existing data to reflect the collected and processed information. Transactional databases prevent two users accessing the same data concurrently. Examples include order entry, retail sales, and financial transaction systems. Azure offers several types of transactional database services. You can organize the Azure transactional database service into three categories: enterprise licenses, open source, and cloud native.

Enterprise License

Many customers have workloads built around an enterprise database. Azure is an interesting use case because Microsoft is also a traditional enterprise database vendor. Amazon, for example, does not have existing on-premise enterprise database customers. Oracle cloud is the other big player in the enterprise market looking to migrate existing customers to their cloud. Slightly off topic, but it may be of interest to some, SAS does support customers running their Oracle database on Oracle Cloud Platform using their SAS Data Connector to Oracle. Azure offers a solution for customers looking to continue their relationship with Microsoft without refactoring their existing workflows. Customers bring an existing enterprise database licenses to Azure and run SQL Server on Virtual Machines. SAS has extended SAS Data Connector support for SQL Server on Virtual Machines. You can also use your existing SAS license for SAS Data Connector to Oracle or SAS Data Connector to Microsoft SQL Server to interact with SQL Server on Virtual Machines.

Remember you can install and manage your own database on a virtual machine. For example, support for both SAS Data Connector to Teradata and SAS Data Connect Accelerator for Teradata is available for Teradata installed on Azure. If there is not an available database as a service offering, the traditional backup and update responsibilities are left to the customer.

SQL Server Stretch Database is another service available in Azure. If you are not prepared to add more storage to your existing on-premise SQL Server database, you can add capacity using the resources available in Azure. SQL Server Stretch will scale your data to Azure without having to provision any more servers on-premise. New SQL Server capacity will be running in Azure instead of in your data center.

Open Source

Azure provides service offerings for common open source databases like MySQL, MariaDB, and PostgreSQL. You can use your existing SAS license for SAS Data Connector to MYSQL to connect to Azure Database for MYSQL and SAS Data Connector to PostgreSQL to interface with Azure Database for PostgreSQL. SAS has not yet formally supported Azure Database for MariaDB. MariaDB is a variant of MySQL, so validation of support for SAS Data Connector is coming soon. If you need support for MariaDB in Azure database, please comment below and I will share your feedback with product management and testing.

Cloud Native

Azure SQL Database is an iteration of Microsoft SQL Server built for the cloud, combining the performance and availability of traditional enterprise databases with the simplicity and cost-effectiveness of open source databases. SAS has extended SAS Data Connector support for Azure SQL Database. You can use your existing license for SAS Data Connector to Microsoft SQL Server to connect to Azure SQL Database.

Analytical Databases (OLAP)

Analytical Databases optimize on read performance. These databases work best from complex queries in smaller volume. When working with an analytical database you are typically doing analysis on multidimensional data interactively from multiple perspectives. Azure SQL Data Warehouse is the analytical database service offered by Azure. The SAS Data Connector to ODBC combined with a recent version of the Microsoft-supplied ODBC driver is currently the best way to interact with Azure SQL Data Warehouse. Look for the SAS Data Connector to Microsoft SQL Server to support SQL Data Warehouse soon.

NoSQL Databases

A non-relational or NoSQL database is any database not conforming to the relational database model. These databases are more easily scalable to a cluster of machines. NoSQL databases are a more natural fit for the cloud because the loose dependencies make the data easier to distribute and scale. The different NoSQL databases are designed to solve a specific business problem. Some of the most common data structures are key-value, column, document, and graph databases. If you want a brief overview of these database structures, I cover them in my AWS database blog.

For Microsoft Azure, CosmosDB is the option available for NoSQL databases. CosmosDB is multi-model, meaning you can build out your databases to fit the NoSQL model you prefer. Use the SAS Data Connector to ODBC to interact with your Data in Azure CosmosDB.

Hadoop

The traditional deployment of Hadoop is changing dramatically with the cloud. Traditional Hadoop vendors may have a tough time keeping up with the service offerings available in the cloud. Hadoop still offers reliable replicated storage across nodes and powerful parallel processing of large jobs without much data movement. Azure offers HDInsights as their Hadoop as a service offering. Azure HDInsights supports both SAS Data Connector to Hadoop and SAS Data Connect Accelerator for Hadoop.

Finally

It is important to think about the use case for your database and the type of data you plan to store before you select an Azure database service. Understanding your workloads is critical to getting the right performance and cost. When dealing with cloud databases, remember that you will be charged for the storage you use and for the data that you move out of the database. Performing analysis and reporting on your data may require data transfer. Be aware of these costs and think about how you can lower these by keeping frequently accessed data cached somewhere or remain on-premise. Another strategy I’ve seen becoming more popular is taking advantage of the SAS Micro Analytics Service to move the models you have built to run in the cloud provider where your data is stored. Data transfer is cheaper if that data moves between cloud services instead of outside of the cloud provider. Micro Analytics Service allows you to score the data in place without movement from a cloud provider and without having to do an install of SAS.

Additional Resources
1. Support for Databases in SAS® Viya® 3.4
2. Support for Cloud and Database Variants in SAS® 9.4

Accessing Databases in the Cloud – SAS Data Connectors and Microsoft Azure was published on SAS Users.

11月 052019
 

Editor’s note: This is the third article in a series by Conor Hogan, a Solutions Architect at SAS, on SAS and database and storage options on cloud technologies. This article covers the SAS offerings available to connect to and interact with the various database options available in Microsoft Azure. Access all the articles in the series here.

The series

This is the next iteration of a series covering database as a service (DBaaS) and storage offerings in the cloud, this time from Microsoft Azure. I have already published two articles on Amazon Web Services. One of those articles covers the DBaaS offerings and the other covers storage offerings for Amazon Web Services. I will cover Google Cloud Platform in future articles. The goal of these articles is to supply a breakdown of these services to better understand the business requirements of these offerings and how they relate to SAS. I would encourage you to read all the articles in the series even if you are already using a specific cloud provider. Many of the core technologies and services are offered across the different cloud providers. These articles focus primarily on SAS Data Connectors as part of SAS Viya, but all the same functionality is available using a SAS/ACCESS Interface in SAS 9.4. SAS In-Database technologies in SAS Viya, called the SAS Data Connect Accelerator, are synonymous with the SAS Embedded Process.

As companies move their computing to the cloud, they are also moving their storage to the cloud. Just like compute in the cloud, data storage in the cloud is elastic and responds to demand while only paying for what you use. As more technologies move to a cloud-based architecture, companies must consider questions like: Where do I store my data? What cloud services best meet my business requirements? Which cloud vendor should I use? Can I migrate my applications to the cloud? If you are looking to migrate your SAS infrastructure to Azure, look at the SAS Viya QuickStart Template for Azure to see a rapid deployment pattern to get the SAS Viya platform up and running in Azure.

SAS integration with Azure

SAS has extended SAS Data Connectors and SAS In-Database Technologies support to Azure database variants. A database running in Azure is much like your on-premise database, but instead Microsoft manages the software and hardware. Azure’s DBaaS offerings takes care of the scalability and high availability of the database with minimal user input. SAS integrates with your cloud database even if SAS is running on-premise or with a different cloud provider.

Azure databases

Azure offers database service technologies familiar to many users. If you read my previous article on SAS Data Connectors and Amazon Web Services, you are sure to see many parallels. It is important to understand the terminology and how the different database services in Azure best meet the demands of your specific application. Many common databases already in use are being refactored and provided as service offerings to customers in Azure. The advantages for customers are clear: no hardware to manage and no software to install. Databases that scale automatically to meet demand and software that updates and creates backups means customers can spend more time creating value from their data and less time managing their infrastructure.

For the rest of this article I cover various database management systems, the Azure offering for each database type, and SAS integration. First let's consider the diagram below depicting a decision flow chart to determine integration points between Azure database services and SAS. Trace you path in the diagram and read on to learn more about connection details.

Integration points between Azure database services and SAS

Relational Database Management System (RDBMS)

In the simplest possible terms, an RDBMS is a collection of managed tables with rows and columns. You can divide relational databases into two functional groups: online transaction processing (OLTP) and online analytical processing (OLAP). These two methods serve two distinct purposes and are optimized depending in how you plan to use the data in the database.

Transactional Databases (OLTP)

Transactional databases are good at processing reads, inserts, updates and deletes. These queries usually have minimal complexity, in large volumes. Transactional databases are not optimized for business intelligence or reporting. Data processing typically involves gathering input information, processing the data and updating existing data to reflect the collected and processed information. Transactional databases prevent two users accessing the same data concurrently. Examples include order entry, retail sales, and financial transaction systems. Azure offers several types of transactional database services. You can organize the Azure transactional database service into three categories: enterprise licenses, open source, and cloud native.

Enterprise License

Many customers have workloads built around an enterprise database. Azure is an interesting use case because Microsoft is also a traditional enterprise database vendor. Amazon, for example, does not have existing on-premise enterprise database customers. Oracle cloud is the other big player in the enterprise market looking to migrate existing customers to their cloud. Slightly off topic, but it may be of interest to some, SAS does support customers running their Oracle database on Oracle Cloud Platform using their SAS Data Connector to Oracle. Azure offers a solution for customers looking to continue their relationship with Microsoft without refactoring their existing workflows. Customers bring an existing enterprise database licenses to Azure and run SQL Server on Virtual Machines. SAS has extended SAS Data Connector support for SQL Server on Virtual Machines. You can also use your existing SAS license for SAS Data Connector to Oracle or SAS Data Connector to Microsoft SQL Server to interact with SQL Server on Virtual Machines.

Remember you can install and manage your own database on a virtual machine. For example, support for both SAS Data Connector to Teradata and SAS Data Connect Accelerator for Teradata is available for Teradata installed on Azure. If there is not an available database as a service offering, the traditional backup and update responsibilities are left to the customer.

SQL Server Stretch Database is another service available in Azure. If you are not prepared to add more storage to your existing on-premise SQL Server database, you can add capacity using the resources available in Azure. SQL Server Stretch will scale your data to Azure without having to provision any more servers on-premise. New SQL Server capacity will be running in Azure instead of in your data center.

Open Source

Azure provides service offerings for common open source databases like MySQL, MariaDB, and PostgreSQL. You can use your existing SAS license for SAS Data Connector to MYSQL to connect to Azure Database for MYSQL and SAS Data Connector to PostgreSQL to interface with Azure Database for PostgreSQL. SAS has not yet formally supported Azure Database for MariaDB. MariaDB is a variant of MySQL, so validation of support for SAS Data Connector is coming soon. If you need support for MariaDB in Azure database, please comment below and I will share your feedback with product management and testing.

Cloud Native

Azure SQL Database is an iteration of Microsoft SQL Server built for the cloud, combining the performance and availability of traditional enterprise databases with the simplicity and cost-effectiveness of open source databases. SAS has extended SAS Data Connector support for Azure SQL Database. You can use your existing license for SAS Data Connector to Microsoft SQL Server to connect to Azure SQL Database.

Analytical Databases (OLAP)

Analytical Databases optimize on read performance. These databases work best from complex queries in smaller volume. When working with an analytical database you are typically doing analysis on multidimensional data interactively from multiple perspectives. Azure SQL Data Warehouse is the analytical database service offered by Azure. The SAS Data Connector to ODBC combined with a recent version of the Microsoft-supplied ODBC driver is currently the best way to interact with Azure SQL Data Warehouse. Look for the SAS Data Connector to Microsoft SQL Server to support SQL Data Warehouse soon.

NoSQL Databases

A non-relational or NoSQL database is any database not conforming to the relational database model. These databases are more easily scalable to a cluster of machines. NoSQL databases are a more natural fit for the cloud because the loose dependencies make the data easier to distribute and scale. The different NoSQL databases are designed to solve a specific business problem. Some of the most common data structures are key-value, column, document, and graph databases. If you want a brief overview of these database structures, I cover them in my AWS database blog.

For Microsoft Azure, CosmosDB is the option available for NoSQL databases. CosmosDB is multi-model, meaning you can build out your databases to fit the NoSQL model you prefer. Use the SAS Data Connector to ODBC to interact with your Data in Azure CosmosDB.

Hadoop

The traditional deployment of Hadoop is changing dramatically with the cloud. Traditional Hadoop vendors may have a tough time keeping up with the service offerings available in the cloud. Hadoop still offers reliable replicated storage across nodes and powerful parallel processing of large jobs without much data movement. Azure offers HDInsights as their Hadoop as a service offering. Azure HDInsights supports both SAS Data Connector to Hadoop and SAS Data Connect Accelerator for Hadoop.

Finally

It is important to think about the use case for your database and the type of data you plan to store before you select an Azure database service. Understanding your workloads is critical to getting the right performance and cost. When dealing with cloud databases, remember that you will be charged for the storage you use and for the data that you move out of the database. Performing analysis and reporting on your data may require data transfer. Be aware of these costs and think about how you can lower these by keeping frequently accessed data cached somewhere or remain on-premise. Another strategy I’ve seen becoming more popular is taking advantage of the SAS Micro Analytics Service to move the models you have built to run in the cloud provider where your data is stored. Data transfer is cheaper if that data moves between cloud services instead of outside of the cloud provider. Micro Analytics Service allows you to score the data in place without movement from a cloud provider and without having to do an install of SAS.

Additional Resources
1. Support for Databases in SAS® Viya® 3.4
2. Support for Cloud and Database Variants in SAS® 9.4

Accessing Databases in the Cloud – SAS Data Connectors and Microsoft Azure was published on SAS Users.