A New Year for Data Scientists

Five resolutions data science professionals should make—and keep—for 2019

By Tina Schweihofer, Customer Advisory Manager, Data Sciences and Alex Terado, Data Science Solutions Specialist

Happy 2019! Hopefully, your holiday season was hectic in only the best way, and that you’re facing the new year with clear eyes, a clean slate, and a new sense of purpose.

Tradition has it that at the turn of the year, we make resolutions to improve ourselves, be better at being who we are and doing what we do. As data scientists, there are five areas where, with some focus and commitment, we can deliver better results this year.

These resolutions apply whether you’re an analytics veteran or someone relatively new to the cause, and we speak from both of those perspectives: Tina is a long-time analytics ambassador and team leader, while Alex brings the perspective of a recent recruit to the table.

The best resolutions to make are the realistic ones. We all have an unused gym membership or unread Gardening for Dummies in our closets because we didn’t approach our resolutions realistically. Remember the advice of the American Psychological Association: start small, change one thing at a time, and ask for support when you need it.

RESOLUTION #1: TREAT DATA SCIENCE AS A TEAM SPORT

Do you feel like you’re treading water, having trouble delivering data science initiatives or scaling to absorb new stakeholders or use cases? That’s sometime symptomatic of a data science team working in isolation from the rest of the business. Typical data science teams are small and scattered throughout the enterprise, organizationally and often geographically.

Data science teams have to get bigger to service the surge in enterprise use cases. But all that growth isn’t necessarily within the core data science team. The extended cast includes business stakeholders, data engineers, application developers, and more, and according to research firm Forrester, those extended data science teams will become bigger than software development teams in the next five years. For a data science team to provide maximum value, there must be buy-in from all stakeholders. Everyone has a significant role in the delivery of a shared analytic and artificial intelligence vision and that requires effective collaboration among all these team members.

RESOLUTION #2: EMBRACE AUTOMATION

Data science taxes the intellect, places demands on the analytic and modeling centres of the brain, and is ultimately a rewarding and satisfying intellectual discipline. Too bad we spend as little as 20 per cent of our time on it, according to a study by CrowdFlower. Most of a data scientist’s time is spent collecting, organizing, and cleansing data sets.

Vendors like SAS offer numerous tools to automate the heavy lifting part of the analytics job: data preparation and auto-tuning, model assessments and interpretation, suggestion engines driven by AI.

These can improve productivity, expose extended team members to the analytics curve, and let you get back to the kind of intellectual work that led the Harvard Business Review to name data scientist “The Sexiest Job of the 21^st Century.”

RESOLUTION #3: EXPERIMENT

“One sometimes finds what one is not looking for,” said Alexander Fleming of his accidental discovery that mold kills bacteria, paving the way for the first antibiotic, penicillin. While a data science query generally starts with a hypothesis, sometimes the data itself raises questions of its own. This iterative process can lead down the road to insights no one had foreseen, or even sought.

Truly experimenting with data requires resources. Data science teams need access to all the relevant data, not just a sample or subset.  AI and machine learning use data-hungry algorithms. More data means better models. Work with the extended team to make it easier to bring all the data to the table.  A high-performance analytics engine is needed to practically run iteration after iteration of experimental data within reasonable run times.

Remain open to as many algorithms, tools and techniques as you can bring to bear on a dataset. There’s an element of Zen to finding the answer to a question you didn’t know was important to ask. Governance standards are essential to ensure the results can be trusted regardless of coding language.

Read the final resolutions and learn more here.

I was asked to present on the Internet of Things at the November 2018 OPUS event in Ottawa... It's crazy to see how much information is available on this cool topic. The technology side of things is complex but the concepts are simple. 

My mission was to present it in a way that it doesn't make it sound overly complicated - yes, SAS has technology to support this but what is IOT and how does it help us be better- smarter... We are surrounded by this phenomenon and it does have an influence on our lives. From smart home switches to sophisticated sensors, we are generating a lot of data that needs to be understood.

I have been adding smart devices in my house for some time now and following my research and prep for this session I better understand how it all works... more importantly, that it only works if you do something with the information that is being collected. My latest addition was a smart thermostat -- that picks up when you leave the house and turns down the heat until it detects that you are on your way home. Great way to save energy but not so great if the smartphone that controls this device is away but the house isn't really empty. I ended up getting a phone call from my family because the house was getting colder. Easy to resolve now that I understand it better and that I have turned on notifications!!!

Learn and grow with IOT -- confidence will come over time. Get those smart devices working for you.

Here are the slides I used during the OPUS session.

Artificial Intelligence is a term that has become extremely popular in the business community. We see it everywhere, in the news, on the TV, in research papers, and yet it is a very recent phenomenon. According to Google’s Trends Tracker (see graph below), the term Artificial Intelligence had a relative interest rating of 38 on January 1^st, 2015. Contrast that to January 1^st of this year, where the interest rating had skyrocketed up to 88. Even with the prevalence of AI in our society, it is still a term that is relatively misunderstood. Therefore, it is essential that we understand what exactly we mean when we use the term “Artificial Intelligence”.    

According to Forrester, “Artificial Intelligence refers to the theory and capabilities that strive to mimic human intelligence through experience and learning.” At SAS, AI has been a core piece of our software for many years. Our key differentiator is that we help our customers operationalize AI, thereby bringing maximum value to their business. We embed AI in our solutions to drive value across industries by:

• Improving business efficiencies and increasing productivity through automated decisioning and completion of tasks.
• Decreasing costs and increasing profitability by helping to increase innovation, eliminate redundant costs and generate new revenue streams.
• Driving faster innovation cycles and accelerating time to market as AI technology is nowadays easier available at less costs which makes it easier for organization to start, scale and grow.
• Enhancing customer adoption and loyalty through better product offers, faster customer service, and more relevant messaging.

AI’s use cases range from the practical (such as the automation of tasks and decisioning) to the transformative. As a member of the SAS Canada Pre-Sales team, I had the tremendous opportunity to be part of an Advanced Artificial Intelligence Workshop hosted by members of the SAS Global Technology Practice team. During this week-long workshop our teams trained in creating tangible end-to-end AI applications that will inspire customers to leverage SAS as the underpinning of their AI needs, with some of the highlights being:

• Image Recognition to detect illegal fishing boats in protected waters
• Recommendation Engine to suggest optimal combinations of shot-type and player for a basketball team, outputted through a web application
• Anomaly Detection surfaced through a web application to collaborate with health-care practitioners to detect potential cases of breast cancer
• Natural-Language Processing Chatbot linked to business reports to improve the productivity and access of information for business analysts

Expert knowledge of tools, techniques and methodologies is vital to unlocking the benefits of AI. This knowledge is scarce and difficult to acquire because the need for AI talent has outpaced industry’s ability to fill it. To address this problem, SAS has created the SAS Artificial Intelligence Center of Excellence (SAS AI CoE), a group of PhD-level experts in AI, machine learning, natural language processing, computer vision, optimization and simulation, who are focused exclusively on customer implementations. The fee-for-service team is highly tuned to customer needs and combines a business-focused mindset with deep technical expertise to address business challenges and conduct assessments to uncover innovative opportunities that have business value. Learn more about the AI COE here.

In summary, Artificial Intelligence has become a predominant force in our world, one that is driving organizations to unprecedented levels of growth and prosperity. With SAS and AI, you can solve complex problems in sales, inventory, customer retention, fraud detection and much more. The computer can also discover information that you never thought to ask. There is no limit to what we can achieve with AI, and SAS is excited to partner with our customers to ensure their vision and goals are realized.

What are some use cases that you've seen with AI? How have you applied it and what were some of the challenges? Let us know in the comments below!

Having built numerous custom software demonstrations over the last few years there is no question that without good data, it is difficult to create a great demo let alone get meaningful insights. What is even more interesting is hearing clients claim that "we have great data" - this of course is until you try to use it! Then it becomes apparent that much "clean-up" is still required. All that clean-up tends to take a lot of time and this is where so many analysts and data scientists end up spending too much time.

Enter the world of AI for data preparation. Quite simply, AI can help the data preparation process in three distinct areas: detection, suggestion and automation.

Detection is the ability to use profiling of the data to understand its distribution, categorical levels and other characteristics so that your solution will utilize each variable properly in reporting and analysis.

Suggestion furthers this by inferencing how the data should be formatted, tagged and potentially cleansed for optimal usage. Formatted data is essential for proper representation but cleansing data to standardize on naming conventions and potentially treating missing data is crucial to creating the best analysis.

Automation is the final step. If detection and suggestion can be done automatically but also included in complex data jobs that can be shared with other analysts the time savings will allow analysts from across an organization to better collaborate and it will enable an increased amount of analytical work to actually happen.

Fortunately, SAS has been working in this realm for decades but the focus with the current platform is to bring everything discussed above to the user via an in-memory framework with an interface that is visually consistent regardless of the data preparation task being completed. Automatically provide all the profiling, format/cleansing suggestions and you have AI embedded into data preparation. Why not see this for yourself?

Be sure to attend the SAS AI event on November 14th and stop by the data preparation booth to see firsthand how AI now powers Data Preparation on the new SAS platform.

There is certainly no shortage of terrific tips and tricks in various SAS blogs from some of our most distinguished SAS in-house experts. But, there's another group of equally qualified experts who don't often get to share their expertise on this channel: our customers. So, I went on a quest to get the inside scoop from various SAS users, polling Friends of SAS members to get their feedback on their favorite SAS tips.

We asked a few of these Friends of SAS members who are regular SAS users to share with us their top SAS tips and tricks for improving performance or something they wished they had known earlier in their SAS career. Based on that, we got a wide range of tips and tricks from a number of different SAS users – ranging from novice to expert and across various industries and product users. Check out some of them below:

FUNCTIONS

Functions are either built into SAS itself or you can write your own customized code that act in the same manner, all of which help in analyzing and processing data. There are a variety of function categories that include mathematical, date and time, character, truncation, and miscellaneous. Using functions makes us more efficient, and we don’t have to re-invent the wheel every time we want to figure something out. With this being said, some of our regular SAS users have a thing or two to say about dealing with functions that may help you out:

“Before you program any complex code, look for a SAS function that will do the task for you.”
     - John Ladds, Past President, OASUS

“Insert a line break in a concatenated string, such as: manylines = catx('0a'x,a,b,c);”
     - Aroop Ghosh, Principal Consultant, Webtalk Communications

“Use the lag function to create time related variables, for example, in time punch data”
     - Yolanda, Analyst, TD

“A good trick that I have recently learnt [sic]which can make the code less wordier is using the functions IFN and IFC as an alternative to IF THEN ELSE statements in conditional processing.”
     - Sunny Giroti, Master of Business Analytics Candidate, Schulich School of Business

“IFN can be used in place of IF THEN ELSE to shorten code”
     - Neil Menezes, Senior Business Anlyst, CTFS

“Ron Cody’s link from SAS.COM. It has many SAS function examples.”
     - John Lam, CIBC

SYNTAX/SHORTCUTS/EFFICIENCIES

You know what they say: time is money. So for a SAS programmer, finding shortcuts and ways to work more efficiently and faster are important to get a job done quicker. Here are a few ways SAS users think can make your life easy while working with SAS:

“Use missover to ensure no records are skipped when reading in a file”
     - Scott Bellefeuille, IT Solutions Developer (Merchant Services), TD Bank

“Pressing keys 'Ctrl'+'/' to comment out a line of code.”
     - Bunce Leung, Execution Manager, RBC

“Variable Lists - being able to refer to variables using double dashes to indicate all variables between first and last in a dataset is super useful for many procs. The later versions of being able to use the prefix and colon to indicate all datasets with a prefix is a great shortcut as well.”
     - Fareeza Khurshed, Manager (Statistical Services), Alberta Treasury Board and Finance

“I like to use PERL in SAS for finding stuff in character variables.”
     - Peter Timusk, Statistics Officer, Statistics Canada

“Title "SAS can give you an Inheritance". Have an ODBC driver on your local PC but not on a remote server? No problem. Use rsubmit with the inheritlib option. Your remote server will now inherit the ODBC driver and be able to access a database you thought you could only reach with your PC.”
     - Horst Wolter, Manager, TD Bank

“If you want to speed the processing of your program. Run your join statements on the "work" library. It is must faster.”
     - Estela Tavares, Economist, Statistics Canada

“When dealing with probability, can logistic be used in all cases? Trick Q - as A is N0. What about the times, probability is 0 and 1. What if the data is heavily distributed on 1s and 0s.”
     - Mukul Pandey, Student Business Analytics, Schulich School of Business

“Proc tabulate can perform descriptive statistics better than proc freq and proc means.”
     - Taha Azizi, Senior Business Insight Analyst, TD

Your turn

Were any of these tips and tricks useful? Do you use them already? What are some of your top SAS tips and tricks? Please be sure to share in the comments below!

Looking for more tips and tricks? Check out this video featuring six Canadian SAS programmers, including a few Friends of SAS members, who share some of their favourite SAS programming tips.

About Friends of SAS

If you’re not familiar with Friends of SAS, it is an exclusive online community available only to our Canadian SAS customers and partners to recognize and show our appreciation for their affinity to SAS. Members complete activities called 'challenges' and earn points that can be redeemed for rewards. There are opportunities to build powerful connections, gain privileged access to SAS resources and events, and boost your learning and development of SAS all in a fun environment.

Interested in learning more about Friends of SAS? Feel free to email myself at Natasha.Ulanowski@sas.com or Martha.Casanova@sas.com with any questions or more details.

Find the original blog post a ton of other great blog posts about various SAS topics on the SAS Blogs website here. 

It’s that time of year again – back to school! And the SAS Canada Academic Program is at it again. We are organizing, leading, and sponsoring several different competitions this fall. These are awesome opportunities for students to learn SAS and for our partners to meet students and put their analytics skills to the test! A few highlights to know about:

The Queen’s Innovation Challenge – SAS is the technical sponsor for this year’s Queen’s International Innovation Challenge. The theme is Smart Cities. Students around the world will be submitting projects on October 29, 2018. The top five projects will win travel bursaries to visit the SAS Canada office on Friday, November 30, 2018. (Feel free to send me a message if you’re interested in attending!) SAS Viya is available to all students participating in the challenge. You may have noticed a previous post about this in the discussion forum – we’ve set this up so that students can submit questions about Viya and mentors will connect with them in our community. Our Data Sciences team has graciously agreed to mentor the students. Keep your eye out for questions!

The CRDCN National Policy Challenge – This is our first annual national competition in partnership with Statistics Canada and the Canadian Research Data Centre Network. We received over 40 proposals from students across the country and judges from SAS, StatsCan and the CRDCN are busy reviewing the proposals now. Up to ten teams will be selected to present their research in the finals – this will be held at StatsCan in June 2019. More info can be found here.

SAS Student Symposium – This is an annual competition that is part of SAS Global Forum. Students must register by November 16, 2018 and submit their projects by January 25, 2018. The top eight teams will be sent to SAS Global Forum to present in front of a panel of judges. Canada has won two of the last three Student Symposiums so let’s get those projects going and continue the Canadian streak!

We are always looking for mentors and judges to help us with our competitions. If you’re interested – or just want to chat about what’s happening and share your ideas – feel free to send me a message. Stay tuned for more information about our students’ success throughout the (school) year!

I had the opportunity to sit down with Rosie Foti and ask a few questions about the Admin community that she has fostered here in Canada. Learn more about what the Admin community is, how you can get involved and how to take advantage of the resources available to SAS Admins. SAS Administrators are the people that administer the SAS environment - which means they have a big job to ensure the environment is stable and the users stay happy!

Tell us a bit about how the Admin community first came together:        

I was inviting one of my Admin contacts within one of the accounts I still support to a Regional User Group Meeting.  She made the comment “why don’t you do something for the Admins similar to what you do for users.  We do not have anything available to us in terms of education or networking”. I took her comments seriously and started the ball rolling.  It was not very easy to organize the first virtual Canadian event which consisted of a SAS presentation as well as customer presentation.  However, given the overwhelming attendance and feedback on this session, this event turned into a global one led by our Community Team in Cary.  

How have you seen the community grow?

 The Canadian virtual meeting became what we know today as SUGA, quarterly global Admin related subject matters covered via Webex.  Most of those sessions are selected by the SUGA committee, which is a mix of SAS and customers with SAS Administrative roles.

In order to maintain a personal contact with Admins, I have continued the tradition of inviting Admins yearly to an Admin event, which covers subjects of interest to them.  This year we have opened it globally and the response was overwhelming.

Another Program grew out of these two events:  The SGF (SAS Global Forum) Admin Program.  We are in our 4^th year of offer free passes to Admins to encourage them to come down to SGF and get as much education as possible in their areas of expertise.  This program has again grown year over year. 

Why do you think these events have become so popular?

The SAS platform is one of those platforms that integrates with a lot of their databases and environments and hence that adds complexities to the environments.  Thus, there is a lot of learning to be done before Admins can become experts in their respective fields. Additionally, it was only during the last 3 years that SAS started offering learning events that are of interest to Admins. 

What was your most recent event?

Just last week, we had our 3^rd Annual event in Toronto which we also opened to all Admins across the world via the Communities.  That session was also recorded and shared with all participants and also placed on Admin community.

That event was followed by a new Architect event, which is just in its infancy and shows lots of promise to grow across time.

Where can people find Admin resources?

The SAS Users Group for Administrators (SUGA) is open to all SAS administrators who install, update, manage or maintain a SAS deployment.

https://communities.sas.com/t5/Administration-and-Deployment/bd-p/sas_admin.  There is a wealth of information in that domain and even, if one does not find what they want, all what they have to do is ask for help and someone will respond to them.

What are the upcoming admin events that SAS users might be interested in?

Looking forward:  there will be an upcoming SUGA webinar:

SAS® 9.4 and  SAS® Viya® : Admin Perspective 

Presenter:  Darrell Barton – Sr. Technical Training Consultant      

October 9th, 2:00 - 3:00pm ET

Go beyond technology - consider your people, your data and your existing processes.

There are many choices when it comes to analytics service and technology providers. Here are 4 things to consider as you embark on your analytics journey. 

1. From a people perspective, it’s critical to embrace all your analytics users.

Analytics has become as pervasive as Business Intelligence. As a result, analytics initiatives are often part of a broader mandate - no longer owned by a single data science function or team. That’s not to say the data scientist is not important, nothing could be further from the truth. They remain critical to the success of your analytics programs. However, they are several other voices at the “analytics table”. Depending on your organization, these could include business analysts, developers, IT and data-savvy executives. The right analytic toolkit can help bring all these users up the analytics curve and allow them to work together to solve business problems. With more people actively participating in the analytics conversation, data science teams can focus their efforts on the toughest problems.  When coupled with capabilities to automate time-consuming analytic tasks, overall productivity increases as well.

2. From a data perspective, experiment to innovate.

The discovery of penicillin was one of the most important medical discoveries of the 20^th century. It was an accidental discovery made by Sir Alexander Fleming in 1928, who was quoted as saying: "One sometimes finds what one is not looking for”. The same is true for the analytic discovery process. Although the process typically starts with a specific question or hypothesis, the data itself will often lead us down different paths and push us to ask new questions. This dynamic and iterative process can result in unexpected insights and great data discoveries.

So, how do you enable the type of experimentation that leads to innovation? Here are a few things to consider: Simplify access to your data. Provide users with a broad range of analytic algorithms, techniques and tools so that they are free to ask many different questions of their data. Leverage a high-performance engine designed for analytics that will crunch the data quickly and easily.  

3. From a process perspective, integrate results into your applications.  

This is all about taking the results of your experiment and making them actionable and repeatable. The value of a discovery increases exponentially when it is shared or integrated into existing processes. From an analytics perspective, this can be as simple as incorporating your results into an existing report. It could also involve embedding the output of a predictive model into a business process or calling a model in real-time to make a data-driven decision. Your insights could even serve as a building block in a larger application.

To tie this back to our earlier example, the true value of penicillin was only realized when physicians began to use the drug to treat infections in 1942 – but it took several years to get to that point. After the initial discovery, significant time and effort was spent communicating the initial findings, convincing others of the medical applications and determining how to mass produce the drug. Today’s organizations also face challenges moving from discovery to action in a timely fashion. They are often dealing with disjointed and inefficient workflows in large part as a function of how they have traditionally have worked with IT.  As an example, analytic models developed by the business typically need to be recoded manually by IT before they can be integrated into production systems. It is not uncommon for this to take several weeks or months.  

How can we make improvements in this area?  Start by eliminating the need for language conversion by using a common base to deploy models coded in different languages. Automate execution processes. Finally, remember that analytics are not static. It’s critical to govern and monitor models over time to ensure they are continuing to deliver the expected business results. 

4. From a technology perspective, consider the benefits of a unifying architecture.

Today’s analytics ecosystem comes with complexity. Organizations are using a mix of open source technologies, commercial software solutions, enterprise-hosted applications and cloud deployments to meet their analytics and data management needs.  The right platform will unify these disparate toolsets and analytic assets into a streamlined, governed and collaborative environment that delivers tangible, trusted results to your enterprise.

SAS® Viya^TM can help you embrace, experiment, integrate and unify all your analytics assets.

Let me know if you’re interested in learning more!

Tina Schweihofer is a Pre-Sales Manager at SAS Canada. She is passionate about helping people understand how high-performance analytics, coupled with the right data strategy can deliver real business benefits.  Tina leads a talented data sciences team that helps organizations across industries apply analytics to solve unique business problems using SAS. Tina can be reached at tina.schweihofer@sas.com

The analytics-driven business has become the rule, not the exception, and with good reason. Research has shown that analytics-driven businesses are more likely to have superior financial performance, make timely decisions, and execute their plans. No wonder growth in business investment in analytics continues apace, slated to reach over $70 billion (US) by 2022, according to Stratistics MRC.

But paradoxically, fewer businesses are driving appreciable differentiation from that investment, according to MIT Sloan Management Review. “The percentage of organizations gaining competitive advantage from analytics has declined significantly over the last two years.”

Why? I believe there are three primary roadblocks to squeezing competitive advantage from analytics:

• A lack of staff with the right training for the new analytics world.
• Disjointed and inefficient workflow processes.
• Siloed technology that makes communication and collaboration more difficult.

Incorporating data visualization into an analytics regimen can help address those pain points by simplifying the analytics process to make it more accessible to those without specialized data scientist training, allowing the exploration of and experimentation with huge data stores, and by reporting results in a common graphical language.

I’ve experienced these benefits first hand, while working with the Data Sciences team here at SAS. We have a mix of resources on the team; some are very senior and have very deep analytics expertise, while others are recent graduates and are just beginning their data science journey. The problem I faced, is that I needed a way to ramp up our junior resources on analytics processes and techniques quickly, so they could begin to collaborate with customers and gain some experience in the field.   I gave them access to SAS Visual Analytics very early in their training plan. This accelerated their analytics learning and gave them a platform they could use to collaborate with the more senior resources.  As a result, we were able to get them working with our customers, solving real-world business problems more quickly.

Interested in learning more?  

READ MORE IN OUR SAS INSIGHTS ARTICLE

WATCH OUR ON-DEMAND WEBCAST “DATA VISUALIZATION FOR DATA ANALYTICS 2018”

Tina Schweihofer is Pre-Sales Manager, Data Sciences, SAS Canada. She is passionate about helping people understand how high-performance analytics, coupled with the right data strategy can deliver real business benefits.  Tina leads a talented data sciences team that helps organizations across industries apply analytics to solve unique business problems using SAS. Tina can be reached at tina.schweihofer@sas.com

Judy Orr Lawrence

Location: Toronto, Ontario, Canada

Education:

BBM, Ryerson University

CPA/CGA

Using SAS since 1999        Teaching SAS since 2001

Professional Experience:

Business/finance/marketing/sales in the packaged goods industry.

Courses I teach include:

• Foundation Programming courses: Programming 1, Programming 2, Macro 1
• Enterprise Guide: EG1, EG2, EG for Programmers, EG Creating Reports 7 Graphs
• Customer Intelligence: SAS Marketing Automation Designing Campaigns, SAS Marketing Automation Defining the Data

What is the best part about teaching?

There is no room for boredom, there is always lots to learn.  SAS offers hundreds of courses, so as an instructor there is always something new to learn. Students teach us as well, just when you think you have heard all the possible questions, someone comes along and challenges you with an interesting twist.

Favorite activities:

Generally fitness/health related activities, currently it’s Pilates Barre. Using a Ballet Barre you get a high intensity workout that incorporates elements of Dance and Pilates to elongate muscles and work them to fatigue.

What are you favourite Apps and Websites?

Amazon Shopping, if you can’t find a product in a brick-and-mortar store you can find it on Amazon!

Allrecipes.com, lots of dinner ideas!

SAS Programming Professionals,

Check out this hack: http://michaelraithel.blogspot.com/2017/07/hack-55-using-macros-to-comment-out.html       

...excerpt from my book:  Did You Know That?  Essential Hacks for Clever SAS Programmers

http://tinyurl.com/zfd67rh

I plan to post each and every one of the hacks in the book to social media on a weekly basis.  Please pass them along to colleagues who you know would benefit.

Best of luck in all of your SAS endeavors!

----MMMMIIIIKKKKEEEE

(aka Michael A. Raithel)

Author of the new cult classic for computer programmers:  It Only Hurts When I Hit <ENTER>

Print edition:  http://tinyurl.com/z8bzx2e

Kindle edition: http://tinyurl.com/zypgqa7

Twitter: @MichaelRaithel

Louise Hadden

I have used SAS my entire adult life – much longer than the years I have owned a car! I love the capacity for order and logic, and the ability to access and present data in so many ways. I love to solve problems. I like to be challenged.

I like to think of new ways to solve old problems. I like talking to people about SAS and I like listening to people who talk about SAS.

In the conference setting, I seek at least one tip I can take home from my experiences.

Among many other things, at SAS Global Forum 2018:

1. I learned about using CSS stylesheets in the recently deployed Excel destination in Chevell Parker’s “Deep Dive” presentation.
2. I learned about creating Powerpoint slides with custom backgrounds in the ODS Powerpoint destination. The presentation was a SAS demo by an amazing technical support staff person and SAS author who I have consulted frequently with PROC REPORT questions, Jane Eslinger, and it incorporated information on several newer SAS reporting capabilities. She sought out my opinion and we’re going to Webex later this month.
3. I talked extensively to Sanjay Matange, who is a SAS developer with a wonderful blog, Graphically Speaking. I enjoy discovering new possibilities. I have long wanted to annotate images on maps, and that now looks like a possibility with the new PROC SGMAP procedure – not in an annotate step but as a procedural option. I find that so exciting.
4. I should also say that I took a pre-conference seminar & learnt MAGIC=101 / 102 / 103 procedural options in PROC SQL. It gives you more information in the log – another tip I took home from the conference.

That’s something I love about SAS conferences, talking to SAS developers, with whom we have unparalleled access to. SAS developers and technical support staff really care about SAS users and their challenges and what they want or need to do in their work. They share their expertise willingly and seek and approach challenges the way I do.

I also like to share my tips with people, and hope they take home something from my presentations that can inspire them. Collaboration is a powerful bonding agent. Being at a conference with like-minded people from all walks of life is an elixir like no other. I am an active member of a number of SAS groups, and have posted most of my papers on sascommunity.org (which is now read only – I’m searching for a new home for my papers – any thoughts?).

I must confess I haven’t seen a SAS tattoo before. Have you? Do you know anyone else that sports a cool SAS tattoo? Plus the generous list of takeaways she provided with all the papers she has written makes Louise a user to be admired. Now your turn dear reader. Do you maybe have any ideas to help Louise now with where to store her papers?

About Louise Hadden

Louise Hadden is a Lead Programmer Analyst with Abt Associates Inc., in the Division of Health and Environment. Louise has presented as a contributed and invited speaker at in-house, local, regional, national and global conferences since 1997 (SUGI 22!) for which she created her first SAS/Graph® maps. She loves a good SAS reporting challenge and spends her spare time enthusiastically traveling, reading voraciously and volunteering at a local animal shelter, walking and photographing dogs.

• Regina User Group - Tuesday, September 24, 2019
• Delta Regina
• Link to presentation archives

• Saskatoon SAS User Group - Fall 2019
• Location and time TBD
• Link to presentation archives