Non-traditional (and surprising) applications of big data analytics

Big data analytics have become a standard in many industries and it has been a game-changer for many businesses around the world.

Around 55% of companies around the world use big data analytics to improve their performance and keep an eye out for changes in the market and customer behaviour.

Over the years, big data analytics have opened new horizons for all kinds of industries. That being said, big data is also being used in some very surprising ways that we would have never imagined in the past.

In this post, we’ll take a look at these non-traditional applications of big data analysis.

Smart parking

Smart transport solutions are quickly becoming a feature in most modern cities around the world and where there is smart transportation, smart parking technology will follow.

Today, real-time big data and information from the payment systems in parking lots are used to provide smart parking solutions to drivers. 

With big data on weather patterns, daily events, the amount of time a car spends in the lot and the time of day, parking lot staff can find ways to maximise parking prices and utilise the space in the parking lots effectively.

Organisations that require large parking spaces, like hospitals, airports and community centres can optimise their revenue and staffing strategies effectively thanks to big data analytics.

According to Wen Sang, the CEO of Smarking, airports generate about 20% of their revenue through parking; this revenue can potentially increase if airports adopt big data analytics.

Emotions

Demographics like age, race, social standing, gender and sexuality play a major role in determining how potential customers will react to marketing. Understanding the emotions that these marketing campaigns and advertisements instil is also important.

The emotional effect an advertisement has on people will determine how they will see the product and how they will interact with the business. Now, big data analytics can be used to measure the emotional impact these campaigns have on people.

Data collected using facial recognition software on videos or photographs of people reacting to the advertisements is analysed to gain insight into what emotions people feel when they viewed the advertisements. 

If people displayed emotions a business expected from them, the advertisement would be a success and they can predict how potential customers will approach them and their product.

Using this emotional data, businesses can further optimise their campaigns for desired reactions from their customers.

Big data analytics on emotions is also being used in the movie industry, especially to measure how people react during horror movies. With big data, movie studios can identify what kind of content brings out fear in their audience and make horror movies that scare people the way they want to be scared.

Movie scripts and casting

Film production companies want their movies to engage their audience and their cast to be relatable.

Nowadays, film companies use big data gathered from streaming services and social media to get an idea of the kind of stories people want to watch, with the actors that viewers feel are most suited for certain roles.

According to some filmmakers, movies have become very commercialised and tend to follow similar patterns and stories. Major film companies do this to protect their investment in these movies.

Big data helps film companies have a better understanding of the current trends and what moviegoers are interested in, enabling the creation of more unique and diverse content that can satisfy a range of audiences.

Music icons

Every decade or so, a new musician walks into the scene and quickly becomes popular with the masses. 

Thanks to the internet, social media and data collection technology, it’s possible to predict who will become a superstar in the music industry.

Recording companies are always keeping an eye out for new talent and today, they use big data analysis to find their next profitable music icon.

These companies use data analysis software to gather big data from a potential music icon’s social media to gauge their popularity and decide if they are worth investing in. They can also use this data to identify which social media platforms the musician has the biggest following on, and use this platform for their marketing campaigns.

Big data analytics pave the way for many new possibilities

The number of potential uses for big data analytics is seemingly endless. 

From filmmaking to measuring emotions, big data analytics can cater to virtually every industry and leverage their success.

Jupyter with SAS Analytics Pro (cloud-native)

The new containerised version of SAS Analytics Pro from the SAS Institute opens up a world of possibilities for leveraging third-party technologies to enhance what is already a pretty powerful Data and Analytics platform.

One of these technologies that has really taken off and helped Data Scientists take advantage of a unified programming experience regardless of the language used is Project Jupyter. A core feature of Project Jupyter is known as a Notebook, and this is explained on the Jupyter site as “…an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text“. This not only makes it an easy, pleasant experience to work in but also facilitates the ability to present complex processes in a nice visual manner to non-programmers – kind of like reading through a notebook 🙂

Jupyter can also be used for SAS programming, and as part of our SAS Analytics Pro Launcher (available at https://github.com/Selerity/sas-analytics-pro/releases) you can enable this functionality with a simple change to the settings file!

Enabling JupyterLab in the Selerity Launcher for SAS Analytics Pro

If you have followed our previous post, Cloud-native SAS Analytics Pro – for your Desktop!, you will have a functioning SAS Analytics Pro container environment that leverages our custom Launcher (available on GitHub).

To enable Jupyter in your environment, open up the apro.settings file in your $deploy directory (the location where you unzipped the Selerity Launcher code) and set JUPYTERLAB to true.

# Enable Jupyter Lab?
JUPYTERLAB=true

Stop your SAS Analytics Pro container if it is currently running with the following command:

docker stop sas-analytics-pro

Now start your environment back up by running the launchapro script again. When you launch your environment with JUPYTERLAB=true the following things happen behind the scenes (all transparent to the user):

1. A virtual Python 3.9 environment is created in /python (the python directory in the repository)
2. The bits-and-pieces required to run JupyterLab and Jupyter Notebooks are installed to /python
3. The SAS Kernel for Jupyter is installed to /python and configured to use SAS in your SAS Analytics Pro container
4. Jupyter Lab is started up after SAS Studio is started

Depending on the speed of your internet connection it could take up to 15 minutes for all this to happen, but as long as you don’t delete the python directory all subsequent startups should be just as quick as before. This is what the startup process looks like with JupyterLab enabled:

#############################################
#    SAS Analytics Pro Personal Launcher    #
#-------------------------------------------#
# S = SAS Studio has started                #
# J = Jupyter Lab has started               #
#############################################
.....S..J
Password=aS7yiXxtA0
To stop your SAS Analytics Pro instance, use "docker stop sas-analytics-pro"

Using Jupyter

Open your browser to http://localhost:8888 and enter your generated password. You will then be presented with the JupyterLab main interface:

You can click on the SAS icons in the Launcher to create a new Notebook using the SAS Kernel, and then start writing your SAS code. Click the play button to submit your code:

Hosted Option

If you would prefer to just login-and-start-using Jupyter with SAS Analytics Pro, our Selerity Analytics Desktop offering provides SAS Analytics Pro as-a-service (including Jupyter), which can also be integrated into your existing IT infrastructure if required. This allows you to leverage you existing security, login credentials and code assets without needing to maintain your own SAS infrastructure. Contact us if you would like to learn more!

Cloud-native SAS Analytics Pro – for your Desktop!

In August 2021 SAS released a cloud-native version of SAS Analytics Pro. This release is based on the SAS Viya Platform and provides the full features of Base SAS, SAS/STAT and SAS/GRAPH via SAS Studio – a browser-based interface that users of recent SAS 9.4 and SAS Viya server environments will be familiar with.

The cloud-native version also adds the full SAS Viya set of SAS/ACCESS products, giving you access to many data sources!

Containerisation

This new release of SAS Analytics Pro leverages container technology, which means that the concept of installing your software is no longer just a matter of running “setup.exe”. The benefits of containerisation are many and include:

1. Ability to run on Windows, Mac and Linux
2. A consistent environment – e.g. your install is not going to be different from your colleague’s
3. Ease of updates – SAS regularly update and patch their software. Previously this meant finding, downloading and installing those updates. Now you just have to “point” to the release of SAS (including updates) you want to use
4. Portability – if you get a new PC (or move from PC to Mac) you just need to copy your config across

Deploying cloud-native SAS Analytics Pro

SAS provide a comprehensive set of instructions to get up and running which involve:

1. Installing Docker (the software used to run containers)
2. Logging into my.sas.com to get your license and certificate files
3. Creating a script to startup your SAS Analytics Pro environment

On the surface, this seems pretty straightforward, but in case users feel a bit hesitant or unsure (especially when it comes to creating a launch script) we have created a “launcher” process to help you out. Our process mirrors the official SAS process but we provide the script, along with a simple way to tweak the features you want to add.

SAS Analytics Pro Launcher from Selerity

The first step is to download and install Docker from https://www.docker.com/products/docker-desktop.

Next, navigate to our GitHub repository and download the source code of our launcher that matches the SAS Analytics Pro version you want to use: https://github.com/Selerity/sas-analytics-pro/releases

Extract the ZIP file to a location on your machine, e.g. C:\SAS. The final directory (referred to as the $deploy directory) will be a subdirectory of this location created as a result of the unzipping, e.g. C:\SAS\sas-analytics-pro-2021.1.4.

Now log into my.sas.com and go to the “My Orders” section. In here, expand your SAS Analytics Pro Order and then click both the Download Certificates and Download License Only links. Save the file that each link provides to the directory created when you extracted the ZIP file, e.g. C:\SAS\sas-analytics-pro-2021.1.4

Finally, open a PowerShell (or Terminal on Linux/Mac) prompt, “cd” into the $deploy directory (created when you extracted the ZIP file) and then run launchapro.ps1 (or launchapro.sh on Linux/Mac)

After a minute or so you see a message letting you know that SAS Analytics Pro is up and running!

You can now open your browser and log into SAS Studio at http://localhost:81 using the same username you logged into Windows with along with the generated password that is displayed.

Customisation

There are many ways that this SAS Analytics Pro environment can be tailored/customised and we have provided some of the key options available within the apro.settings file that comes with our launcher. This file contains comments explaining each option, which we also document in the CONFIGURATION.md file.

Hosted Option

If you would prefer to just login-and-start-using SAS Analytics Pro, our Selerity Analytics Desktop offering provides SAS Analytics Pro as-a-service, which can also be integrated into your existing IT infrastructure if required. This allows you to leverage you existing security, login credentials and code assets without needing to maintain your own SAS infrastructure. Contact us if you would like to learn more!

Cracking down on insurance fraud with SAS Detection and Investigation

The insurance industry is one of the most important industries in an economy-not only does it provide a respite for individuals when they face financial losses, medical expenses, or retirement, but it also helps governments finance development initiatives to keep the economy stable.

In addition, insurance payments prevent businesses from bankruptcy and help keep essential employees at work. The insurance industry even has a hand in bringing food to our tables, as agri businesses rely on insurance payments to keep their fields and farms open despite floods, droughts and other natural disasters.

All of this means that insurance companies collect, process, and store sensitive information of millions of policyholders, making processing insurance claims an arduous and time-consuming task. 

These companies receive thousands of insurance claims each year, and the amount of data to be processed and reviewed has created major bottlenecks in their due diligence process. 

Sensing this vulnerability, offenders are filing an increasing number of fraudulent claims each year, with relative success, resulting in insurance fraud close to $80 billion annually.    

That said, insurance providers are now looking for better, more holistic ways of investigating insurance claims. SAS Detection and Investigation for the insurance industry might be the tool they need.

The impacts of insurance fraud

When people think of insurance fraud, they assume that only the insurance companies are affected, though in reality, the repercussions affect every single policyholder paying premiums.

Successful fraudulent claims increase the premium for policyholders across all different insurance schemes. In the USA, for example, insurance fraud costs an average family between $400–$700 a year.

They also lengthen the review process of all insurance claims, increasing the waiting period for deserving customers, who require swift insurance payouts—leading to loss of customer loyalty, and ultimately, revenue.

Establishing the current insurance fraud landscape

Across the world, insurance fraudsters use different methods to manipulate the insurance claim due diligence process. In Europe, insurance fraud is an organised crime by gangs.

In other parts of the world, fraudulent insurance claims involve individual claimants inflating the value of their losses or damages to receive heftier payouts. Ghost broking is another emerging type of insurance fraud, where fraudsters target a single type of insurance product.

Although the traditional claim review process identifies the common traits of insurance fraud, it takes a considerable amount of time, and some claims can eventually slip through the cracks.

How can SAS Detection and Investigation for Insurance help?

Traditionally, claim investigation units hold data related to all insurance claims, including historical claims data, policy details, and specifics related to the particular claim. These units operate independently of similar teams from other insurance providers, creating a data silo.

If fraudsters target new insurance providers for their claims, the lack of integration between different claim investigation units means that these claims may get approved without information on historical claims from other providers by the insurer.

Anti-fraud systems like SAS Detection and Investigation for Insurance help improve integration between departments of insurance providers, improving information availability across the industry.

Improved data availability means investigation units can identify obvious common traits of fraudulent claims across the entire network and flag fraudulent claims—reducing the probability of a fraudulent payout.

These systems can also help enforce a holistic due diligence process and help achieve the two primary objectives of insurance claim investigation; detect and flag fraudulent claims for an in-depth review, and approve legitimate claims of customers in need.

SAS Detection and Investigation for Insurance is the hero the industry deserves

Insurance fraud is becoming an increasingly common occurrence, with one in ten claims being fraudulent. 

In this vulnerable landscape, insurance providers need to work together and open up their data silos to enforce a robust claims investigation process across the industry.

Data analytics tools like SAS Detection and Investigation can streamline this process by reducing fraudulent claims and speeding up the review process, leading to high customer satisfaction and loyalty.

How SAS managed services can help businesses leverage the power of data analytics

What do mega-corporations like Apple and YouTubers have in common?

Well, both parties use data analytics to make business decisions.

Whether it’s marketing or product development decisions by the $2-Trillion Apple Inc or decisions on content ideas by YouTubers with a few hundred thousand subscribers, data analytics plays a critical part in the decision-making process.

More and more companies are jumping on the analytics bandwagon after realising the benefits offered by data analytics.

Data analytics platforms facilitate this shift to data-backed decisions by offering analytics services that span a large spectrum of real-world applications. According to Statista, analytics platforms facilitate the use of data in market monitoring, manufacturing and much more.

While there are many data analytics platforms, none are more popular than SAS, the data analytics industry leader. Today, organisations both big and small use SAS’ data analytics platform to obtain actionable insights.

Businesses, however, require SAS managed services such as installation, administration and hosting services to leverage the full potential of their analytics. In this post, let’s explore how SAS managed services help organisations optimise their analytics deployment.

SAS installation services

Not all organisations are created equal. The needs and requirements related to data analytics deployment differ, accordingly, across each organisation.

Certain companies may need to deploy their analytics platform on a single server setup. Others might require more expansive deployment setups spanning multiple servers both locally and on the cloud.

A standard SAS installation may not meet your team’s specific requirements. SAS installation services provided by managed service providers, on the other hand, help you meet these varying requirements. These types of Installation services also help you get the best return on your SAS analytics investment by customising your deployment according to your specific requirements.

SAS installation services also give you the benefit of leveraging the services of SAS-qualified industry experts who work with you to meet your analytics needs.

SAS admin services

The effective deployment of a SAS business solution, alone, won’t help you leverage the full power of your SAS analytics platform.

That’s because it needs to be maintained and tested constantly to weed out any issues that may arise as part of your deployment. The resolution of these issues, however, requires extensive knowledge not only of your general SAS platform but your customised deployment as well.

While bigger organisations employ in-house SAS administrations to resolve these issues as they arise, that is not a luxury every organisation can afford. Most entities either don’t have the financial resources or the human resources for a dedicated SAS administrator.

Dedicated SAS admin services eliminate the hassle of managing and maintaining the platform and give you more time to extract actionable insights from your deployment.

SAS admin services act as your point of liaison with SAS, making the update, maintenance, troubleshooting and fixing of your SAS deployment easier and cost-effective.

SAS hosting services

One of the most critical issues facing organisations is the scalability of their analytics infrastructure. Traditional organisations rely on on-site servers to deploy SAS analytics solutions, making it harder to scale as analytics requirements become more complex and expansive.

That’s why many modern organisations are migrating their analytics deployment to cloud-based servers. Migrating your SAS deployment by yourself, though, is not necessarily straightforward as you have to figure out certain prerequisites before moving to the cloud.

With SAS hosting services, you’re free of dealing with technical requirements because SAS experts take care of everything from migrating your data to cloud servers to configuring AWS to meet your requirements.

Leverage SAS managed services to optimise your SAS deployment

SAS has become the leading name in the data analytics industry with its business solutions, which cater to various applications ranging from historical data analytics to preventive analytics.

Leverage the power of SAS with the support of managed services providers who take care of the installation, hosting and administration of your analytics deployment. Make use of these services to optimise your analytics platform today.

How SAS business solutions improve organisational performance

What would your answer be if someone asked you what the most valuable asset to modern organisations is?

Well, the results are out. According to CEOs, data is the most critical and valuable asset to any business, regardless of whether it is a multibillion-dollar tech company or a small family-owned bakery.

The reason?

Modern businesses are largely dependent on data to make the right decisions. Data-backed decision-making makes modern businesses more efficient than businesses of the past, whose choices relied on nothing more than unscientific instinct and gut feeling.

Any team that doesn’t leverage the power of data analytics, today, is in danger of losing its edge in the market. 

Fortunately, there are several tools available for modern businesses to take advantage of the rich reserves of data that are often readily available. 

SAS solutions, in particular, help businesses access actionable insights with advanced analytics tools, which are influential in making business decisions that improve organisational performance over time.

What are SAS business solutions?

SAS solutions are data analytics platforms that use AI and machine learning to collect and analyse vast amounts of data, giving you the insight you need to make critical decisions. 

SAS business solutions cater to specific industries, such as education, healthcare, and technology, making it easier to resolve issues and devise innovative solutions that improve revenue and profitability.

SAS business solutions help organisations navigate demand and supply volatility

Demand and supply are two of the most volatile economic forces that any business has to grapple with. Mishandling these forces can lead to lasting impacts on organisational performance.

Restaurants, for example, have to predict demand on a daily basis to be able to react to changes in demand caused by various factors like seasonality, consumer preferences and unexpected events like the current pandemic.

Unfortunately, more than 50% of restaurants do not handle these shocks in demand efficiently and go under fairly quickly.

With predictive analytics tools like SAS, restaurants can predict potential disruptions in demand and be prepared to handle these disruptions, improving their performance.

Data analytics also help businesses handle disturbances in supply as well.

The global semiconductor shortage, for example, forced many companies across various industries to cut down on expected production output. Certain companies, however, were able to foresee the chip shortage in advance thanks to data analytics tools like SAS and prepare more resiliently. 

Data analytics can help organisations make better investment decisions

The majority of modern businesses diversify their returns by investing in various investment opportunities and assets. By diversifying returns, it’s easier to mitigate financial risks, which can lead to bankruptcy if they’re not managed.

Before the advent of data analytics, however, business owners relied on their knowledge of market conditions to make investment decisions. Modern analytics tools, however, help businesses choose the most appropriate investment avenues by providing insights on critical factors like the level of risk and return on investment.

These types of data-backed investment decisions ensure the financial agility of modern businesses, allowing them to improve their financial performance in a very flexible manner.

SAS business solutions help organisations offer hyper-personalised services

Most modern organisations offer personalised services to their clients and customers, creating deep, long-lasting relationships.

Did you know, however, that offering personalised services is made easier, efficient and more effective with data analytics?

While it’s true that small businesses offer a certain level of personalisation without the use of data analytics, larger organisations need these insights, through tools like SAS, to create customer profiles, which are critical in creating a personalised customer experience as they contain information like customer preferences.

Using these insights, business teams are able to provide a level of service that is tailored to specific interests and priorities, providing customers and clients with an exceptional buyer experience.

Are you ready to supercharge your performance with the power of SAS business solutions?

Data analytics has become a buzzword for organisations looking to improve their performance and increase their edge in the market. 

With petabytes of data readily available for businesses to use, data analytics tools like SAS are helping organisations improve their performance across the board.

Find out how you can use these solutions and insights to change how you do business today.

5 Categorical Feature Encoding Techniques in SAS

What is Categorical Feature Encoding?

Categorical variables are usually represented as strings in limited numbers while categorical feature encoding is the process of converting data into a format understandable by machine learning models.

The performance of machine models depends on several factors. One factor that determines performance of the models are the methods used to process data and feed it to the model. As such, encoding data is a crucial process because it converts data into categorical variables understandable by machine learning models. Encoding data elevates model quality and helps in feature engineering.

In this blog, we explore the different classic encoding methods along with a snapshot of how each encoding method works in SAS Macro.

1. Label Encoding

Label Encoding assigns the value of 1-N to a class of categorical features. For instance, if there is a variable “Hair color” with values of Black, Brown, and Red, Label encoding will replace these values with 1, 2, and 3. However, one problem with Label Encoding is that it does not consider the order or any relationship between class levels. This will not stop machine learning algorithms from treating them in this incorrect order, which may lead to inaccurate readings.

SAS Macro for Label Encoding

Here is an example macro to perform Label Encoding in SAS:

%macro label_encode(dataset,var);
   proc sql noprint;
     select distinct(&var)
     into:val1-
     from &dataset;
 select count(distinct(&var))  into:mx from &dataset;
 quit;
 data new;
     set &dataset;
   %do i=1 %to &mx;
     if &var="&&&val&i" then new=&i;
   %end;
   run;
 %mend;

2. Binary Encoding

Binary Encoding converts class values into numeric values, like Label Encoding does. However, Binary Encoding takes it a step further and converts the numeric values into binary numbers where each digit will have their own separate column.

“If there are n unique categories, then binary encoding results in the only log (base 2) ⁿ features”.

For more information, visit here.

SAS Macro for Binary Encoding

Here is an example macro for Binary Encoding in SAS:

%macro binary_encoding(dataset,var);
 proc sql noprint;
     select distinct(&var)
     into:val1-
     from &dataset;
 select count(distinct(&var))  into:mx from &dataset;
 quit;
 data new;
     set &dataset;
   %do i=1 %to &mx;
     if &var="&&&val&i" then new=&i;
   %end;
     format new binary.;
   run;
 %mend;

This macro creates a single variable with a binary formatted value. To split those values into multiple columns, you could create a Split Column Macro.

SAS Macro for Splitting Column

Here is an example macro for splitting columns in SAS:

%macro split_column(data,var);
   data try;
     set &data;
     cha=put(&var, binary.);
   run;
 proc sql noprint;
     select max(length(cha)) into :ln from try ;
   quit;
 data &data;
     set try;
   %do i=1 %to &ln;
       c_&i=substr(cha,&i,1);
   %end;
   run;
 %mend;

3. One-Hot Encoding

One-Hot Encoding is the process of converting categorical variables into 1’s and 0’s. The binary digits are fed into machine learning, deep learning, and statistical algorithms to make better predictions or improve the efficiency of the ML/DL/Statistical models.

SAS Macro for One-Hot Encoding

Here is an example macro to do One-Hot encoding in SAS:

%macro hot_encoding(data,var);
   proc sql noprint;
     select distinct &var 
       into:val1-
     from &data;
 select count(distinct(&var))   into:len from &data;
 quit;
 data encoded_data;
     set &data;
   %do i=1 %to &len;
       if &var="&&&val&i" then %sysfunc(compress(&&&val&i,'$ - /'))=1 ;
       else  %sysfunc(compress(&&&val&i,'$ - /'))=0;
   %end;
   run;
 %mend;

4. Count/Frequency Encoding

As the name suggests, Frequency Encoding counts unique class values, then divides it by the total number of values. This encoding technique helps the model understand and assign the weight either inversely or directly.

SAS Macro for Count/ Frequency Encoding

Here is an example of a macro for Frequency Encoding in SAS:

%macro frequency_encoding(dataset, var);
   proc sql noprint;
     create table freq as 
     select distinct(&var) as values, count(&var) as number
     from &dataset 
     group by Values ;
 create table new as  select *, round(freq.number/count(&var),00.01) As freq_encode  from &dataset  left join freq    on &var=freq.values;
 quit;
 data new(drop=values number);
     set new;
   run;
 %mend;

5. Effect/Sum/ Deviation Encoding

The Deviation Encoding technique has different names, like Effect encoding, some analysts call it Deviation Encoding, and some say Sum Encoding, but the meaning and the definition is the same. Deviation encoding is the same as Hot Encoding, but the only difference is if there are 0 values in all the columns, then the values will become -1. For example

One Hot Encode

Effect/ Sum/ Deviation

SAS Macro for Effect/Sum/ Deviation Encoding

Here is an example macro for Deviation Encoding in SAS:

%macro sum_encoding(data,var);
   proc sql noprint;
     select distinct &var 
       into:val1-
     from &data;
 select count(distinct(&var))   into:len from &data;
 quit;
 data encoded_data;
     set &data;
   %do i=1 %to &len;
       if &var="&&&val&i" then %sysfunc(compress(&&&val&i,'$ - /'))=1 ;
       else  %sysfunc(compress(&&&val&i,'$ - /'))=0;
   %end;
   run;
 data sum_encode;
     set encoded_data;
     if %sysfunc(compress(&&&val&Len,'$ - /'))=1 then do;
     %do x=1 %to %eval(&len-1);
           %sysfunc(compress(&&&val&x,'$ - /'))=-1;
     %end;
     end;
     drop %sysfunc(compress(&&&val&Len,'$ - /'));
   run;
 %mend;

Wrapping Up

A data scientist spends over 70-80% of their time cleaning and preparing data, which means encoding or converting categorical data is a crucial part of their work. However, it is important to select the right encoding technique to ensure data quality, which is why it is important to understand the different encoding methods.

If you are looking for more information, more specifically, on SAS Macro Definition code, you can check it out here.

Why SAS business solutions are the top choice for data science and analytics

Technology is developing at a breakneck pace, and analytics is no exception. While SAS business solutions are still the leading analytics platform for most major organisations, other languages have started to make significant inroads into the market, as well. However, there is no denying that SAS is still the preferred choice for most organisations. In our latest blog post, we explore why SAS software is still one of the leading platforms in the analytics industry, despite fierce competition.

What are SAS data analytics?

SAS, previously known as the Statistical Analysis System, is a platform developed by the SAS Institute for data management, advanced analytics, business intelligence and predictive analytics. 

Using a combination of cloud computing, artificial intelligence, and machine learning, SAS data analytics solutions can collect and analyse vast amounts of data to provide actionable results which can be leveraged to get better insights into business operations and refine strategies to accomplish business goals.

Why SAS business solutions remain the top choice for organisations

It is more than a programing language

First, it is important to keep in mind that SAS software is more than just a programming language. It is a data analysis framework that comes with a GUI. When installed, there is a lot of functionality on offer, like report writing, data retrieval, and operations research.

This provides incredible value for organisations that are looking for cost-effective ways to complete several data collection and analysis functions. SAS delivers incredible value to organisations by creating a more efficient data analysis process.

SAS applications are still valuable

Despite the growth in popularity of other programming languages, SAS remains prominent because it is still a highly sought after platform. Several prominent business surveys have reported that SAS business solutions are still highly valued amongst organistions, especially those operating in healthcare, finance, and public service.

Furthermore, research also shows that several data analytics professionals above a certain tenure prefer SAS over other progamming languages.

SAS offers better data handling capabilities

Given the growing volume of data, organisations are looking for platforms that can process it efficiently. This is where SAS platforms offer tremendous value over other programming languages.

SAS business solutions are designed to handle large volumes of data. Considering that most organisations are generating big data, a platform specifically optimised to process it would reap huge benefits for the organisation.

SAS works with the latest technology

Organisations are looking to incorporate the latest technology into their operations. Technology, like cloud computing and IoT devices, are playing more prominent roles in business operations as organisations look for ways to reduce expenses. SAS business solutions are perfectly suited for this because it works seamlessly with cloud and IoT devices.

SAS is offering several cloud-based products, like SAS Cloud, allowing organisations to cut operation costs and generate insights at a faster rate. Furthermore, SAS and Microsoft have also partnered to bring more cloud-based SAS industry solutions to its customers.

SAS is easy to learn

While open-source languages have their advantages, in terms of accessibility, it does not mean that SAS software is a slouch in that department either. In addition to its GUI, SAS applications provide PROC SQL, making it more accessible to anyone familiar with SQL. Furthermore, there are several certifications and training courses on offer to help potential analysts become more familiar with the language.

SAS is constantly being updated

One of the main benefits of open-source languages is that it is easy to expand its capabilities. However, SAS receives regular updates as well. Even though it’s not open-source, SAS is updated to expand functionality, making it easier to keep up with industry and client demands.

Furthermore, SAS products are tailoured to address industry specific problems. For example, SAS has developed a solution to aid the fight against the spread of COVID-19. The model helps optimise operations vital for curtailing the spread of the virus, like critical response and medical resource management.

What can SAS do to pave the way for the future?

Despite fierce competition, SAS remains one of the leading firms for data analytics software. However, there is no denying that there are some issues SAS can address. For example, one of the biggest complaints is the cost of investing in SAS. While some third-party solutions make SAS analytics more accessible, SAS would do well to assess the appeal of open-source technology and see how they can incorporate some of those benefits into their product offering.

The data analytics industry is constantly evolving. This inevitably means new alternatives entering the industry. However, SAS has been an industry leader for over thirty years because of its ability to adapt to meet changing expectations. While there is no denying that SAS business solutions need to evolve, they remain relevant in the data science and analytics industry.

4 reasons to invest in SAS software for accounting

When determining what accounting software is best for your business, you will need to consider the size of your company (as measured by the number of transactions), the type of platform you prefer, the complexity of your business and what you are willing to pay. This is where SAS software for accounting can help you. The platform is designed to help organisations optimise accounting and financial operations.

Here are some reasons that make SAS software for accounting one of the best assets an organisation can have.

Easy-to-use interface

There is often a growing dichotomy between technical requirements and work culture. On one hand, the collaboration between professionals of different specialities is important. However, if professionals with non-technical background have difficulty accessing data, it is hard to foster that collaborative environment organisations need. This is where SAS software for accounting comes into play.

With its clean interface, the platform is designed to ease accessibility. The simple user-interface is not bloated with unnecessary features but includes all that is vital to the success of your organisation. The clean interface makes it easy to focus on the important tasks and reduce the learning curve for professionals so that your organisation can embrace a collaborative work process to deliver better results.

Look for a fast and efficient system

Close your books faster by letting your SAS software for accounting perform on-demand consolidations – including automatic currency conversion, intercompany eliminations, ownership adjustments, allocations and operational efficiency.

The primary reason an organisation would invest in accounting software is to alleviate the burden of work, time spent on operations and ensure that no errors would occur. With cutting-edge software, like machine learning and AI, organisations can generate more accurate forecasts and speed up operations to reduce the occurrence of errors. Say hello to optimal efficiency with the right accounting software.

Budgeting and financial planning without the fuss

Perhaps one of the biggest benefits is that it will allow your business to perform complex accounting tasks relatively efficiently. Since the software is accessible, you can ease the workload on your finance team and avoid employing extra manpower during busy fiscal periods.

With SAS software for accounting, you will be able to utilise intelligent forecasting to efficiently optimise your financial planning strategy. The software also allows you to dive into the deep end of rolling forecasts, budgeting, workflow control and budget cycle seeding without bogging you down with the complex calculations of it all.

Support services offered

This is the most important but most ignored factor while selecting SAS software for accounting. No matter how good or easy the software is, you will need support at some point and if you have nobody to talk to when you are stuck, the quality and efficiency of operations will be compromised.

SAS software for accounting is a complex infrastructure that requires SAS specialists. Specialists can not only install but also tweak the SAS platform to suit your data infrastructure and provide administrative services to ensure that the analytics platform is working in optimum condition so that it continues to deliver accurate, timely insights at all times. Selerity is well-versed in installation, administration and hosting services, making it perfectly placed to assist you with any support services you might need for SAS software.

Is SAS software for accounting for you?

By using SAS software for accounting, you’re guaranteed transparency and accuracy. A reliable solution is created and programmed to deliver data on time, calculate accurately and avoid errors. As such, you’re guaranteed to get transparent and easily understandable reports on your company’s finances. This, in turn, will help you come up with programs and strategies that are specific to the needs of the company. Likewise, identifying the quantity and type of resources needed will also become an easier task.

Using the software increases productivity levels in your business. As an all-in-one system, SAS accounting software performs essential tasks and helps companies fulfil their objectives. Aside from collecting data, particularly financial data, the software also organises and analyses all the information it gathers. It also helps make the accounting team’s work easier, as the software usually comes with tax compliance features, particularly those dedicated to payroll assistance.

For more information on SAS software for accounting, please visit our website.

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