Data Science is the ability to take data — to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it — that’s going to be a hugely important skill in the next decades. SAS (previously "Statistical Analysis System") is a statistical software suite developed by SAS Institute for data management. In ACTE you will learn how to access data from variety of sources, create process to manage transform data and ensure reliability and consistency of data.Start Learning with us ACTE Data Science With SAS Classroom and Online Training Course.
Data Science With SAS is very useful for career. Data Science has become a revolutionary technology that everyone seems to talk about. Hailed as the ‘sexiest job of the 21st century’, Data Science is a buzzword with very few people knowing about the technology in its true sense. While many people wish to become Data Scientists, it is essential to weigh the pros and cons of data science and give out a real picture. In this article, we will discuss these points in detail and provide you with the necessary insights about Data Science.
Data Science is one of the most highly paid jobs. According to Glassdoor, Data Scientists make an average of $116,100 per year. This makes Data Science a highly lucrative career option.
Data Science With SAS, have great scope, Scope is high as I can see from news and media…But still their is always a risk involved in everything you do or opt.
Valuable! But really depends how you have earned them. If you have really invested the effort in learning and reading for that certificate then it is worth and you know there are other ways of getting those. Have come across people who are certified and do not know the basics.
Even as a fresher, you can get a job in Data Science With SAS domain. Well to get you started with Data Analytics, the answer would be Yes R and SAS are sufficient. But on the long run definitely a big no no. You must understand Data Analytics is a very versatile field and the amount of data generated is different for different organisations. The sources that generate this data differ.
We are happy and proud to say that we have strong relationship with over 700+ small, mid-sized and MNCs. Many of these companies have openings for Data Science With SAS. Moreover, we have a very active placement cell that provides 100% placement assistance to our students. The cell also contributes by training students in mock interviews and discussions even after the course completion.
The program you signed up for is US only, but we can make exceptions if the other country agrees that payment may be made with your SAS Training Points. Please be aware that pricing for training varies greatly outside the US, and there is no guarantee of receiving a discount. Contact your education account representative to assist you with this request.
- SAS Base Programming.
- SAS SQL Programming.
- Any programming language experience is must.
- Good knowledge of mathematics.
- Good analytical skills.
- Writing logic for detecting patterns and trends.
It is absolutely possible to learn Data Science without a computer science or mathematics background. It is also possible to get a job. There are three main Data Science skills that one must be required these are programming, statistics and business knowledge.
Our course ware is designed to give a hands-on approach to the students in Data Science With SAS. The course is made up of theoretical classes that teach the basics of each module followed by high-intensity practical sessions reflecting the current challenges and needs of the industry that will demand the students’ time and commitment.
Yes It is worth , Absolutely. Well, the point is nothing you learn is waste. SAS is a pretty good deal these days. Learn SAS and further you can aim for data science and as you know we are dealing with immense data these days. Data is flowing like anything and every single bit is important in its own sense. So future generations needs some kind if technology to handle this immense data and SAS is pretty much good in handling huge data volumes. So you can take a risk and go for it.
You might be surprised by how quickly you can learn SAS. The entry-level SAS Programming 1: Essentials course is only two days long, while the Statistics 1 course is three days long (both are available as free e-learning courses). You’ll need to factor in some practice time, and you may want to supplement your learning with free video tutorials or books for novice users – but overall it’s a fairly quick process.
- If you know SAS, you are in demand.
- It is one of the best in handling data.
- With deep knowledge you can manipulate the functionalities.
- You are powered by an efficient customer service facility.
- SAS follows the global lead.
Future scope of SAS
There is a huge scope of SAS for fresher. Banks are heavily using SAS as are Insurance and other Financial Services companies like Citi, HSBC, JP Morgan, and Wells Fargo. The reasons are:
- They have been using SAS for ages and have systems built around SAS.
- SAS is safer than open source tools like R, very important for Data Security and Basel II norms and more statutory norms.
- SAS has introduced big data capabilities along with SAS JMP and SAS Visual Analytics.
- Production level capability: SAS can put your analytics into production in banking and financial systems.
SAS Job Profiles with respect to Data science
- A SAS analyst, unlike a SAS programmer, is a business, or financial risk, an analyst who relies on SAS software products as his, or her, primary analysis tools.
- The collection, and analysis, of data to reveal patterns, and anomalies which can, in turn, be used to predict future trends, and forecast cost to an organization.
- Development, management, and delivery of statistical analysis techniques for a business database analysis.
- A SAS Programmer, under general guidance, designs develops, evaluates and modifies SAS (Statistical Analysis Software) programs to analyze and evaluate data.
- Assesses data accuracy and consistency.
- Develops data listings and other reports necessary for clinical studies and study reports.
- Tests, documents and integrates software tools into programming procedures.
- Identify and manage external partners for delivery of specialized data science services
- Define and implement world-class data science practices to ensure that insights are timely, robust, repeatable, and trust-worthy.
SAS Careers in India
- CrossTab
- Modelytics
- Pharmacy
- Amba Research
- Genpact and Symphony Marketing solutions
- Infosys
- Wipro
- Capgemini
- Mahindra Satyam
- IBM
- Accenture
Career opportunities and Scope of Data Science
Data Scientist
Data scientists examine which questions need answering and where to find the related data. They have business acumen and analytical skills as well as the ability to mine, clean, and present data. Businesses use data scientists to source, manage, and analyze large amounts of unstructured data. Results are then synthesized and communicated to key stakeholders to drive strategic decision-making in the organization.
Skills needed:Programming skills (SAS, R, Python), statistical and mathematical skills, storytelling and data visualization, Hadoop, SQL, machine learning
Data Analyst
Data analysts bridge the gap between data scientists and business analysts. They are provided with the questions that need answering from an organization and then organize and analyze data to find results that align with high-level business strategy. Data analysts are responsible for translating technical analysis to qualitative action items and effectively communicating their findings to diverse stakeholders.
Skills needed:Programming skills (SAS, R, Python), statistical and mathematical skills, data wrangling, data visualization
Data Engineer
Data engineers manage exponential amounts of rapidly changing data. They focus on the development, deployment, management, and optimization of data pipelines and infrastructure to transform and transfer data to data scientists for querying.
Skills needed:Programming languages (SAS, Java, Scala), NoSQL databases (MongoDB, Cassandra DB), frameworks (Apache Hadoop)