Learn SAS Big Data credentials equal big professional value with Epoch SAS Training (www.epoch.co.in)

SAS Big Data Analytic's: SAS Authorised Training Partner Epoch Research Institute (Ahmedabad | Bangalore|Chennai)

What Is Epoch?

Established in 2009, Epoch Research Institute India Pvt Ltd., is one of India oldest SAS Accredited training partner imparting SKILLS and TALENT DEVELOPMENT, offers multi-disciplinary LEARNING MANAGEMENT, TRAINING, on SAS to individuals, corporations, institutions, across pan India. It has become known, in particular, as a one of primer institute providing quality SAS Training over the years. Along with SAS we offer more than 150 programs  on ILT and e-learning platform.

In Addition to SAS Training Epoch also offers BUSINESS CONSULTING, STAFFING SOLUTIONS, & SAS SOFTWARE RESELL through its division “Epoch Technology & Consulting Services”. We state of art highly developed offshore and near-shore facilities, experienced team of domain specialists. Our innovative approaches to customer experience management & delivery has been a catalyst in sustaining long-term customer engagements. 

What is Big Data?

Big data is now a reality: The volume, variety and velocity of data coming into your organization continue to reach unprecedented levels. This phenomenal growth means that not only must you understand big data in order to decipher the information that truly counts, but you also must understand the possibilities of big data analytics.

Why is big data analytics important?

For years SAS customers have evolved their analytics methods from a reactive view into a proactive approach using predictive and prescriptive analytics. Both reactive and proactive approaches are used by organizations, but let's look closely at what is best for your organization and task at hand.

Reactive vs. proactive approaches

There are four approaches to analytics, and each falls within the reactive or proactive category:

Reactive – business intelligence: In the reactive category, business intelligence (BI) provides standard business reports, ad hoc reports, OLAP and even alerts and notifications based on analytics. This ad hoc analysis looks at the static past, which has its purpose in a limited number of situations.

Reactive – big data BI: When reporting pulls from huge data sets, we can say this is performing big data BI. But decisions based on these two methods are still reactionary.

Proactive – big analytics: Making forward-looking, proactive decisions requires proactive big analytics like optimization, predictive modeling, text mining, forecasting and statistical analysis. They allow you to identify trends, spot weaknesses or determine conditions for making decisions about the future. But although it's proactive, big analytics cannot be performed on big data because traditional storage environments and processing times cannot keep up.

Proactive – big data analytics: By using big data analytics you can extract only the relevant information from terabytes, petabytes and exabytes, and analyze it to transform your business decisions for the future. Becoming proactive with big data analytics isn't a one-time endeavor; it is more of a culture change – a new way of gaining ground by freeing your analysts and decision makers to meet the future with sound knowledge and insight.

With SAS, you can truly change operations, prevent fraud, gain competitive edge, retain more customers, anticipate disease outbreaks or run unlimited budget simulations – the possibilities are endless.

§  First off, if you have certified big data skills, the general consensus is that you will find a “competitive and thriving market.” That’s good news.

§  The most compelling statistic for SAS certification holders is that SAS grabbed two of the top 5 spots out of 60+ certifications surveyed. A full list hasn’t yet been released, but often follows the survey by a few weeks.

§  Over 730 certified individuals were surveyed and more than 40% hold two or more active big data certifications.

§  In the US, 52% of the respondents reported receiving a raise within a year after earning their first certification. The same goes for 35% of international respondents.

§  40% of respondents say they use the skills learned or enhanced through certification every day.

§  When asked “What was the first Big Data Certification you earned?,” 15% answered SAS Predictive Modeler, while 13% said SAS SBA Certification.

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SAS Big Data Analytics - EpochSASTraining

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SDTM & ADaM Domain Training Along With SAS Authorized Training At Epoch Research & Quartesian LLC.

Be a SAS Certified Professional with Clinical Domain training by Mentors of Epoch & Quartesian, also get 3 month paid internship on Clinical SAS.




As a clinical programmer, there are many paths to take. The main goal is always to access the data, manipulate and transform the data, analyze the data and report on the data. As a programmer, one can specialize in Data management (DM) programming and spend a majority of the time cleaning the data through edit checks and the creation of patient
listings and profiles. Another task of the DM programmer is to transform the data from its raw format into a standard format. This standard format could be the CDISC Study Data Tabulation Model (SDTM) that is requested by regulatory agencies upon submission of a new compound or it could be a sponsor’s own standards. In the process of transforming the data, the DM programmer must make sure that the output conforms to the standard and is compliant as well as valid So another part of the job is to write programs to check the data against the standard and run the programs whenever a new study is about to be analyzed.
 
CDISC end-to-end !
 
SDTM defines a standard structure for study data tabulations.
ADaM specifies the fundamental principles for the creation of analysis datasets .

In order to increase the efficiency of the drug development process, the Clinical Data Interchange Standards Consortium (CDISC) has developed a series of clinical study data standards to facilitate efficient transfer, access and review of clinical trial data. These standards include the Operational Data Model (ODM), the Study Data Tabulation Model (SDTM) and the Analysis Data Model (ADaM). This paper presents basic strategies and practical methods for creating SDTM domain data sets from clinical data management (CDM) system files. Before initiating the data mapping and conversion process it is crucial to have a basic understanding of the SDTM specifications. CDISC provides implementation guides for all of the CDISC data standards on their Website (www.cdisc.org). The SDTM Implementation Guide(SDTMIG)is an essential tool for anyone involved with the metadata mapping or programming associated with the creation of SDTM data sets. The SDTM Implementation Guide contains the specifications and metadata for all of the SDTM data domains and guidance for producing SDTM domain files. The SDTM is an evolving standard and it is important to ensure that everyone involved in the conversion process is adhering to the same version of the SDTM. It is also important to understand the difference in the version numbers for the SDTM standard and the associated implementation guide.

The Analysis Data Model (ADaM) document specifies the fundamental principles and standards to follow in the creation of analysis datasets and associated metadata. Metadata are “data about the data” or “information about the data.” The Analysis Data Model supports efficient generation, replication, and review of analysis results.

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Students visualize aircraft data in real time using SAS with Epoch Research Institute India Pvt. Ltd. (www.epoch.co.in)

What do you get when you combine analytics, aviation and the Internet of Things? A learning experience that leaves everyone flying high!
At Data on the Fly, 25 area high school students had the opportunity to learn how technology has changed – and continues to change – the aviation industry. The day began with a tour of the air traffic control tower at RDU International Airport. Students then gathered at the DOT hangar to hear about the day’s agenda and meet the team of volunteers who would walk them through the project.
Presenters from SAS, the Department of Transportation and the NC Science Festival shared their excitement about analytics and aviation, and it wasn’t long before the student teams were each digging into a small box of parts they’d been provided with. The final product was a Stratux aircraft monitoring device, which was assembled from a Raspberry Pi computer board, software radios and antennae.
The Stratux boxes were placed on the tarmac and immediately began receiving data from aircraft in the area. Information such as aircraft speed and altitude was bounced down and displayed on each team’s iPad via an app called Foreflight, and the teams were able to see their work come to life with the power of SAS Visual Analytics.

Volunteers show passion for aviation and analytics Karen Allen Lee, Senior Director of Internal Communications at SAS, pulled together volunteers from SAS to help organize the event, which she says couldn’t have happened without a great team effort. Senior Director of R&D Don Koch and Principal Implementation Project Manager John McNeill, both amateur pilots, were excited to participate.

“I’ve been around aviation as a hobby and information technology as a profession since well before these students were born,” McNeill said. “This event allowed me to bring the two together in a way that hopefully inspires them to consider a career that incorporates both.”

Alongside Lee, Koch and McNeill, SAS had five other employees volunteering as team leaders.
“I have a personal interest in both aviation and evangelizing STEM to students, and this event was a perfect combination of the two,” said Senior Manager of Software Development Michelle Proctor, one of the volunteers. “I especially liked seeing the light bulb go off for a young woman in my group. It’s moments like these that make every second of volunteering worthwhile.”
Another volunteer, Senior Associate Implementation Project Manager and student pilot Vatslav Orlov,  said. “It was enjoyable to watch the students’ curiosity bloom throughout the event with an increasing amount of great questions. The variety of fun activities will likely make a lifelong impact on how they view the world of data and aviation, showcasing the power of science and how two different disciplines can be intertwined with one another.”
It’s impossible to predict where the next great innovator might be hiding. But programs like Data on the Fly help spark an interest in STEM in young people. With a little luck, one of the 25 students who participated in the event might be inspired to study aeronautical engineering, or simply to think about a career that marries analytics and aviation. The sky really is the limit.
​
“Today we were able to provide an opportunity for high school students to have a hands-on experience with technology around IoT, big data and the power of analytics,” Lee said. “They gained a broad knowledge of how aviation data plays a big role in getting an aircraft to its destination, and how the FAA uses that data to help make critical decisions. And being that North Carolina was ‘First in Flight,’ an aviation-related project just seemed like a natural fit.”

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Data without analytics is data not yet realised (interview)

Dr Jim Goodnight, co-founder and chief executive of SAS, has been at the helm for the past 41 years. Under his guidance and some very astute management philosophies, the company has become the largest privately owned, pure-play company in the big data and analytics space.
And according to industry analysts’ reports, it’s also very much a leader in predictive analytics and machine learning solutions.
Throughout the Forum Dr Goodnight's name was used in revered tones. As Oliver Schabenberger, executive vice-president and chief technology officer said, “It may be SAS.com but it is really Jim.Goodnight.com – he has had such an amazing influence on the company”.
Goodnight admits SAS is now a little too big for him to totally oversee and he has selected some excellent VPs. How long will he continue? “As long as I am having fun and can make a difference,” he responded.
He is currently the head of an education task force with the chief executives of the Business Roundtable. There, he is focusing on helping children learn to read.
He was interviewed during the recent SAS Global Forum.

What are some of the biggest changes you have seen over the past 40 years?
After leaving the university environment all we hoped was to make it through the next year! That SAS has thrived and grown each year is a testament to the foresight, the corporate philosophy, and great people. In 2016, SAS made US$3.2 billion, had over 83,000 customers and over 14,000 employees.
SAS was doing analytics before it was cool. It can do so much more to effect change for good.
We are in the age of Analytics 4.0 and over 40 years we have had to reinvent ourselves on average every ten years. We started in 1969 writing in PL/1 for IBM 360 mainframes. Ten years later SAS needed to run on Vax/DG minicomputers. Ten years after that – 1989 - was the beginnings of democratisation of computing with the 16-bit IBM PC so we went there too. Now it is all about the cloud.
That meant a fundamental rewrite using C language and that was to become a real strength as it supported all platforms. One version of SAS and portability to different operating systems was way ahead of its time. It also marked the move of analytics to the data – we were able to use massively parallel PCs to give us the memory and processing capacity.
The next big change was the coming of the cloud and Viya is a cloud extension of SAS 9.4. It is for big tasks – high-performance analytics. It is both a superset and subset of SAS 9.4 – both platforms will continue to develop and interoperate but Viya allows you to use the power of the cloud – you can get up to 3 billion instructions per second and work on much larger data sets.
The next evolution is definitely about the rise of the machines. Analytics is not standing still – Machine learning (ML), Deep learning, Artificial Intelligence (AI), advances in insights, algorithmic intelligence, automation, and more.
Classic ML is data driven. Modern ML is where the algorithm acquires new skills by itself and that is where we are heading.
Oliver Schabenberger said we need to be careful not to label ML as AI. Is that your corporate direction?
Yes, our version of ML is about algorithms acquiring new skills. There is no computer powerful enough today to build the neural networks and approach AI status. Oliver called it algorithmic intelligence and that is more accurate.
As computer hardware increases in power and storage, what does that mean to SAS?
SAS has always had more capability than the machines it runs on so we welcome technology advances. Bigger, faster, more powerful hardware is good for SAS. It means we can solve bigger tougher problems. SAS capabilities still exceed even the biggest, fastest hardware of today.
The cloud is interesting as it potentially can link every computer together so bigger problems can be solved – That is Viya’s direction.
Tell me more about SAS visualisation techniques?
In the past analytical uses of data tended to be relatively flat – crosstabs and graphs could represent it.
Today data is multi-dimensional – you add your data to other sources and it is simply beyond human comprehension to think multi-dimensionally. Visualisation takes you so far but we need ML to reveal those hidden linkages and reveal insights.
Over the past 40 years we have seen visualisation go from standard X, Y charts to dashboards and scorecards but frankly these do not work for dimensional data – its big data in overdrive.
SAS uses a bucketing system to compress thousands of data points into perhaps 50 important ones that we can understand. We think that democratising visualisation techniques is where we can make the most difference to uncovering new insights – opening it up to everyone – not just data scientists.
You demonstrated on stage accessing SAS via Alexa. Is that the next logical step in analytics?
Anything that helps humans interact with data and analytics is a good step. By the way, SAS works with Siri, Cortana, Google Assistant and Bixby too. But these are nothing more than digital assistants and we think the “miss” rate is way too high for analytical use.
We plan to have our own analytics focused voice engine that will understand data, analytics and SAS.
Is SAS’s commitment to education a big overhead?
It has never been regarded as such. I think most CEOs of large companies have that responsibility. It takes the CEO to at least approve doing something like this.
We need to get people talking about analytics – data at rest is data not realised. Let’s just say that some 63 Universities now offer Masters Degrees in Advanced Analytics and 144 certifications. Between SAS University Edition and SAS OnDemand for Academics, there have been more than 1 million registrations and downloads of free SAS software for teaching, learning and research.
SAS training in Australia is the equal of any offered in the world and its certification program is recognised globally. Our commitment means that SAS is synonymous with analytics and people get well-paying jobs.
Where is SAS heading?
If analytics is the engine of change, data is the fuel. The opportunity is enormous and we need to bring analytics everywhere.
SAS has grown so much from my original vision, not in the technology sense but its uses. We can help analyse sports performance, reduce credit and financial fraud, address cyber security, solve marketing issues, reduce child abuse/neglect, use crowdsourcing (Gather IQ) to solve humanitarian issues, and one new area is Results as a Service to enable everyone to access SAS and pay for results.
The next decade of development is about machine learning, algorithmic intelligence, IoT and the masses of new data we will see generated by things like autonomous cars. I think there will be a move from using analytics in a reactive mode to a proactive mode – real-time.
Meanwhile, we will be looking 20 years ahead to begin to address emerging issues.
The writer attended the SAS Global Forum in Orlando, Florida, as a guest of the company.

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