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How Big Data is Influencing the Sports Industry?

Imagine you have stepped off the field, and your team has lost. Obviously you can look at it as a failure, but if you closely introspect, you could look at it as an opportunity to improve. Why? Because of those embedded sensors in your jersey that are tracking your every move, and proper data analysis of that data will help you get better in the next game.

 
How Big Data is Influencing the Sports Industry?
 

Yes, you heard it right – data plays a key role in the world of sports. Collected data now guides team towards victory. Whether you are a cricket fanatic or a rugby supporter, you will find several instances that would show how big data is influencing this mega industry. Today, the professional sports industry stands at a whooping value of $90 billion – just as other industry domains are utilizing the power of big data and putting it to good use, why should sports industry lag behind? They also are looking for ways to enhance their athlete’s performance and improve organizations’ and fans’ total experience. Continue reading “How Big Data is Influencing the Sports Industry?”

Technology is Bringing off the Best for Students, Here’s how

Technology is omnipresent. And when it comes to imparting engineering education, technology is the meat and potatoes. Gone are the days of traditional teaching methods practiced within the walls of a classroom, following a set of particular curriculum. They have become a history. These days, technology-powered smart classes are in – they keep students enticed and hooked into learning. Laptops, smartphones and tablets have made gaining access to knowledge anywhere anytime downright easy. Not only that, access to education has enhanced versatility in the form of videos, audios and images that are available right at our fingertips through smartphones and tablets.

 
Technology is Bringing off the Best for Students, Here’s how
 

Technology is taking a new shape, each day. None other than ace modern engineers and scientists understands this better, and as a result, they try adopting innovative technologies for better, powerful future harnessing newer opportunities.

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5 Things to Consider While Using Data for Artificial Intelligence

Data is the most influential strategic asset for companies in a data-powered economy. Data is used to measure the ability of a business to perform notable tasks and operations, and draw significant insights through complex machine learning algorithms.

5 Things to Consider While Using Data for Artificial Intelligence

Gaining access to data is not a problem; but the real issue lies in having the right kind of data that helps companies remain on edge. A large number of them don’t even realize they are supplied with chunks and chunks of bad data, punched with wrong formatting, plenty of duplicates, having missing fields or irrelevant information.

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4 Ways in Which Data Scientists Can Add Value to an Enterprise

 
4 Ways in Which Data Scientists Can Add Value to an Enterprise

Data is everywhere. There is no shortage of data – even the neophyte entrepreneurs who have just begun their business operations are sitting on mounds and mounds of data – but this often makes us introspect how can we use data to grow bigger, more productive?

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5 Habits of Highly Successful Data Scientists

5 Habits of Highly Successful Data Scientists

Suppose, you have two resumes of two data scientists in your hands: A and B. Both of them possess similar backgrounds and expertise: qualifications, platforms, languages, frameworks, methodologies, industries and more. Theoretically, they are more like the same person – on paper. Yet there are few things that reflect that A is more successful than B – but how you determine that?

Here we’ve whittled down a set of habits or traits of successful data scientists that make them stand out from the rest of the pack.

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How AI Is Going To Change the Marketplace: Top 6 Trends to Fix Your Eyes in 2018

According to a recently published report from McKinsey – “Alphabet invested roughly $30 billion in developing AI technologies, and Baidu, which is the Chinese equivalent of Alphabet, invested $20 billion in AI last year.”

How-AI-Is-Going-To-Change-the-Marketplace

Not only companies, but reports suggest Chinese government is pursuing AI technology relentlessly in an attempt to drive the AI innovation, singlehandedly.

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Data Science Jobs: Luxury Today, Necessity Tomorrow

Data Science Jobs: Luxury Today, Necessity Tomorrow

A general consensus: the scene of employment is changing. The jobs in data science are spiking up, and at a robust rate. According to World Economic Forum in 2016, a nuanced state of affairs with employment fluctuations is likely to happen across sectors, jobs and geography in the coming years – hold your horses and wait with bated breath!

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Job Opportunities till 2020

A wide set of factors are expected to bring upon different effects on the varying segments of employment market till 2020. For an instance, recent demographic stats in the emerging job market are likely to ace up employment by 5% approx worldwide. On the other side, the surging geopolitical instability across the globe could reduce employment by 2.7%. Amidst this, artificial intelligence, touted as a replacement key for manpower is likely to have a minute effect on job reduction by a mere 1.5%.

Considerably, the overall figure points that the computing and mathematical jobs are going to increase by 3.2% – because a sturdy compilation of technological and geopolitical instability effect is expected to generate an altogether positive effect across various employment chains, suggesting the instability will in return result in a higher demand for programming, computing and modeling.

However, recruitment procedure is going to get more challenging.

Across every sector and every job family the perception is that recruitment will be more challenging in future #ai #sasacademic

Lower University application rates

Following the latest trends, the applications to universities by students have taken a halt – in UK, the number of people applying to universities has fallen drastically – the reason anticipated is the result of Brexit.

But irrespective of any reason, lower application rate is going to affect graduate recruitment. The emergence of a gig economy is largely considered a positive effort, but a lack of benefits like annual leave may cause some hindrance in the effectuality. Also, AI is resulting in a less number of job generation, the automation of entry-level jobs mean lesser jobs.

Hone your skills further after employment

While undergraduates and postgraduates eyes employment as the end of their education, for employers it’s an entirely different ball game. For them, employment is the just a stepping stone in the process of ongoing training to make sure the fresh workforce develops cutting-edge skills. This stands true especially in complex job areas of data science, where a shortage of graduates exists. As a result, motivate your existing workforce to develop required data analytics skills in the most accomplishing way to garner expertise and thorough know-how.

The most desirable quality in a new #DataScience hire is their dedication to continually learn more. #sasacademic #ai

To get the best kind of data science online training, drop by DexLab Analytics Delhi – it is a prime learning platform in India that helps you remain up-to-date with the latest tools and trends. The field of data analytics is evolving rapidly and continuing professional development is the need of the hour.

 
Source blogs.sas.com
 

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Artificial Intelligence: Let’s Crack the Myths and Unfold the Future to You

Artificial Intelligence: Let’s Crack the Myths and Unfold the Future to You

A lot of myths are going around about Artificial Intelligence.

In a recent interview, Alibaba founder Jack Ma said AI can pose a massive threat to jobs around the world, along with triggering World War III. The logic of shared by him explained that in 30 years, humans will be working for only 4 hours a day, and 4 days a week.

Fuelling this, Recode founder Kara Swisher vouched for Ma’s prediction. She supported him by saying Ma is “a hundred percent right,” adding that “any job that’s repetitive, that doesn’t include creativity, is finished because it can be digitized” and “it’s not crazy to imagine a society where there’s very little job availability.” 

Besides, I find all these stuffs quite baffling. I think that if AI is going to be the driving force towards innovation and bringing in a new technological revolution, it’s upon US to curate the opportunities that will require new jobs. Apocalyptic predictions just don’t help.

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Let’s highlight the myths and the logical equations:

Myth 1: AI is going to kill our jobs – it can never happen

Remember, it’s humans who have created robots. We excel at mechanizing, systematizing and automating. We spurred the automation drive, while infusing intelligence to the machines.

The present objective is to create AIs that can work together with human intelligence to develop new narratives for problems we are yet to solve. To solve these new problems, we need new kinds of jobs – there’s a great scope of opportunity, let’s not believe that AI will kill our jobs.

DexLab Analytics is here with its comprehensive machine learning courses.

Myth 2: Robots are AINot at all.

From drones to self-organizing shelves in warehouses to machines sent to Mars, all are just machines programmed to function.

Myth 3: Big Data and Analytics are AI. Who said that?

Data mining, Data Science, Pattern Recognition – they are just human-created models. They might be intricate or complicated in nature, but not AI. Data and AI are two entirely different and divergent concepts.

Myth 4: Machine Learning and Deep Learning are AI. Again a big NO.

Though Machine Learning and Deep Learning are a part of the enormous AI tool kit, they are not AI. They are just mere tools to program computers to tackle complex patterns- like the way your email filters out spam by “understanding” what hundreds and thousands of users have identified as spam. They look uber smart, undeniably, in fact scary at times, when a computer wins against a renowned expert at the game GO, but they are definitely not AI.

Myth 5: AI includes Search Engines. Definitely NO.

Search Engines have made our lives easier, undoubtedly. The way you can search information now was impossible few years back, but being the searcher, you too contribute the intelligence. All the computer does is identify patterns from what you search and suggest it to others. From a macro perspective, it doesn’t actually know what it finds because it’s dumb in the end. We feed them intelligence, otherwise they are nothing.

So, instead of panicking about the uncertainties that AI may bring into our lives, we should take a bow and appreciate the efforts humans gave into creating something so huge, so complex like AI.

And remember, AI has always created jobs in the past and didn’t take them. So, be hopeful!

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Data Journalism: What is it and how it works

The internet has killed some newspapers’ lunch, but it also presented them something truly remarkable – Data Journalism.

 
Data Journalism: What is it and how it works

Introducing Data Journalism

Data journalism is an amalgamation of a nosy reporter’s news sniffing capabilities and a statistician’s fondness for data analysis. By scrounging through vast amounts of data sets that are available through extensive connectivity, data journalists are using this data to etch out interesting stories.

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