Category Archive: data science online learning

3 Stages of a Reliable Data Science Solution to Attack Business Problems

Today, businesses are in a rat race to derive relevant intuition and make best use of their data. Several notable organizations are skimming with cutting edge data science terms and resolving intricate problems (some being more successful than others).

 

3 Stages of a Reliable Data Science Solution to Attack Business Problems

 

However, the crux lies in determining the present stage of data science your organization has embraced, followed by ascertainment of the desired level of data science.

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Quantum Internet Is Now Turning Into a Reality

Quantum Internet Is Now Turning Into a Reality
 

Scientists across the globe are looking forward towards formulating new methods to realize ‘quantum internet’, an unhackable internet, which connects particles linked together by the principle of quantum entanglement. In simple terms, quantum internet will entail multiple particles striking information at each other in the form of quantum signals – but specialists are yet to figure out what it actually does beyond that. The term ‘quantum internet’ is quite sketchy at this moment. There’s no real definition of it as of now.

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Televisory Launches Data Analytics & Operational Benchmarking Platform

Televisory Launches Data Analytics & Operational Benchmarking Platform
 

Televisory, a start-up based out of India and Singapore, has launched its data analytics and operational benchmarking platform. The platform can measure real-time operational and financial performance of companies. While the firm has chosen to launch its platform from the US, its services are available globally.

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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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Business Intelligence: Now Every Person Can Use Data to Make Better Decisions

The fascinating world of Business Intelligence is expanding. The role of data scientists is evolving. The mysticism associated with data analytics is breaking off, making a way for non-technical background people to understand and dig deeper into the nuances and metrics of data science.
 
Business Intelligence: Now Every Person Can Use Data to Make Better Decisions
 

“Data democratization is about creating an environment where every person who can use data to make better decisions, has access to the data they need when they need it,” says Amir Orad, CEO of BI software company Sisense. Data is not to be limited only in the hands of data scientists, employees throughout the organization should have easy access to data, as and when required.

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Data Science: Is It the Right Answer?

‘Big Data’, and then there is ‘Data Science’. These terms are found everywhere, but there is a constant issue lingering with their effectiveness. How effective is data science? Is Big Data an overhyped concept stealing the thunder?
Summing this up, Tim Harford stated in a leading financial magazine –“Big Data has arrived, but big insights have not.” Well, to be precise, Data Science nor Big Data are to be blamed for this, whereas the truth is there exists a lot of data around, but in different places. The aggregation of data is difficult and time-consuming.

Look for Data analyst course in Gurgaon at DexLab Analytics.

Statistically, Data science may be the next-big-thing, but it is yet to become mainstream. Though prognosticators predict 50% of organizations are going to use Data Science in 2017, more practical visionaries put the numbers closer to 15%. Big Data is hard, but it is Data Science that is even harder. Gartner reports, “Only 15% organizations are able to channelize Data Science to production.” – The reason being the gap existing between Data Science expectations and reality.

Big Data is relied upon so extensively that companies have started to expect more than it can actually deliver. Additionally, analytics-generated insights are easier to be replicated – of late, we studied a financial services company where we found a model based on Big Data technology only to learn later that the developers had already developed similar models for several other banks. It means, duplication is to be expected largely.

However, Big Data is the key to Data Science success. For years, the market remained exhilarated about Big Data. Yet, years after big data infused into Hadoop, Spark, etc., Data Science is nowhere near a 50% adoption rate. To get the best out of this revered technology, organizations need vast pools of data and not the latest algorithms. But the biggest reason for Big Data failure is that most of the companies cannot muster in the information they have, properly. They don’t know how to manage it, evaluate it in the exact ways that amplify their understanding, and bring in changes according to newer insights developed. Companies never automatically develop these competencies; they first need to know how to use the data in the correct manner in their mainframe systems, much the way he statisticians’ master arithmetic before they start on with algebra. So, unless and until a company learns to derive out the best from its data and analysis, Data Science has no role to play.

Even if companies manage to get past the above mentioned hurdles, they fail miserably in finding skillful data scientists, who are the right guys for the job in question. Veritable data scientists are rare to find these days. Several universities are found offering Data Science programs for the learners, but instead of focusing on the theoretical approach, Data Science is a more practical discipline. Classroom training is not what you should be looking for. Seek for a premier Data analyst training institute and grab the fundamentals of Data Science. DexLab Analytics is here with its amazing analyst courses in Delhi. Get enrolled today to outshine your peers and leave an imprint in the bigger Big Data community for long.

Interested in a career in Data Analyst?

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Move Your Career towards Big Data Analytics: The Future Looks Bright

With state-of-the-art technology looming on the horizon, the $150-billion Indian IT industry has a high appetite for workers accomplished in the fields, like AI, Data Science, Big Data, and more.

 
Move Your Career towards Big Data Analytics: The Future Looks Bright
 

Soon, it wouldn’t be enough to flash an engineering degree or some minor knowledge in Java or Python – the need for data science and artificial intelligence is on the rise. Automation is going to be the key to change. Globally, 12% of employers have started thinking of downsizing their workforce owing to technological advancement. Amidst all this, don’t think India would be spared. Indian bosses fear automation will reduce their headcount too. But fret not, it’s not all a bad news – there is always a silver lining after rains and that is Big Data jobs.

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The Tides Of Change Is Here: Accenture’s Bhaskar Ghosh Talks About AI, IoT and Big Data

With the Fourth Industrial Revolution looming ahead, many would think that we are already in a digital economy era. Well, somewhat it holds true even. There are countless new apps and software programmes that help people hail a cab, make reservations in a hotel or mop floors by using robotic technology. Smart machines have become really smart to do a plethora of highly adept jobs, which would have been a little bit difficult on the part of humans to perform.

 
The Tides Of Change Is Here: Accenture’s Bhaskar Ghosh Talks About AI, IoT and Big Data
 

“While technology has long been developed to serve specific business needs, we are now in an era where people are central to the design and development of technologies,” stated Bhaskar Ghosh, group chief executive, Accenture Technology Services. In a recent interview with a leading financial magazine, he talked over Accenture’s Technology Vision 2017 and gave snippets about the latest trends and innovations that have become a pre-requisite to achieve success in the more-than-ever digitised economy.

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SAS and Equifax Clouts Deep Learning and AI to Improve Credit Risk Analysis

SAS and Equifax Clouts Deep Learning and AI to Improve Credit Risk Analysis

The noteworthy triumphs over us, humans, in Poker, GO, speech recognition, language translation, image identification and virtual assistance have enhanced the market of AI, machine learning and neural networks, triggering exponential razzmatazz of  Apple (#1 as of February 17), Google (#2), Microsoft (#3), Amazon (#5), and Facebook (#6). While these digital natives command the daily headlines, a tug of war has been boiling of late between two ace developers –  Equifax and SAS – the former is busy in developing deep learning tools to refine credit scoring, and the latter is adding new deep learning functionality to its bouquet of data mining tools and providing a deep learning API.

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Curiosity is Vital: How Machine Inquisitiveness Improves the Ability to Perform Smartly

What happens when a computer algorithm merges with a form of artificial curiosity – to solve precarious problems?

 
Online Data Science Certification
 

Meticulous researchers at the University of California, Berkeley framed an “intrinsic curiosity model” to make their learning algorithm function even when there is a lack of strong feedback signal. The pioneering model developed by this team visions the AI software controlling a virtual agent in video games in pursuit of maximising its understanding of its environment and related aspects affecting that environment. Previously, there have been numerous attempts to render AI agents’ curiosity, but this time the trick is simpler and rewarding.

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