Tag Archives: Big data certification

Data Science and Machine Learning: In What State They Are To Be Found?

Keen to have a sweeping view of data science and machine learning as a whole? 

Want to crack who is playing tricks with data and what’s happening in and around the budding field of machine learning across industries?

Looking for ways to know how aspiring, young data scientists are breaking into the IT field to invent something new each day?

Hold your breath, tight. The below report showcases few of our intrinsic findings – which we derived from Kaggle’s industry-wide survey. Also, interactive visualizations are on the offer.

  1. On an average, data scientists fall under the age bar of 30 years old, but as a matter of fact, this age limit is subject to change. For example, the average age of data scientists from India tends to be 9 years younger than the average scientists from Australia.
  2. Python is the most commonly used language programs in India, but data scientists at large are relying on R now.
  3. Most of the data scientists are likely to possess a Master’s degree, however those who bags a salary of more than $150K mostly have a doctoral degree under their hood.

Who’s Using Data?

A lot of ways are there to nab who’s working with data, but in here we will fix our gaze on the demographic statistics and the background of people who are working in data science.

What is your age?

To kick start our discussion, according to the Kaggle survey, the average age of respondents was 30 years old subject to some variation. The respondents from India were on an average 9 years younger than those from Australia.

What is your employment situation?

What kind of job title you bag?

Anyone who uses code for data analysis is termed as a data scientist. But how true is this? In the vast realm of data science, there are a series of job titles that can be pegged. For instance, in Iran and Malaysia, the job title of data scientist is not so popular, they like to call data scientists by the name Scientist or Researcher. So, keep a note of it.

How much is your full-time annual salary?

While “compensation and benefits” ranked a little lower than “opportunities for professional developments”, the best part remains it can still be considered a reasonable compensation.

Check out how much a standard machine learning engineer brings home to in the US

What should be the highest formal education?

So, what’s going on in your mind? Should you get your hands on the next formal degree? Normally, most of the data scientists have obtained a full-time master’s degree, even if they haven’t they are at least data analytics’ certified. But professionals who come under a higher salary slab are more likely to possess a doctoral degree.

What are the most commonly used data science methods at work?

Largely, logistic regression is used in all the work areas except the domain of Military and Security, because in here Neural Networks are being implemented extensively.

Which tool is used at work?

Python was once the most used data analytics tool, but now it is replaced by R.

The original article can be viewed in Kaggle.

Kaggle: A Brief Note

Kaggle is an iconic platform for data scientists, allowing ample scope to connect, understand, discover and explore data. For years, Kaggle has been a diverse platform to drag in hundreds of data scientists and machine learning enthusiasts, and is still in the game.

For excellent data science certification in Pune, look no further than DexLab Analytics. Opt for their intensive data science training in Pune and unlock a string of impressive career milestones.

Interested in a career in Data Analyst?

To learn more about Machine Learning Using Python and Spark – click here.
To learn more about Data Analyst with Advanced excel course – click here.
To learn more about Data Analyst with SAS Course – click here.
To learn more about Data Analyst with R Course – click here.
To learn more about Big Data Course – click here.

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Streaming Huge Amount of Data with the Best-Ever Algorithm

Can you measure water coming out of a fire hose, while it’s hitting your face? No? Then how would you calculate the amount of data that is constantly being churning out of numerous social media platforms? In simple terms, it’s not feasible, unless you opt for streaming algorithms – these are computer programs that execute such on-the-go calculations.

 
Streaming Huge Amount of Data with the Best-Ever Algorithm
 

Data flow is constant and humongous – in order to strategically record the essence, the rest of the data is mostly forgotten. A large pool of data scientists is constantly looking for ways to build a better, improved streaming algorithm, but now I guess their search has come to an end, they have invented something incredible to vouch for. This new, best-of-the-lot streaming algorithm performs miraculously by grasping just what it seems to be necessary, ignoring others. It remembers just that which it has seen the most, and that gives it an upper hand.

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DexLab Analytics Organized Mock Interview and Resume Building Workshop by Industry Expert

data science

A constructive mock interview and resume building session is a game-changer. Imbibing in-demand analytic skills is tough, but gearing up to crack high-flying job interviews is tougher. And DexLab Analytics addressed that point by curating an intensive resume building workshop on 20th October 2017. The session was headed by Mr. Tanmoy Ganguli, Program Director, DexLab Analytics at the Gurgaon centre in three time slots: 2-4 PM, 4-6 PM, 6-8 PM.

What is a mock interview?

Mock interviews prepare you for the real interview challenge. They enable the candidates to gain some notion about what sort of things they are going to experience during real interviews, while helping them deal with hard times. Often, these kinds of preparatory interview workshops are organized by data science training institutes in Gurgaon that seek ways to train their students to explore the wide vistas of job opportunities across various industry domains. DexLab Analytics is one such pioneering institute that takes the initiative to cater for the needs of its aspiring students, and these kinds of resume building sessions work wonders.

Over a period of time, DexLab Analytics has garnered a lot of good reputation based on the level of training they provide. The trainers working here are industry experts possessing all the needful knowledge regarding this particular field of study, hence learning from them would be fun. Their intensive data analyst courses and workshops are prepared in tune with the latest industry trends and development taking place, hence are high-on-value.

The best part of the story here is that the intensive resume building workshop was conducted by none other than our very own honorable program director, Mr. Tanmoy Ganguli. He has been in this industry for years, and possesses incredible expertise in the domains of SAS, Credit Risk Modelling and Regression Models. Being a key influencer, the sessions presided by him are a sure not-to-miss things for students.

What people learned from this session?

Resume building and mock sessions drastically reduce the anxiety levels. They equip the candidate with the needful interview questions that might be asked in the actual one. The interviewer and the trainer who conducts such events feed the candidate with needful responses that precisely tackles a candidate’s potentials and shortcomings. No one is perfect; hence the mock interview sessions help the candidates in becoming a better person, both knowledge-wise and skill-wise.

So, if you are one of them who want to pull up your career dreams of bagging the highest-paying job in the world of analytics, DexLab Analytics would be the right place for you. Right from imparting crucial skill-based knowledge to providing needful advice regarding how to crack a job interview, the event organized by DexLab Analytics is the best way to gather extensive knowledge to nail the best job in town!

Interested in a career in Data Analyst?

To learn more about Machine Learning Using Python and Spark – click here.
To learn more about Data Analyst with Advanced excel course – click here.
To learn more about Data Analyst with SAS Course – click here.
To learn more about Data Analyst with R Course – click here.
To learn more about Big Data Course – click here.

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Revising the Basics of Big Data Hadoop

Big data is a very powerful term nowadays. It seems to be a large amount of data. Big data means large amount of structured, unstructured, semi-structured data. We get data continuously from various data sources.

 
Revising the Basics of Big Data Hadoop
 

Just have a look on how we get data.

 

Nowadays we are living in a techno era in which we need to use technology so that’s why we are generating data. If you are doing any type of activity like – driving car, having some shakes in CCD, surfing internet, playing games, emails, social media, electronic media, everything plays a crucial role to develop big data. 

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How to Devise a Big Data Architecture – Get Started

How to Devise a Big Data Architecture – Get Started
 

Designing Big Data architecture is no mean feat; rather it is a very challenging task, considering the variety, volume and velocity of data in today’s world. Coupled with the speed of technological innovations and drawing out competitive strategies, the job profile of a Big Data architect demands him to take the bull by the horns.

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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?

To learn more about Machine Learning Using Python and Spark – click here.
To learn more about Data Analyst with Advanced excel course – click here.
To learn more about Data Analyst with SAS Course – click here.
To learn more about Data Analyst with R Course – click here.
To learn more about Big Data Course – click here.

Dexlab

Cyber Security Today: Curing Big Mobile Security Holes with Small Steps

You have employees? And they bring smartphones to work? Is everything right? Or wrong?

 

Period.

 
Cyber Security Today: Curing Big Mobile Security Holes with Small Steps
 

The moment an employee carries a personal mobile device, be it a smartphone or a tablet, to work, a merger of personal and professional is bound to happen. And this could definitely give a rough time to the employer. If not handled properly.

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Hadoop 2017: The Survivor and Not the Casualty

Hadoop 2017: The Survivor and Not the Casualty

 

Most people decipher – Hadoop and Big Data are the two sides of the same coin. Adding the fascinating word to your resume leads to better opportunities and higher pay structure. But what the future holds for Hadoop? Is it dismal or encouraging?

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6 FAQs to Get Acquainted With the Fundamentals of Big Data

By mobilizing the volume and wealth of information in an organization, Big Data leads to improved customer perceptiveness, competitive advantage and operational efficiency. In the current data-centric era, big data is the buzzword. Nevertheless, how many of you actually know what it entails?

 
6-FAQs-to-Get-Acquainted-With-the-Fundamentals-of-Big-Data
 

In this blog, we have compiled few FAQs, which will instantly shed some light about the basics of Big Data and its implementation.

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Attributes of Effective Data Monetization Strategy

The saying goes – ‘necessity is the mother of all inventions’ and with the advent of globalization we have witnessed this aphorism in its sincerest form. A new wave of competition and profit generation owing to the advent of the internet, within the labyrinth of our society has led to the creation of Data at a scale previously unthinkable. To capture the essence of this huge amount of data, a new term Big Data, was coined which meant extremely large data sets, which are to be analyzed to reveal patterns that lie within.

 
 Attributes of Effective Data Monetization Strategy
 

Today, technology has become the backbone of the society and data is its vertebrae. The technological boom began and became common around year 2000; this is when data monetization became apparent.

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