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Statistical Application in R & Python: Normal Probability Distribution

Statistical Application in R & Python: Normal Probability Distribution

Gauss, the famous French Mathematician is responsible for developing one of the most significant distributions in all of statistics, i.e. – The Normal Distribution. Please refer to the blog on Central Limit Theorem: www.dexlabanalytics.com/blog/the-almighty-central-limit-theorem. It will help you fully grasp the significance of the Normal Distribution. However, if you want to revisit our series of blogs by following it from the start, you can reach STATISTICAL APPLICATION IN R & PYTHON: CHAPTER 1 – MEASURE OF CENTRAL TENDENCY right now!

Essentially, the Normal Distribution provides “approximations” to most other distributions such as the Binomial, Poisson, Gamma, Exponential, etc. This is to say as sample sizes get statistically large enough, most distributions approximate into a normal shaped curve.

Every distribution has important features known as its “parameters”. Normal distribution has two parameters. These are Mean ( ) and Variance (σ²). The normal distribution has a bell-shaped curve, where the probability of likelihood peaks at its mean in the middle.

The Normal Distribution has vast practical applications in the field of Business, Finance, Medicine, and Physics and so on. Things like weights, heights, IQ scores follow the Normal Distribution.

Normal Distribution, Gaussian distribution, is a continuous probability distribution and is defined by the Probability Density Function (PDF).

Where,

Application:

Assume that the credit score fits a Normal Distribution.

Suppose Mr. Arjun’s last 10 month’s credit score are:

789, 635, 739, 687, 724, 810, 817, 735, 819, 820

What is the probability that the percentage of credit score will 825 or more in the 11th month?

Months

Credit Score

January

789

February

635

March

739

April

687

May

724

June

810

July

817

August

735

September

819

October

820

 

Calculating Normal Distribution in R:

If we go to calculate Normal Probability Distribution in R, we can predict that the probability of the 11th month credit score will be 825 or greater than that is 14.60%, whereas in another case, the probability of the 11th month credit score will be 825 or less than that is 85.40%.

Calculate Normal Distribution in Python:

Make a data frame of the data and calculate Mean and Standard Deviation for calculate Normal Distribution.

Now, we can easily calculate Normal Distribution in Python

So, in calculating the Normal Probability Distribution in Python, we can predict that the probability of the 11th month credit score will be 825 or greater than that is 14.60%, whereas in another case, the probability of the 11th month credit score will be 825 or less than that is 85.40%.

Conclusion:

Normal Distribution is used for calculating parameters. It is represented by the bell curve, where the total area of the curve is 1. Normal Distribution has its use in Finance, Business, Salaries, Blood Pressures, Measurement etc and many other fields.

Here, we have used Normal Distribution to predict Mr. Arjun’s 11th month credit score, and set the target (825). By Normal Distribution we can predict the percentage of possibility to achieve the target.

Calculating Binomial Distribution might be tricky for many but with Dexlab Analytics it won’t be hassle anymore. So, get hold of our STATISTICAL APPLICATION IN R AND PYTHON: CALCULATING BINOMIAL DISTRIBUTION blog, to get around all your problems.

 

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Statistical Application in R and Python: Calculating Binomial Distribution

Statistical Application in R and Python: Calculating Binomial Distribution

In this blog, we will take a look at the Binomial distribution. This blog is among the series of blogs through which you’ll have a vivid idea of the Statistical Application using R and Python. Statistical Application In R & Python: Chapter 1 – Measure Of Central Tendency is the first of such blogs.

The binomial distribution is an extension of the Bernoulli distribution. In Bernoulli, we have only one parameter, i.e. the probability of success.

Now, consider a case where we have “n” number of trials and we want to predict the probability of success from it. This is the Binomial case.

Binomial distribution has two parameters, i.e.: number of trails (n) AND probability of success (p). The mean of the binomial is a product of its two parameters, i.e. n multiplied by p. It is a discrete probability distribution. Here, each trial is assumed to have only two outcomes, either success or failure.

If X be a discrete random variable (taking only non-negative values), it is said to be following binomial distributions with a probability mass function as:-


Application:

A food shop starts a offer for a festive season, They have 12 different baskets, each basket has 5 combos and only 1 of them is non-veg. Find the probability of having 4 or less non-veg combos, if a consumer tries every combos at random.

Since, only 1 out of 5 combos is non-veg, the probability of choose a non-veg combos by random is 1/5 = 0.2

Calculate Binomial Distribution in R:

In R the probability of one non-veg combos choose by random in 5 is 13.28%, whereas the probability of four or less combos choose by random in a twelve baskets is 92.44%

Calculate Binomial Distribution in Python:

In Python the probability of one non-veg combos choose by random in 5 is 16.66%.

Conclusion:-

Binomial Distribution is the process by which we can calculate the probability of success from “n” number of trails. In Binomial Distribution we can find only two outcomes like “Yes” or “No”.

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DexLab Analytics is Providing Intensive Demo Sessions in March

DexLab Analytics is Providing Intensive Demo Sessions in March

The internet has spurred quite a revolution – in several sectors, including education. Interested candidates are at liberty today to learn a vast array of things and garner a humongous pool of knowledge. Online demo sessions further add to the effect. These demo sessions are state-of-the-art and in sync with the industry demands. They are one of the most effective methods of learning and upgrading skills, particularly for the professionals. They transform the learning process and for all the good reasons.

DexLab Analytics is a premier data science training institute that conducts demo sessions, online and offline regularly. These demo sessions are indeed helpful for the students. With an encompassing curriculum, a team of experts and a flexible timing, the realm of demo sessions has become quite interesting and information-laden.

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Talking of online sessions, they are incredibly on-point and high on flexibility. With daring innovations in technology, no longer do you have to travel for hours to reach your tuition center. Instead, from the confines of your home sweet home, you can gain access to these intensive demo sessions and learn yourselves. Adding to that, the medium of learning is easy and user-friendly. The millennial generation is extremely tech-savvy that leaves no room for difficulties learning online.

Moreover, we boast of top-of-the-line faculty strength, well-versed in the art and science of data science and machine learning. With years of experience and expertise, the consultants working with us are extremely professional and knowledgeable in their respected field of study. Lastly, online demo sessions are great tools for career advancement. While working, you can easily upgrade your skills in your own time – boosting career endeavors further. The flexibility of learning is the greatest advantage.

This month, DexLab Analytics is organizing the following demo sessions; kindly take a note of the date and timing:

  • Demo session on Machine Learning, Deep Learning and Python – Saturday 16th March at 2 PM by industry professionals

  • Demo session on Data Visualization and Reporting – Saturday 23rd March at 11 AM by industry professionals

  • Demo session on Credit Risk Modelling – Saturday 16th March at 2 PM by industry professionals

For more information on big data Hadoop training in Delhi, follow DexLab Analytics.

 

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How Google Is Fighting Floods in India with AI

How Google Is Fighting Floods in India with AI

Of late, the search engine giant, Google made a slew of announcements tailor-made for India focusing on new-age technologies, including Artificial Intelligence and Machine Learning. They are to improve response time to natural disasters, such as flood along with address healthcare challenges.

At their recently conducted annual flagship conference Google For India 2018, the search engine giant also revealed the company is eager to use crisis response and SOS alerts to predict natural disasters. Speaking to the context, Rajan Anandan, VP, India and SEA Sales and Operations at Google stated that technology does come to rescue during extraordinary conditions.

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He further added, “India has gone online to rally behind the victims of the Kerala and Karnataka floods. Our Crisis Response team turned on SOS alerts on Google Search in English and Malayalam, and activated Person Finder to help people search for family and friends. Locations of flood relief resources like shelters are being shared on Google Maps. Outside of the tech support, Google.org and Googlers are contributing over $1 million to support relief and recovery efforts. And others are also donating towards the Kerala flood relief on Tez.”

Floods are ravaging; especially in countries India, Bangladesh and China. It’s for them that Google considered it’s high time to devise something to prevent disasters happening in these countries. Thus, the team started seeking ways to implement AI for flood prediction. The recent Kerala flood was an eye-opener. Hundreds have lost their lives and thousands are still living in makeshift relief camps. The numbers say more than 7.8 lakh people are said to be living in these camps across Kerala.

To offer help, Goggle has initiated a steady stream of measures to assist the state. It has activated SOS alerts on Google search, which hooked all the response numbers and emergency resources in languages, English and Malayalam.

Talking about the technology launch, Google Technical Project Manager (TensorFlow) Anitha Vijayakumar was found saying, “We have been doing AI research to forecast and reduce the impact of floods… Floods are the most common disaster on the planet, and with adequate warning, we can greatly reduce the impact of floods. The current modelling systems are only physics-based, and the data is not detailed enough, while Google is using a system that combines physics modelling plus AI learning, and combines that with elevation and satellite map data.”

In addition, “We also activated Person Finder in English and Malayalam, to help people search and track family and friends – on last count, there were 22,000 records in person finder. We also extended this information on Google Maps to aid the rescue efforts,” said Rajan Anandan, Vice President of Google (South East Asia and India).

He further added that Google Tez’s (the notable payment) donation drive has so far raised USD 1.1 million towards Kerala Chief Minister Relief Fund. Also, Googlers and Google.org has donated USD 1 Million for recovery schemes and relief measures.

Now, that you are reading this blog, it means you are interested in the broad scopes of artificial intelligence and power it brings with it. Get enroll in Big Data Hadoop training in Gurgaon; DexLab Analytics offer state of the art Big Data Hadoop certification courses that’ll take you a step closer to fulfilling your dreams.

 

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6 Indian Union Ministries That Are Using Artificial Intelligence

6 Indian Union Ministries That Are Using Artificial Intelligence

It’s no brainer; artificial intelligence has seeped deep into our lives and it has even caught the attention of Indian government. Indian government initiatives are proof of that. The NDA-led BJP government is an admirer of new technology and has given enough importance to AI by setting up an AI Task Force to arm India for the Industrial Revolution 4.0.

In fact, if you follow through a series of events or speeches, you’ll find how frequently our Prime Minister, Narendra Modi projects India and his government to be technologically-driven. In this blog, we’ll share how our top 6 Union Ministries are using Artificial Intelligence on a wider scale for better economy and powerful country presence:

Ministry of Defense

AI Task Force of the Ministry of Defense led by Tata Sons Chairman N Chandrasekaran filed its final report to Defense Minister Nirmala Sitharaman about employing AI for military superiority. The report includes recommendations regarding making India AI-empowered, both in terms of offensive and defensive needs, across naval, aviation, cyber, land, nuclear and biological warfare verticals.

NITI Aayog (the former Planning Commission)

The National Institution for Transforming India recently identified 5 sectors, namely ealthcare, agriculture, education, smart cities and infrastructure, smart mobility and transportation where profound importance will given towards AI implementation to serve societal needs.

Ministry of Information and Broadcasting

Recently, BECIL (Broadcast Engineering Consultants India Limited), functioning under the Ministry of Information and Broadcasting unveiled a tender showing the present government is more likely to take public opinion and media seriously. The government has chalked out a proposal for a respective “technology platform”, which would tap into public emotions by analyzing social media blogs, accounts, posts and even emails to promote nationalism and negate any media bickering by India’s adversaries.

Ministry of Railways

Indian Railways has been in a line of fire for its food catering services. Say thanks to Artificial Intelligence – AI is transforming the way the food is prepared. Not only is it revamping the entire food menu in trains but also promoting a greener environment by going bio-degradable and delivering food in environment-friendly containers.

Ministry of Home Affairs

First of its kind, Intelligence Traffic Management System is going to be installed by the Delhi Police, under the supervision of Home Ministry. This initiative will initiate smart traffic signals, with the help of AI and their first phase is going to be completed by April 2019.

Ministry of External Affairs

With intent to enhance the flow of information between countries, the Ministry of External Affairs had recently conducted a confidential meeting including global AI stalwarts to discuss how to drag attention of Indian Diaspora.

A quick bite: Niti Aayog, under the guidance of CEO Amitabh Kant has been a key stimulator of numerous digital campaigns across the country, including Aadhaar, encompassing biometric programme and India Chain Project.

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The blog has been sourced from – analyticsindiamag.com/7-indian-union-ministries-who-have-embraced-artificial-intelligence-big-time

 

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Cryptojacking: How Businesses Can Protect Systems from This Latest Cyber Threat

Cryptojacking: How Businesses Can Protect Systems from This Latest Cyber Threat

The rising threat of cyber attacks and the sophistication of these crimes have created a frightening security situation all over the world. The cases of data and privacy breach are increasing every day. Both private and public sector are at risk and understandably the average internet user is very paranoid. Cybercriminals keep innovating new ways to take advantage of security vulnerabilities present in systems.

Cryptojacking is one such cyber threat that has targeted countless unsuspected users all around the world. Particularly in India, cryptojacking has become a pressing problem. According to a recent study by Quick Heal Technologies, from January to May 2018, nearly 3 million cryptojacking cases have been reported.

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What is Cryptojacking?

Cryptojacking is a method of hacking into systems and illegally using them to mine cryptocurrency. Malicious scripts are loaded into machines without the knowledge of owners. The group or individual that loads the malicious program reaps the rewards of cryptomining activities, while the owner of the machine isn’t provided any kind of compensation.

There are two types of processes used to carry out cryptojacking attacks:

In the first process, a cryptomining code is installed in the compromised system by means of an infected file.

In the second method, a website or online ad is infected with a JavaScript-based cryptomining script. When users click on this link, the scrip auto-executes itself.

Why is Cryptojacking So Challenging for Businesses?

The malicious script transmits processing power from the compromised machine to the unauthorized cryptocurrency mining. This affects the computer in the following ways:

  • Slows down the system
  • Causes the machine to lag
  • Some applications become completely inaccessible
  • Resource-intensive operations related to cryptomining damage the hardware of an infected system and at times even cause it to crash repeatedly.

Cryptojacking is a serious business hazard. These disruptions result in downtime and IT tickets, which basically cost the business a lot of money. Global businesses lose billions of dollars due to IT downtime. Infected systems consume huge amounts of electricity and hence the operational costs increase significantly. Bottom line, cryptojacking eats away business revenues, which if taken precautions may be avoided.

How to Protect from Cryptojacking Attacks?

The modern cyber-attack landscape evolves every minute. In the face of such dynamism, it is absolutely essential to adopt a multi-layered approach for preserving IT security. The need of the hour is to invest in advanced security solutions. These solutions must include the following features:

Endpoint Security: In order to protect endpoints from cryptojacking a robust Endpoint Security solution with cutting-edge features like behavior based detection and antivirus is necessary.

Web Filtering: Web Filtering includes a set of tools that can be customized to safeguard your business network from suspicious websites. Distrustful websites are blocked and users are prevented from accessing them.

Network Monitoring: This is a tool that is able to detect huge surges in processor activity, which is a well-known symptom of a cryptojacked device. It helps network administrators keep a close eye on data anomalies.

Mobile Device Management (MDM): Business users depend on mobile phones for conveniently carrying out activities. Hence, deploying a robust MDM solution is important for preventing this type of hijacking.

Apart from these, businesses must ensure basic security hygiene, such as installing a web security solution for the safety of visitors on their website and also carry out patching of latest security updates. For example, SecBI has developed an artificial intelligence solution that analyzes network data and identifies cryptojacking threats.

For more blogs on the latest technical innovations, follow the premier big data Hadoop training instituteDexLab Analytics. Do take a look at the course details for big data Hadoop certification in Delhi.

 

Reference: cio.economictimes.indiatimes.com/tech-talk/how-businesses-can-secure-their-systems-from-cryptojacking/3175

 

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Tapping Into Big Data for Better Talent Acquisition

Tapping Into Big Data for Better Talent Acquisition

There are many variables that need to be considered while making hiring decisions. Most importantly, there’s need to fill skill gap. Other factors are candidate behavior and financial aspects of hiring, like cost for training new employees. Big data and analytics help form valuable insights into the job market. Consider the example of IBM acquiring the services of consulting firm Kenexa. It was used to access data of 40 million workers in order to find the personality trait most suitable for a sales job. All kinds of information starting from the workers’ job applications to managerial level was analyzed and it was determined that ’persistence’ is the most valued trait.

Here are some important ways big data helps firms attract promising candidates:

Automate HR Affairs

Talent Acquisition encompasses a wide variety of tasks and when HR teams work in tandem with AI then many day-to-day tasks gets simplified. It helps with tasks like filtering and tracking application status of candidates, getting new hires onboard and making future decisions about employees by analyzing data of previous employees. Data enabled systems saves a lot of time and makes tedious tasks much easier.

Predictive Analytics for Better Hiring Decisions

Hiring professionals need 360 degree information about a particular situation in order to make the best decision possible. They need to analyze everything starting from the human capital requirement in the organization to the economics. Big data enables them to form a clear idea about the skill gaps in the company’s workforce, analyze current trends in the market, follow the financial KPI’s and demographic traits associated with hiring, set the hiring quota and identify the skills and talents to look for in new hires.

Discard ‘’Eleventh Hour’’ Hiring Method

The urgency to fill skill gaps often pressurizes HR professionals to make quick hires, which can be impulsive and not the best. With the help of predictive analytics, these last minute situations can be completely avoided. It allows HR teams to form long-term hiring strategies that align with company goals and also enables them to make timely hires. Using the power of big data, you can be aware of the future needs of your company and job market trends. Hence, it helps eliminate panic situations where you make a hire only to realize later that he/she doesn’t fit the bill.

Social Media for Insights

Big data helps firms attract the right candidates that fit a role. The hard data available on the social media platforms of promising candidates and their search behavior online give organizations crucial information that help them make right decisions. Talent Bin is one of the many employment websites that use information from social media to form insights.

Targeted Job Ads

With the help of analytics, companies can create target groups and rope them in by showing relevant ads. For example, if there’s a financial service provider who enjoys a large talent network interested in marketing on LinkedIn, then they can take this opportunity to post marketing-specific job advertisements. Many potential candidates might find these posts engaging and the company will find the right fit for the job.

Wrapping up, we can say that big data has opened up fresh avenues to make better hires. The influence of big data in every aspect of the modern corporate sector is truly astounding. The smartest candidates are enrolling for big data courses to build skills that sell the most in today’s world of work. For expert-guided big data Hadoop training in Gurgaon, visit DexLab Analytics.

 

Reference: insidebigdata.com/2018/07/20/big-data-talent-acquisition-effective-synergy-make-better-hires

 

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#JobTrends: Open Data Analytics Jobs in India Is Set To Double in 2018

#JobTrends: Open Data Analytics Jobs in India Is Set To Double in 2018

Prediction says – the demand for AI and Big Data Analytics jobs is expected to hit 5.11 lakh, but professionals possessing the desired skills will number only 3.7 lakh by the end of 2018 – according to the National Association of Software and Services Companies (Nasscom). 

Further, the demand is expected to spike up to 7.86 lakh by the end of 2021.

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No wonder, the Indian IT industry is exploding with lucrative opportunities – 2018 began witnessing a steep rise in demand for skilled consultants specialized in the quarters of emerging technologies, like machine learning and artificial intelligence as well as big data and analytics. And, with a steady focus on Digital India, the IT recruitment industry is on its wheels to add 50% more workforce, resulting in another 1.80 to 2.0 lakh job creation by the end of this year.

Artificial Intelligence alone has the ability to generate 2.3 million jobs globally by 2020, says Alka Dhingra, GM, IT Staffing, TeamLease Services, a leading recruitment company. 

Revival of Indian IT sector

Since the technology is taking charge and rapidly transforming the every facet of business, the World Economic Forum has predicted a net loss of 5 million jobs in a couple of years. However, this leaves little room for worry, because job seekers and skilled professionals possessing the desired skills will be in a comfortable position to capitalize this trend and strive for better.

In this context, “Priority focus for us would be re-skilling the workforce in AI and big data,” says Debjani Ghosh, President, Nasscom, further adding, “Of the 4 million jobs in the industry, the nature of 60-65% is likely to change over the next five years.”

Quite interestingly, 1 out of 5 companies are found using AI to boost decision-making capacity. It help companies provide curated customized solutions and instructions to techies in real-time. Back in the day, traditional text analytics platforms were extremely complex; a handful number of companies were lucky enough to successfully analyze text data. But now, with Deep learning in AI, analysis of structured and unstructured text data has become a piece of cake – as a result of which, “We expect a 60 per cent increase in demand for AI and machine learning specialists in 2018,” shares BN Thammaiah, Managing Director, Kelly Services India.

Just like their job responsibility, the pay package of an AI professional breathes of adequacy – a techie with 2-4 years of experience earns 15-20 lakh INR annually, whereas 4-8 years of experience leads to 20-50 lakh INR annually. 

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New Streams to Consider

Retail, healthcare, telecom and manufacturing – these sectors are going to first witness the big data impact, followed by automobiles and FinTech. The next 5 years is going to be pivotal. Companies would be struggling hard to find and appoint AI engineers, especially for positions relating BI and Cloud for industrial automation. BlockChain is another new-age digital discipline that has started shifting focus and drawing attention across the e-com industry. It is found penetrating the sector, and for good reasons.

Now, if you are a data-enthusiast and seeking ways to reap benefits out of such a magnanimous tech-revolution? We got your back. DexLab Analytics offers state of the art Big Data training in Gurgaon at the best prices. Learn more.

 

The blog has been sourced from —

www.thehindu.com/business/Industry/ai-big-data-will-require-51-lakh-people-in-2018/article24534536.ece?utm_campaign=socialflow

www.thehindubusinessline.com/info-tech/big-data-machine-learning-ai-to-shape-job-market-in-2018/article10006991.ece

 

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The 8 Leading Big Data Analytics Influencers for 2018

The 8 Leading Big Data Analytics Influencers for 2018

Big data is one of the most talked about technology topics of the last few years. As big data and analytics keep evolving, it is important for people associated with it to keep themselves updated about the latest developments in this field. However, many find it difficult to be up to date with the latest news and publications.

If you are a big data enthusiast looking for ways to get your hands on the latest data news, then this blog is the ideal read for you. In this article, we list the top 8 big data influencers of 2018. Following these people and their blogs and websites shall keep you informed about all the trending things in big data.

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Kirk Borne

Known as the kirk in the field of analytics, his popularity has been growing over the last couple of years.  From 2016 to 2017, the number of people following him grew by 30 thousand. Currently he’s the principal data scientist at Booz Allen; previously he has worked with NASA for a decade. Kirk was also appointed by the US president to share his knowledge on Data Mining and how to protect oneself from cyber attacks. He has participated in several Ted talks. So, interested candidates should listen to those talks and follow him on Twitter.

Ronald Van Loon

He is an expert on not only big data, but also Business Intelligence and the Internet of Things, and writes articles on these topics so that readers become familiar with these technologies. Ronald writes for important organizations like Dataconomy and DataFloq. He has over hundred thousand followers on Twitter. Currently, he works as a big data educator at Simplelearn.

Hilary Manson

She is a big data professional who manages multiple roles together. Hilary is a data scientist at Accel, Vice president at Cloudera, and a speaker and writer in this field. Back in 2014, she founded a machine learning research company called Fast Forward labs. Clearly, she is a big data analytics influencer that everyone should follow.

Carla Gentry

Currently working in Samtec Inc; she has helped many big shot companies to draw insights from complicated data and increase profits. Carla is a mathematician, an economist, owner of Analytic Solution, a social media ethusiat, and a must-follow expert in this field.

Vincent Granville

Vincent Granville’s thorough understanding of topics like machine learning, BI, data mining, predictive modeling and fraud detection make him one the best influencers of 2018. Data Science Central-the popular online platform for gaining knowledge on big data analytics has been cofounded by Vincent.

Merv Adrian

Presently the Research Vice President at Gartner, he has over 30 years of experience in IT sector. His current work focuses on upcoming Hadoop technologies, data management and data security problems. By following Merv’s blogs and twitter posts, you shall be informed about important industry issues that are sometimes not covered in his Gartner research publications.

Bernard Marr

Bernard has earned a good reputation in the big data and analytics world. He publishes articles on platforms like LinkedIn, Forbes and Huffington Post on a daily basis. Besides being the major speaker and strategic advisor for top companies and the government, he is also a successful business author.

Craig Brown

With over twenty years of experience in this field, he is a renowned technology consultant and subject matter expert. The book Untapped Potential, which explains the path of self-discovery, has been written by Craig.

If you have read the entire article, then one thing is very clear-you are a big data enthusiast! So, why not make your career in the big data analytics industry?

Enroll for big data Hadoop courses in Gurgaon for a firm footing in this field. To read more interesting blogs regularly, follow Dexlab Analytics– a leading big data Hadoop training center in Delhi. Interested candidates can avail flat 10% discount on selected courses at DexLab Analytics.

 

Reference: www.analyticsinsight.net/top-12-big-data-analytics-and-data-science-influencers-in-2018

 

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