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R Vs Python: A Debate Forever

R Vs Python: A Debate Forever

In this blog, we will bring forth the age old question and check which one is better, R programming and Python programming, when it comes to data science?

To be very honest, this question does not have a strict answer to it. However, in this blog we will lay down the key components of both the languages to give you a clearer picture. In the end, please decide for yourself and leave your comments in the section below.

The aim of this blog is to objectively put forward the pros and cons of both languages strictly from the perspective of data science.

We will discuss only about three main components, which are as follows:

  • Syntax
  • Performance
  • Applicability

There are other metrics, such as, trends in Industries and adaptation in the recent years which are beyond the scope of this blog. However, you can safely declare Python as the clear winner if those perspectives were concerned.

So let’s get started:

Syntax

Both R and Python are object-oriented languages. This is to say that everything is created as an object in which the information is mapped with the idea of using that object later in the analysis. However, when it comes to the syntax, i.e., the grammar of programming, R and Python are indeed very different.

R Programming

R programing is more suited to more seasoned coders who have prior experience of coding. The syntax is actually very similar to that of the previous languages, such as C, or C++ or Java and so on. The fundamental rules are that of C programming language. Also, use of semicolons is deemed optional in R. However, semicolons are necessary for multiple lines in a code inside a code block.

Deep Learning and AI using Python

Python

Python on the other hand, is the language more adaptable to the new generation of programmers. You can come from a non-programming background and still learn Python with relative ease.

Python is one of the most user friendly languages for the beginners. The syntax is designed to prioritize readability over preciseness of the code. In layman’s terms – coding in Python is very close to reading and writing with hand. In this regard, it is really popular amongst beginners in Data Science.

Performance

The performance is essentially measured by speed essentially when it comes to programming.

R Programming

As far as the general consensus goes R programming is much slower in terms of speed. The reason behind this is that R programming was initially designed to be used by statisticians for data analysis. Thus, R programming stresses more on precision than the speed.

Python

Python on the other hand, is relatively faster than R. Python offers the same level of precision whilst acting on a faster speed.

Note – The speed is taken into account independent of packages and libraries.

Applicability

Lastly, we will discuss the popular domains in which these languages are used.

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R Programming

As mentioned above, R was developed specifically for statisticians. For this reason, R is mainly used in various research organizations and academia in general. However, R is now quickly being absorbed in the enterprises as well, mainly because of its popularity and the availability of a large number of packages for statistical computation.

Python

Python is a gene

As Python is a general-purpose programming language we can use to build different kinds of applications. We can use Python to build web applications using popular frameworks like Django or Flask.

Lately, Python is becoming popular amongst data scientists as the language of choice given the simplicity of syntax, high speed and performance it has to offer. There has been a trend which has seen a sharp rise in the adaptability of Python over R in the last few years in Data Science.

So, there you have it folks. Decide for yourself now! We will meet you soon in the next blog.

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The Impact of Big Data on the Legal Industry

The Impact of Big Data on the Legal Industry

The importance of big data is soaring. Each day, the profound impact of data analytics can be felt across myriad domains of digital services – courtesy an endless stream of information they generate. Yet, a handful number of people actually ponders over how big data is influencing society’s some of the most important professions, including legal. In this blog, we are going to dig into how big data is impacting the legal profession and transforming the dreary judiciary landscape across the globe.

Importance of Big Data

Information is challenging our legal frameworks. Though technology has transformed lives 360-degree, most of the country’s bigwigs and institutions are still clueless about how to harness the power of big data technology and reap significant benefits. The men in power remain baffled about the role of data. The information age is frantic and the recent court cases highlight that the Supreme Court is facing a tough time taming the big data.

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However, on a positive note, they have identified the reason of slowdown and are joining the bandwagon to upgrade their digital skills and upend tech modernization strategies. Data analytics is a growing area of relevance and it must be leveraged by the nation’s biggest legal authorities and departments. From tracking employee behaviors to scanning through case histories, big data is being employed everywhere. In fact, criminal defense lawyers are of the opinion that big data is altering their courtroom approaches, which have always dominated the trials with a set of certain evidence. Today, the pieces of evidences have become digital than judicial.

Boon for Law Enforcement Officials

The technology of big data has proved to be a welcoming-change for the army of law enforcement officials; the reason being efficiency in prosecuting a large number of criminals in a jiffy. Officials can now scan through piles and piles of data at a super-fast pace and handpick scam artists, hackers and delinquents. Besides law enforcers, police officers are also identifying threats and rounding up criminals before they even plan to get way.

Moreover, the prosecutors are leveraging droves of data to summon up evidence to support their legal arguments in court. That’s helping them win cases! For example, of late, federal prosecutors served a warrant to Microsoft to gain access to their data pool. It was essential for their case.

Big Data Transforming Legal Research

Biggest of all, big data is transforming the intricacies of the legal profession by altering the ways how scholars research and analyze the court proceedings. For example, big data is used to study the Supreme Court’s arguments and we have discovered that arguments are becoming more and more peculiar in their own ways.

Such research tactics will largely lead the show as big data technology tends to become cheaper and more widely popular across the market. In the near future, big data is going to be applied in a plethora of industry verticals and we are quite excited to witness impactful results.

As a matter of fact, you don’t have to wait long to see how big data changes the legal landscape. In this flourishing age of round-the-clock information exchange, the change will take no time.

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The blog has been sourced from —  e27.co/how-big-data-is-impacting-the-legal-world-20190408
 

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Transforming Construction Industry With Big Data Analytics

Transforming Construction Industry With Big Data Analytics

Big Data is reaping benefits in the construction industry, especially across four domains – decision-making, risk reduction, budgeting and tracking and management. Interestingly, construction projects involve a lot of data. Prior to big data, the data was mostly siloed, unstructured and gathered on paper.

However, today, the companies are better equipped to utilize the power of big data and employ it in a better way. They can now easily capture data with the help of numerous high-end devices and transform the processes. In a nutshell, the result of implementing big data analytics is positive and everybody involved is enjoying the benefits – namely improved decision-making, higher productivity, better jobsite safety and minimum risks.

Moreover, using the previous data, construction companies now can predict future outcomes and focus on projects that are expected to be successful. All this makes big data the most trending tool of the construction industry and for all the right reasons. The sole challenge is, however, how businesses adopt these robust changes.

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Reduce Costs via Optimization

To stay relevant and maintain a competitive edge, continuous optimization of numerous processes is important. Big data lends a helping hand to ensure the efficacy of such processes by keeping a track of all the processes from first to the very last step – making them quick and productive. With big data technology, companies can easily understand the areas where improvements are required and devise the best strategy.

Needless to say, the primary focus of optimization is to reduce costs and unnecessary downtime. Big Data is by far tackling this concern well.

Worker’s Productivity is Important

Generally, when we discuss productivity in the construction industry, it mostly concerns technology and machines – leaving behind a crucial factor, humans. Big data takes into account each worker’s productivity. It is no big deal to track their work progress. In fact, it will help increase their productivity and boost efficiency.

Furthermore, when a lot of data is at hand, companies can even analyze how their workers are interacting to discover ways to enhance their efficiency levels by replacing tools and technologies.

The Role of Data Sharing

The construction industry is brimming with data. There is so much data here that it needs another capable organization to handle such vast piles of information. Among other things, companies need to share information with their stakeholders. They also need to strategize this data for better accessibility.

Ultimately, the main task of these companies is to eliminate data silos if they really want to savor the potentials of this powerful technology to the fullest. Till date, they have been successful.

In a nutshell, we can say that big data is positively impacting the whole construction industry and is more likely to expand its horizons in the next few years. However, the companies need to learn how to imbibe this cutting edge technology to enjoy its enormous benefits and sail towards the tides of success – because big data is here to stay for long!

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The blog has been sourced from —  www.analyticsinsight.net/how-big-data-is-changing-construction-industry

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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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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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6 Mind-Blowing Facts on Big Data Everyone Must Know

6 Mind-Blowing Facts on Big Data Everyone Must Know


The hot topic in today’s business world is Big Data. The ability to access and analyze the massive amount of data generated every second is crucial for the growth of a business. In this blog, we highlight the rapid growth in data and its significance in business decisions through some incredible statistics.

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  1. The amount of information man created from the dawn of civilization until 2003 is currently created every two days!

    And the instant messages, tweets and pictures you exchange every second contributes to this data. Ex CEO of Google, Eric Schmidt wonders if the world is ready for the big data-driven technological revolution that is imminent.

  1. 5 quintillion bytes of data are generated by internet users on a daily basis.

    If the data generated in a day was burned onto DVDs, the number would be so massive that it could be piled on top of each other to reach the moon twice!

  1. Out of all the data we create, only about 0.5% is analyzed and put to use.

There’s a huge amount of data that remains untapped. For all the Silicon Valley big shots, like Google, LinkedIn and Facebook, the aim is to link big data with personal data and create products that are highly personalized.

  1. 40,000 search queries are processed by Google every second and these add up to 3.5 billion searches each day and 1.2 trillion searches every year globally.

Google was founded in 1998 and back then it was catering to only ten thousand search queries every day. However, you shall be astonished after knowing that since 2006 more than ten thousand search queries have been performed through Google per second!

  1. Big data has the potential to create 6 million jobs in the U.S.

    LinkedIn’s head of data recruiting, Sherry Shah, described the big data job market as being ‘’very hot right now’’.

  1. A 10% increase in the data accessibility for Fortune 1000 companies is likely to increase their income by $65 million!

    And this is exactly why companies care so much about big data.

The job market for big data and analytics looks promising. Especially if you are fresher skilled in big data Hadoop then there’s a lot of scope for you. Compared to the current demand for professionals with Hadoop training, the number of available candidates is low. So, what are you waiting for? Enroll for Hadoop training in Gurgaon and grab amazing discounts on big data certifications.

 

This article has been sourced from:

ediscovery.co/ediscoverydaily/electronic-discovery/date-fun-facts-big-data-ediscovery-trends

 

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How Can Big Data Tools Complement a Data Warehouse?

How Can Big Data Tools Complement a Data Warehouse?

Every person believes that he/she is above average. Businesses feel the same way about their best asset— data. They want to believe that their big data is above average and perfect for implementing advanced big data tools. But, that’s not the case always.

Do you really need big data tools?

In the data world, big data tools like Hadoop Spark and NoSQL are like freight trains delivering goods. Freight trains are powerful, but they’ve limited routes and a slow start. They are great for delivering goods in bulk regularly. However, if you need a swift delivery, freight train might not be the best choice.

So firs of all, it is important to understand if there’s a big data scenario in your business or not.

A 100 times increase in data velocity, volume or variety indicates that you have a big data situation at hand. For example, if data velocity increases to hundreds of thousands of transactions per hour from thousands of transactions, or if the data sources shoot up from dozens to hundreds, you can safely conclude that your business is dealing with big data.

In such scenarios, you are likely to get frustrated with traditional SQL tools. A complete revamp or moderate tuning of existing big data tools is needed to effectively handle such massive data sets.

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What tools to use?

The tool to be used depends on the task at hand. For main business outcomes like sales, payments, etc., traditional reporting tools employed within the data warehouse architecture are suitable. For secondary business outcomes like following the customer journey in detail, tracking browsing history and monitoring device activity, big data tools within data warehouse are necessary. In a data warehouse these events are aggregated into models that show the summarized business processes.

Incorporating Big Data Tools in Data Warehouse

Consider an alarm company with sensors that are connected though the internet across an entire country. Storing the response of individual sensors in a SQL data warehouse would incur huge expenses, but no value. An alternative storage solution is retaining this information in data lake environments that are cheaper and later aggregating them in a data warehouse. For example, the company could define sensor events that constitute a person locking up a house. A fact table recording departures and arrivals could be stoked up in a data warehouse as an aggregate event.

There are many other use cases. Some are given below:

Sum up and filter IoT data: A leading bed manufacturing company uses biometric sensors in their range of luxury mattresses. Apache Hadoop could be used to store individual sensor readings and Apache Spark can be employed to amass and filter signals. The aggregated data in data warehouses can be used to create time-trended reports once the boundary metrics are surpassed.

Merge real-time data with past data: Financial institutes need live access to market data. However, they also need to store that data and use it for identifying historical trends in future. Merging these two types of data with tools like Apache Kafka or Amazon Kinesis is important because, with these tools the data can be directly streamed to visualization tools and there’s hardly any delay.

The ultimate goal is to form a balance between the two sides of the data pipeline. While it is important to collect as much raw data about customers as possible, it is equally important to use the right tool for the right job.

To read more blogs on the latest developments in the field of big data, follow DexLab Analytics. We are a premier Hadoop training institute in Gurgaon. To aid your big data dreams, we have started a new admission drive #BigDataIngestion where we offer flat 10% discount to all students interested in our big data Hadoop courses. Enroll now!

 

Reference: https://tdwi.org/articles/2018/07/20/arch-all-5-use-cases-integrating-big-data-tools-with-data-warehouse.aspx

 

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The Future of Humanity Lies in Big Data

The Future of Humanity Lies in Big Data

The World Economic Forum Annual Meeting 2018 was held in Davos, Switzerland. Here politicians, decision-makers from the world’s largest companies, and thought leaders come together to discuss about pressing global challenges. In this important platform, the opening words of historian, professors and famous author Yuval Harari were these— ‘’ we are probably the last generations of Homo sapiens.’’

He went on to explain that the new entities that humans will eventually evolve into will differ a lot more from the modern man than we did from our predecessors, the Neanderthals. However, the new species won’t be products of natural evolution of human genes, rather the result of humans engineering bodies and brains.

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Harari said that in future, the power will lie in the hands of those who control data. Data is the most important asset in the world and has redefined the prerequisites of power and dominance. Earlier, the ownership of land and subsequently machinery separated humans into aristocrats and commoners, capitalists and workers. However, in the modern age data is the determining asset. This is reflected in the biggest companies of the world. Out of ten of the leading companies in the world, six are tech firms that deal with enormous amounts of data, namely Apple, Microsoft, Amazon, Alphabet, Tencent and Facebook. The fact that these companies are only around two decades old suggests the role big data played in their growth.

Technology has advanced to the extent that data can be used to hack not just computers but also human beings. It takes only two things- data and computing power. Computing power is advancing with enormous speed. Today, the processing powers of mobile phones we use are greater than the best computers from a few decades ago. At the same time, digital information is ever increasing. Humans generate an average of 2.5 million terabytes of data in a day!

The data humans generate is mostly in unstructured form, especially the data that comes from online surveys and social media platforms. However, if analyzed, this data can reveal a lot about the personality of the person generating the data. It is layered with meaning and very open to interpretation. Understandably, analysts are focusing more and more on making sense of this unstructured data.

Hacking the human mind with algorithms

Through machine learning, smart artificial intelligence and deep learning, it is now possible to mine volumes of data and find patterns that earlier went unnoticed to human minds, which are ‘biologically limited’. Right kind of data and the power of computers can be utilized to develop algorithms that know more about people than they do themselves. After all, humans are just biochemical algorithms and the amalgamation of neuroscience and artificial intelligence has enabled the creation of algorithms that help understand the mechanics of human mind better than ever before.

In the words of Harari— ‘’As you surf the internet, as you watch videos or check your social feed, the algorithms will be monitoring your eye movements, your blood pressure, your brain activity, and they will know.’’

To read more blogs on big data, analytics and all the latest trends in these fields, follow DexLab Analytics. We are a leading institute providing Hadoop training in Gurgaon. Do take a look at our big data Hadoop certifications— we are offering flat 10% discount in these courses.

 

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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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