Hadoop Archives - DexLab Analytics | Big Data Hadoop SAS R Analytics Predictive Modeling & Excel VBA

Fintech Companies: How They Are Revolutionizing the Banking Industry?

Fintech Companies: How They Are Revolutionizing the Banking Industry?

The world of technology is expanding rapidly. And so is the finance. Fintech is the new buzzword; and its extensive use of cutting edge algorithms, big data solutions and AI is transforming the traditional banking sector.

Nevertheless, there exist many obstacles, which fintech companies need to deal with before creating an entirely complementary system that covers the gap between both.

Ezbob and LaaS

Innovation takes time to settle, but with little effort, banks can strike gold than ever. New transparency laws and digital standards are being introduced and if banks are quicker in embracing this new technology, they can ring off success very easily. Not every fintech is determined to cause discomfort to banks, in fact a lot of fintech startups offer incredible services to attract new customers.

One of them is ezbob, a robust platform in partnership with multiple major banking institutions that streamlines an old process with cutting edge technology. This platform develops a smooth, automatic lending process for bank’s customers by sorting data accumulated from more than 25 sources in real time. Currently, it’s leading Lending-as-a-Service (LaaS) industry, which is deemed to be the future of banking sector.

LaaS is one of the key transforming agents that have brought in a new trend in the banking sector. It reflects how everyone can benefit, including customers and partners, when efficiency is improved. Real time decisions are crucial; it helps bankers turn attention to the bigger picture, while technology takes care of other factors.

2

The Art of Regulations

Conversely, fintech startups should be wary of regulations. Notwithstanding the fact that technology is fast decentralizing the whole framework and disrupting institutional banking sector, fintech companies should focus on regulation and be patient with all the innovations taking place around. Banks need time to accept the potentials of fintech’s innovation but once they do, they would gain much more from adopting these technologies.

The aftermath of 2008 financial crisis have made it relatively easier for fintech startups to remain compliant and be more accountable. One of the latest regulations passed is about e-invoicing, which require organizations should send digital invoices through a common system. This measure is expected to save billions of dollars on account of businesses and governments, as well.

Some of the other reforms that have been passed recently are mainly PSD2, which has systematized mobile and internet payments, and AMLD, which is an abbreviation of Anti Money Laundering Directive. The later hurts those who don’t want to be accountable for their income, or involved in terrorism activities.

Conclusion

As closing thoughts, we all can see the financial sector has been the largest consumers of big data technology. According to Gartner, 64% of financial service companies have used big data in 2013. And the figures are still rising.

To be the unicorn among the horses, it’s high time to imbibe big data hadoop skills. This new-age skill is going to take you a long way, provided you get certified from a reputable institute. In Delhi-Gurgaon region, we’ve DexLab Analytics. It offers state-of-the-art hadoop training in Gurgaon. For more information, drop by their site now.

DexLab Analytics Presents #BigDataIngestion

A Special Alert: DexLab Analytics is offering #SummerSpecial 10% off on in-demand courses of big data hadoop, data science, machine learning and business analytics. Enroll now for #BigDataIngstion: the new on-going admission drive!

 
The blog has been sourced from – http://dataconomy.com/2017/10/rise-fintechpreneur-matters
 

Interested in a career in Data Analyst?

To learn more about Data Analyst with Advanced excel course – Enrol Now.
To learn more about Data Analyst with R Course – Enrol Now.
To learn more about Big Data Course – Enrol Now.

To learn more about Machine Learning Using Python and Spark – Enrol Now.
To learn more about Data Analyst with SAS Course – Enrol Now.
To learn more about Data Analyst with Apache Spark Course – Enrol Now.
To learn more about Data Analyst with Market Risk Analytics and Modelling Course – Enrol Now.

10 Frequently-asked Hadoop Interview Questions with Answers

10 Frequently-asked Hadoop Interview Questions with Answers

A substantial part of the Apache project, Hadoop is an open source, Java-based programming software framework that is used for storing data and running applications on different clusters of commodity hardware. Be it any kind of data, Hadoop acts as a massive storage unit backed by gargantuan processing power and an ability to tackle virtually countless tasks and jobs, simultaneously.

In this blogpost, we are going to discuss top 10 Hadoop interview questions – cracking these questions may help you bag the sexiest job of this decade.

What are the components of Hadoop?

There are 3 layers in Hadoop and they are as follows:

  • Storage layer (HDFS) – Also known as Hadoop Distributed File System, HDFS is responsible for storing various forms of data as blocks of information. It includes NameNode and DataNode.
  • Batch processing engine (MapReduce) For parallel processing of large data sets across a standard Hadoop cluster, MapReduce is the key.
  • Resource management layer (YARN) Yet Another Resource Negotiator is the powerful processing framework in Hadoop system that keeps a check on the resources.

Why is Hadoop streaming?

Hadoop distribution includes a generic application programming interface for drawing MapReduce jobs in programming languages like Ruby, Python, Perl, etc. and this is known as Hadoop streaming.

2

What are the different modes to run Hadoop?

  • Local (standalone) Mode
  • Pseudo-Distributed Mode
  • Fully-Distributed Mode

How to restart Namenode?

Begin by clicking on stop-all.sh and then on start-all.sh

OR

Write sudo hdfs (then press enter), su-hdfs (then press enter), /etc/init.d/ha (then press enter) and finally /etc/init.d/Hadoop-0.20-name node start (then press enter).

How can you copy files between HDFS clusters?

Use multiple nodes and the distcp command to ensure smooth copying of files between HDFS clusters.

What do you mean by speculative execution in Hadoop?

In case, a node executes a task slower, the master node has the ability to start the same task on another node. As a result, the task that finishes off first will be accepted and the other one will be rejected. This entire procedure is known as “speculative execution”.

What is “WAL” in HBase?

Here, WAL stands for “Write Ahead Log (WAL)”, which is a file located in every Region Server across the distributed environment. It is mostly used to recover data sets in case of mishaps.

How to do a file system check in HDFS?

FSCK command is your to-go option to do file system check in HDFS. This command is extensively used to block locations or names or check overall health of any files.

Follow

hdfs fsck /dir/hadoop-test -files -blocks –locations

What sets apart an InputSplit from a Block?

A block divides the data, physically without taking into account the logical equations. This signifies you can posses a record that originated in one block and stretches over to another. On the other hand, InputSplit includes the logical boundaries of records, which are crucial too.

Why should you use Storm for Real-Time Processing?

  • Easy to operate simple operating system makes it easy
  • Fast processing it can process around 100 messages per second per node
  • Fault detection it can easily detect faults and restarts functional attributes
  • Scores high on reliability expect execution of each data unit at least for once
  • High scalability it operates throughout clusters of machines


The article has been sourced from
– www.besthadooptraining.in/blog/top-100-hadoop-interview-questions

 

Learn how Big Data Hadoop can help you manage your business data decisions from DexLab Analytics. We are a leading Big Data Hadoop training institute in Delhi NCR region offering industry standard big data related courses for data-aspiring candidates. 

 

Interested in a career in Data Analyst?

To learn more about Data Analyst with Advanced excel course – Enrol Now.
To learn more about Data Analyst with R Course – Enrol Now.
To learn more about Big Data Course – Enrol Now.

To learn more about Machine Learning Using Python and Spark – Enrol Now.
To learn more about Data Analyst with SAS Course – Enrol Now.
To learn more about Data Analyst with Apache Spark Course – Enrol Now.
To learn more about Data Analyst with Market Risk Analytics and Modelling Course – Enrol Now.

The Impact of Big Data on Marketing

The Impact of Big Data on Marketing

In marketing, the analysis of data is a highly established one but the marketers nowadays have a massive amount of public and proprietary data about the preferences, usage, and behavior of a customer. The term ‘big data’ points out to this data explosion and the capability to use the data insights to make informed decisions. Understanding the potential of big data presents various technical challenges but it also needs executive talent devoted to applying the solutions of big data. Today, the marketers are widely embracing big data and are confident in their use of analytics tools and techniques. Let us learn about the ways in which Big data and analytics can improve the marketing efforts of various businesses around the around.

Locating Prospective Customers

Previously, marketers had to frequently make guesses as to which sector of population comes under their ideal market segment but this is no longer the scenario today. The companies can exactly see who is buying and even extract more details about them with the help of big data. The other details include which buttons they generally click while on a website, which websites they visit frequently, and which social media channels they utilize.

Tracking Impact and ROI

Many retailers have introduced loyalty card systems that track the purchases of a customer, but these systems can also track which promotions and incentives are most effective in encouraging a group of customers or a single customer to make another purchase.

Handling Marketing Budgets

Because big data allows companies to optimize and monitor their marketing campaigns for performance, this implies they can allocate their budget for marketing for the highest return-on-investment (ROI).

Personalizing Offers in Real-Time

Marketers can personalize their offers to customers in real time with the combination of big data and machine learning algorithms. Think about the Amazon’s “customers also bought” section or the recommended list of TV shows and movies from Netflix. The organizations can personalize what promotions and products a particular customer views, even down to sending personalized offers and coupons to the mobile phone of a customer when he walks into a physical location. The role of Personalized Merchandising in the ecommerce industry will continue to increase in the years to come.

Improvement in Market Research

Companies can conduct quantitative and qualitative market research much more inexpensively and quickly than ever before. The tools for online survey mean that customer feedback and focus groups are inexpensive and easy to implement, and data analytics make the results easier to take action.

Prediction of Buyer Behavior and Sales

For the past several years, sales teams, in order to rate their hottest leads, have made use of lead scoring. But, with the help of predictive analytics, a model can be generated and it can successfully predict sales and buyer behavior.

 

2

Enhanced Content Marketing

Previously, the return-on-investment for a blog post used to be highly difficult to measure. But, with the help of big data and analytics, the marketers can effortlessly analyze which pieces of content are highly effective at moving leads via a sales and marketing funnel. Even a small firm can afford to use tools for implementing content scoring which can highlight the content pieces that are highly responsible for closing sales.

Optimize Customer Engagement

Data can provide more information about your customers which includes who they are, what they want, where they are, how often they purchase on your site, and how, when they prefer to be contacted, and various other major factors. The organizations can also examine how users interact not only with their website, but also their physical store to enhance the experience of the user.

Tracking Competitors

New tools for social monitoring have made it easy to gather and examine data about the competitors and their efforts regarding marketing as well. The organizations that can utilize this data will have a distinct competitive advantage.

Managing Reputation

With the help of big data, organizations can monitor their brand mentions very easily across different social channels and websites to locate unfiltered testimonials, reviews, and opinions about their company and products. The savviest can also utilize social media to offer service to the customers and create a trustworthy brand presence.

Marketing Optimization

It is quite difficult to track direct ROI and impact with traditional advertising. But, big data can help organizations to make optimal marketing buys across various channels and to optimize their marketing efforts continuously through analysis, measurement, and testing.

What is Needed for Big Data?

At this point, talent and leadership are the major things that big data needs. In most of the companies, the marketing teams don’t have the right talent in place to leverage analytics and data. Apart from people who possess analytical skills to understand the capability of big data and where to use it, companies require data scientists who can extract meaningful insights from data and the technologists who can develop include new technologies. Due to this, there is a high demand for experienced analytics talent today.

Big Data Limitations for Marketing

In spite of all the promise, there exist certain limits to the usefulness of big data analytics in its present state. Among them, the major one is the major one is the analytics tools’ and techniques’ complex “black box” nature which makes it hard to trust and interpret the output of the approaches of big data and to assure others of the accuracy and value of the insights generated by the tools. The difficulty of gathering and understanding data also limits the capability of marketing companies to more fully leverage big data. Beyond this, the marketers are identifying many hurdles to expanding their utilization of big data tools and they include lack of sufficient technology investment, the inability of senior team members to leverage big data tools for decision-making, and the lack of credible tools for measuring effectiveness.

Conclusion

Cloud computing is also playing a major role in marketing with the Cloud Marketing process. Cloud Marketing is a process that outlines the efforts of a company to market their services and goods online via integrated digital experiences. Once the data analytics tools become available and accessible to even the smallest businesses, there will be a much higher impact of big data on the marketing sector as there will be much broader utilization of data analytics. This can only be a boon as organizations enhance their marketing and reach their customers in innovative and new ways.

This article was produced by Savaram Ravindra, a content contributor at Mindmajix and not by the editorial team of DexLab Analytics, a leading Hadoop training institute in Gurgaon.

 

Author’s Bio: Savaram Ravindra was born and raised in Hyderabad, popularly known as the ‘City of Pearls’. He is presently working at Mindmajix.com. His previous professional experience includes Programmer Analyst at Cognizant Technology Solutions. He holds a Masters degree in Nanotechnology from VIT University. He can be contacted at savaramravindra4@gmail.com. Connect with him also on LinkedIn and Twitter.

 

Interested in a career in Data Analyst?

To learn more about Data Analyst with Advanced excel course – Enrol Now.
To learn more about Data Analyst with R Course – Enrol Now.
To learn more about Big Data Course – Enrol Now.

To learn more about Machine Learning Using Python and Spark – Enrol Now.
To learn more about Data Analyst with SAS Course – Enrol Now.
To learn more about Data Analyst with Apache Spark Course – Enrol Now.
To learn more about Data Analyst with Market Risk Analytics and Modelling Course – Enrol Now.

Is Change the Only Constant: How Analytics has Changed, while Staying the Same Over the Last Decade

Data analytics is evolving. Coupled with Big Data, it is changing the topography of almost everything.

 

Is Change the Only Constant: How Analytics has Changed, while Staying the Same Over the Last Decade

 

Each year, more and more companies are allocating their time and budget to exploit and understand vast pools of data strewn across them, both inside and outside company files. Of course, Big Data and Analytics is selling like a hot cake today, but what is its story of evolution? How the technology flourished 10 years back?

Continue reading “Is Change the Only Constant: How Analytics has Changed, while Staying the Same Over the Last Decade”

Top 10 Nifty Tools to Manage Big Marketing Data for Companies

Big Data is the latest buzz. It has to be effectively analyzed to formulate brilliant marketing and sales strategies. It’s of immense importance, as it includes humongous amount of information accumulated about customers from numerous sources like email marketing schemes and web analytics.

 
Top 10 Nifty Tools to Manage Big Marketing Data for Companies
 

However, due to the vast magnitude of information available, it may get quite difficult for marketers to analyze and evaluate all the data in an efficient way. Fortunately, plenty of tools are available in the market that can manage mammoth marketing data and here are few of them:

Continue reading “Top 10 Nifty Tools to Manage Big Marketing Data for Companies”

Big Data Salary Report 2017: A Gateway to a Great Career in Analytics

Big Data Salary Report 2017
 

In the US, big data engineer salaries are predicted to range between $135000 and 196000 in 2017, an increase of 5.8% from 2016 salary structure.  

 

In India, big data professionals are predicted to earn salaries in the range of 9.8L INR to 13.10L INR, increasing 6.4% over 2016 salary level.

Continue reading “Big Data Salary Report 2017: A Gateway to a Great Career in Analytics”

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?

Continue reading “Hadoop 2017: The Survivor and Not the Casualty”

The Future Is In Our Face! How Facial Recognition Will Change Marketing Innovation

big data facial recognition

Most us are taking a lot of technological marvels around us for granted these days. We have casually taken note of the things like how our smartphones now help us assign photos of people or organize them, or how Facebook usually knows the right people’s faces to tag. However, it has only happened recently, which most people have not realized, that this technology is not so much of a “cool trick” and will actually shape the way people are conducting their business endeavours.

These latest technological developments are already being tested out in several different industries and for a lot of different purposes. Like for instance, security scanners at the airports are now making use of this technology to allow the e-passport holders clear their customs faster. And with the further development in facial recognition technology, the border and customs officers will be able to recognize and weed out travellers with fake passports better.

Moreover, the facial recognition technology is now being implemented in several government facilities and businesses that require a higher level of security clearance. With the use of this technology, security professionals may easily run the real-time criminal searches with the use of CCTV footage.

2

Now if you are like us, and constantly purchase things online then you must be aware of the fact that your choice and even your face must be with them in their database as a part of your customer profile. But these days, major retailers in physical stores are using intelligent data and trying to up their game to compete with the shopping sites. This will help them target customers faster and help them provide offers specifically tailored to these people based on their buying preferences just like at online stores.

We have provided Big Data training for Snapdeal, so why not target your customers better with a Big Data certification?

Furthermore, such a technology can also be used to catch shoplifters red handed in the act, a system that Walmart has actually implemented in place in many of its stores

When your face as a customer shows up for the first time on their screens they will start to build a profile of yours, which will be based on your in-store actions. Like for instance, the amount of time one spends in a certain area, the path around the store and items that you choose to buy.

Even the entertainment industry, like theme parks, casinos, etc have already caught up in the use of this technology to not only target marketing activities, but also to keep an eye on suspicious activities. And when it comes to greater applications for facial recognition, like in the industries of banking and fintech we are only just scratching the surface.

Several industry insiders have agreed that facial recognition will allow marketers to effectively know their customers much better, the visitor photos stored may work as the cookies for referencing for identification and for storage of users as well. So, this technology can soon eliminate loyalty cards as an obsolete art.

The moment one walks into a store the staff will already have an idea of what they bought there when visited the store the last time, and thanks to the camera footage with the facial recognition technology, will provide the retailers with an advantage to keep up their pace with ecommerce giants like Amazon, Flipkart, Alibaba etc.

One may also use facial recognition to retarget their customers with several personal offers. Like you decide to buy a certain product at a certain store, but then leave as it is slightly over budget for you. Soon you may find an internet ad or a personal message about a good discount on that product from that retailer offering you a good deal. But for all this to take proper shape, there must be a strong backup strategy, which certainly plays a strong role when it comes to way people collect, use and store data of any kind.

Thus, this will begin a whole new chapter to targeted campaigns be it online or offline or both, through the leveraging of Big Data for even a single customer.

Big Data courses from the industry leaders now just a click away, with DexLab Analytics.

Big Data Hadoop training from Dexlab Analytics

 

Interested in a career in Data Analyst?

To learn more about Data Analyst with Advanced excel course – Enrol Now.
To learn more about Data Analyst with R Course – Enrol Now.
To learn more about Big Data Course – Enrol Now.

To learn more about Machine Learning Using Python and Spark – Enrol Now.
To learn more about Data Analyst with SAS Course – Enrol Now.
To learn more about Data Analyst with Apache Spark Course – Enrol Now.
To learn more about Data Analyst with Market Risk Analytics and Modelling Course – Enrol Now.

Credit Risk Managers Must use Big Data in These Three Ways

Credit risk managers must use Big Data in these three ways

While the developed nations are slowly recovering from the financial chaos of post depression, the credit risk managers are facing growing default rates as household debts are increasing with almost no relief in sight. As per the reports of the International Finance which stated at the end of 2015 that household debts have risen to by USD 7.7 trillion since the year 2007. It now stands at the heart stopping amount of a massive USD 44 trillion and the amount of debts increased in the emerging markets is of USD 6.2 trillion. The household loans of emerging economies calculating as per adult rose by 120 percent over the period and are now summed up to USD 3000.

To thrive in this market of increasing debts, credit risk managers must consider innovative methods to keep accuracy in check and decrease default rates. A good solution to this can be applying the data analytics to Big Data. Continue reading “Credit Risk Managers Must use Big Data in These Three Ways”

Call us to know more